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Navigating Security: Opportunities and Challenges in the AI Era

Posted on by lucy lee

The new generation of AI poses both huge opportunities and risks. While AI can open up a world of new capabilities, it also presents new security concerns, that require our focus at three levels:

  1. LLMs Reliability
  2. Security risks posed by GenAI
  3. AI-powered security solutions

In this article, we will explore the new reality with AI in each of these areas.

LLMs Reliability

LLMs have demonstrated remarkable capabilities in natural language processing, but their reliability remains a concern. In 2023, researchers from Stanford University discovered that GPT-4 could generate highly persuasive disinformation articles that were difficult to distinguish from real news, highlighting ongoing reliability challenges with state-of-the-art language models. We see a growing number of companies addressing issues like biased outputs, hallucinations, and the potential for generating harmful content, through improved AI infrastructure like RAG and mechanisms to test and validate LLMs.

There are a few different methods enabling to test and promise the reliability of the LLMs in our usage, among them:

1. Red teaming: Actively trying to find ways to make the model produce undesirable outputs, to identify weaknesses. Companies like Anthropic, Halcyon, and Adept AI are using red teaming in their AI development processes. Startups like Haize Labs, Robust Intelligence, and Scale AI have products helping provide solutions to handle Red Teaming.

2. Oversight sampling: Regularly sampling outputs and having them reviewed by human raters for quality and safety issues. Startups like Fiddler AI provide solutions with humans in the loop to check for quality issues

3. Runtime monitoring: Analyzing model inputs and outputs in real-time to detect potential reliability issues. Guardrails AI, Galileo and TrueEra are building infrastructure for runtime monitoring of LLMs in production.

    Security risks posed by GenAI

    Generative AI introduces new security challenges. For example, deepfakes can produce highly realistic fake content, potentially leading to misinformation and fraud, and cybercriminals are leveraging tools like Midjourney and Stable Diffusion to generate synthetic media for social engineering attacks. Additionally, GenAI systems are especially vulnerable to unique threats:

    • Prompt injection attacks attempt to craft inputs that cause the model to ignore instructions and do something else, like disclosing sensitive data. In 2023, prompt injection was used to get GPT-4 to reveal training data.
    • Jailbreaking aiming to bypassing safeguards and performing unintended actions, like creating harmful outputs or giving illegal instructions.
    • Model integrity erosion happening when an AI system’s performance deteriorates over time due to adversarial or unforeseen inputs, corrupting the effectiveness of of AI driven security measurements.

    Companies like Flow Security (now CrowdStrike), Sentra, Protect.ai and HiddenLayers are developing solutions to protect data and models from unauthorized access and malicious activity. Cohere, Anthropic, OpenAI, Adept and others are exploring new AI architectures that are more resistant to prompt attacks and jailbreaking attempts.

    AI powered security solutions

    Alongside these risks, AI offers an outstanding opportunity to address security challenges like never before. AI-driven tools can enable high-quality observability, accurate detection, clear prioritization, and accelerated mitigation. Overall, AI can transform the way we handle and mitigate security risks today. Here are a few areas with significant potential for improvement in the new era of AI:

    1. Anomaly and Threat Detection: LLMs are designed to analyze large amounts of data and identify anomalies more efficiently than humans. This enables the creation of better alert systems that detect fraud and security threats effectively and in real-time. For example, Noname uses AI to identify data leakage, suspicious behavior, and API security attacks, as they happen. Redcoat AI and Abnormal Security identify phishing attempts and malicious email activity.

    2. Penetration Testing: AI-powered tools can be used not only to test the reliability of LLMs, as demonstrated by companies like Adept and Haize Labs, but also to perform intensive and sophisticated penetration testing on systems to identify vulnerabilities, as offered by XBOW. AI-driven simulations of cyber-attacks on networks and systems can test their resilience and train cybersecurity professionals in incident handling, regularly improving security layers.

    3. Code as language: While GenAI-generated code can raise concerns among tech leaders due to potential vulnerabilities and logical flaws, LLMs can read code as if it were natural language, enabling the identification of problematic code blocks and configurations that may lead to security breaches. AI-powered tools and security-oriented LLMs like Snyk DeepCode and Codacy embody the ‘shift left’ philosophy, focusing on identifying and resolving security issues early in the development lifecycle rather than addressing them post-deployment.

    4. Vulnerability Management and prioritization: AI can be highly effective in assisting engineers with intelligent security vulnerability management and prioritization. By creating a unified source of truth for existing security vulnerabilities and analyzing factors such as severity and potential impact, platforms like Wiz and Balbix offer advanced vulnerability management and prioritization, resulting in decreased engineers confusion and response time.

    5. Incident Response and auto mitigation: AI can significantly enhance incident response and automated mitigation, like applying security patches and updates to vulnerable software components in real-time, reducing the time required to contain and resolve security breaches. Solutions like Palo Alto’s Cortex XSOAR, also leverage AI to speed up incident investigation, automate and expedite tedious, manual SOC work, towards the vision of mitigating risks with minimal human intervention.

      While the breakthroughs in AI present exciting opportunities, it is crucial to address the risks related to AI models and security. By focusing on the reliability of LLMs, understanding the new threats posed by GenAI, and leveraging AI to enhance security measures, we can navigate this new era of technology safely. Are you building in this space? Let’s talk.

      Acknowledgements: I would like to thank Pear AI Fellow Libby Meshorer for significant contributions to this post, as well as Avika Patel and Pear team members Lucy Lee Duckworth, Arash Afrakhteh, and Jill Puente for contributing.

      Human Simulating AI Agents are Closest Approach to AGI, Unlocking Value in our Everyday Lives

      Posted on by lucy lee

      AI Agents: Turning Imagination into Reality

      After sharing our GenAI thesis and the 16 fields we are particularly excited about in AI, we’re delving into one of the most interesting trends in the era of capabilities unlocked by GenAI: AI agents, and, specifically, human simulating agents.

      AI agents are software entities that can perceive their environment, make decisions, and take actions independently without human supervision. They are the closest approximation we have today to the vision of Artificial General Intelligence (AGI), replicating a broad range of human cognitive abilities, including perception, reasoning, planning, learning, and adapting to new situations without dedicated preparation.

      AI Agents Add Value Across the Board

      The AI agents space can be divided into several key subspaces and categories, some of which we have already started investing in. One agent can have multiple overlapping functionalities and several interfaces simultaneously:

      AI Agents with Specific Functionalities

      • Human-simulating agents: These agents simulate human behavior and thoughts based on a given profile or need. These transformative approaches can be applied to various use cases, from companions that fight loneliness, to agents with demographic traits, beliefs, and preferences that help predict trends like election results or consumer adoption more quickly, cheaply, and accurately. See more in our section on Human Simulating Agents below.
      • Assistant agents: These agents can handle a wide range of tasks, from running an online search, or playing a song upon voice request (e.g. Siri and Alexa), to scheduling a doctor’s appointment and maintaining a detailed to-do list, as Ohai.ai and Martin do.
      • Automation agents: These agents connect two machines, identify gaps and repetitive processes, and create automated workflows to enhance them. For example, Orby AI, backed by Pear, automates workflows for enterprises in minutes, improving team efficiency by over 60%.
      • General purpose agents: While very broad and challenging to build effectively, these agents can complete multiple tasks across different verticals and complexity levels. Key players in this space include BabyAGI, AgentGPT and Personal AI, which offer solutions for various problems through their agents.
      • Vertical agents: Highly skilled in specific fields such as healthcare, marketing, gaming, legal, and more, these agents excel in their respective areas. A promising code generation agent and engineering co-pilot is Devin, built by Cognition AI, which enables engineers to plan and execute complex engineering tasks.
      • Embodied agents: Embodied agents operate on edge devices such as IoT devices, robots, and drones, as navan.ai does. They enable smarter and more independent decision-making and actions, aiming to improve smart home systems, agricultural practices, defense, and more.
      • Collaborative agents: These agents can interact effectively with other agents, learn from each other, and cooperate to improve their performance and execution over time. Relevance AI is building such solutions to increase team productivity.

      Agents with Defined Interfaces

      • Human Facing Agents: interact with humans through text, audio, video, etc., just like Google Astra does to help people navigate their surroundings.
      • System Facing Agents: Interact with machines and systems through APIs, scripting, and data.
      • Physical world facing agents: interact with the physical world, learning and interacting with it through robots, drones, and automotive, as Tesla autopilot and Weymo.

      Agents Infrastructure

      Agents infrastructure will include ops layers that encompass memory, compute and data infrastructure. Additionally, new agent management platforms will emerge, enabling building, orchestration, observability, and monitoring. Companies like Dust and AgentOps aim to offer these solutions to help agents and their operators achieve their full potential.

      Human Stimulating Agents: Revolutionizing Customer Support, Trend Predictions, and More.

      Human simulating agents allow us to leverage AI to learn from and predict human behavior in different scenarios. There are two broad categories of Human Simulating Agents:

      Support agents

      • Assistants: As mentioned above, AI assistants can simulate human behavior while supporting us. For example, they can order and adjust our grocery lists based on our historical needs and preferences, declutter our email inboxes, and respond in our unique writing styles. They will interact with us in natural language, as if we were asking for help from a close friend, helping us manage our busy lifestyles.
      • Customer support: AI agents in the customer support space will become more sophisticated, providing relevant and satisfying support that saves man-hours, reduces customer frustration, and cuts costs for customer-facing companies. Sierra, Crescendo and yellow.ai are already on a mission to transform the customer support experience using AI agents.

      Human persona agents

      • Trend predictions: Agents will simulate people with specific demographic contexts, traits, and perspectives to predict the adoption of new consumer products, as Keplar and subconscious.ai do, create the most effective personalized marketing content, predict election results, and more. 
      • Companions: AI agents can become companions with personality and relationship history, remembering key moments in our lives, fighting loneliness, and offering initial mental health support if needed. For example, Replika and Kindroid provide engaging relationships with customizable AI companions that users can interact with through text and voice.

      Building in this space?

      If you are building in the agents space, reach out to us (Arash or Arpan). We would love to discuss your vision and explore how we can support your journey.

      Acknowledgements: I’d like to thank Pear AI Fellow Libby Meshorer for significant contributions to this post as well as Pear team members Arpan Shah, Jill Puente, and Lucy Lee Duckworth for contributing.

      Pear Biotech Bench to Business: insights on ‘Designer Immune Systems,’ allogeneic stem cell therapies, and making an impact on the lives of patients with Ivan Dimov

      Posted on by jill

      Here at Pear, we specialize in backing companies at the pre-seed and seed stages, and we work closely with our founders to bring their breakthrough ideas, technologies, and businesses from 0 to 1. Because we are passionate about the journey from bench to business, we created this series to share stories from leaders in biotech and academia and to highlight the real-world impact of emerging life sciences research and technologies. This post was written by Pear PhD Fellow Sarah Jones.

      Today, we’re excited to share insights from our discussion with Dr. Ivan Dimov, CEO and co-founder of Orca Bio. Ivan has co-founded three high-tech companies and two R&D centers, and he is now working to make next-generation cell therapies safer and more efficacious at Orca.

      More about Ivan:

      Ivan earned a Ph.D. in Applied Biophysics from Dublin City University and has since worked as a postdoc at UC Berkeley and as a visiting instructor and senior scientist at Stanford. His passion for translating his work and his tech-heavy background have made him an expert in electronics and bio-microelectromechanical systems (bio-MEMS) and have helped him to work on numerous projects and companies including Blobcode Technologies, Lucira Health, and Orca Bio. 

      If you prefer listening, here’s a link to the recording! 

      Insight #1: Instead of building a technology and then searching for the right application, it’s much more efficient to identify the right problem prior to creating a solution. 

      • There are many approaches to starting a company and making new, impactful discoveries. As someone with a strong tech and engineering background, Ivan was trained to find and create interesting, powerful new technologies and go hunting for applications; he made hammers and went searching for nails. 
      • However, when working with Dr. Irv Weissman at Stanford as a postdoc, Ivan learned to do things a little differently. 
      • Though Ivan’s background was primarily in applied biophysics and bioengineering, the Weissman lab’s focus was medicine and biomedical research. Ivan acknowledged that when you work in medicine, you are exposed to an over-abundance of problems, and in this environment, Ivan learned that the most effective solutions are those that are tailor-made to fulfill a clearly defined need. 

      Working with physicians was a huge change in mentality for me…you’re seeing suffering everywhere and you have all these problems, and you sort of have to figure out, okay, which problem do you want to focus on, and what’s the best solution or technology you can come up with for that problem? I think that’s probably the better way of doing innovation…rather than trying to squeeze in some technology that was thought of in a different context and trying to make it work.

      • One such problem was related to the poor outcomes of stem cell transplants, a procedure in which a donor’s stem cells are harvested and administered to a recipient. Ivan explained that there wasn’t a way to sort out the good cells from the bad and ensure that the recipient was only receiving cells that would therapeutically benefit them and minimize unwanted side effects. 
      • The idea of creating precise and well-defined stem cell therapies would become the central theme of Ivan’s work at Stanford and later of Orca Bio.

      Insight #2: Academia is great for exploring, learning, and making mistakes. However, industry is where you can iron out the more mundane details of company creation and focus on impact and real-world use cases.  

      • Having started three companies–Blobcode Technologies, Lucira Health, and Orca Bio–Ivan has extensive experience in taking ideas from academia to industry. 
      • Lucira Health, a diagnostics company that has since been acquired by Pfizer, was spun out of Ivan’s work at Berkeley. The goal was to miniaturize a microfluidic chip that could be utilized as an at-home diagnostic. Notably, the company received approval from the FDA for their at-home COVID test that could read out results in about 30 minutes.
      • While at Berkeley, Ivan spent time fine-tuning the idea and conducting proof-of-concept experiments for the chip. However, it became apparent that this academic setting wasn’t necessarily conducive to the less thrilling aspects of the project. Spinning out and starting Lucira allowed the team to more efficiently work on the ‘mundane’ details like reproducibility and clinical trial design.

      [Academia is a safe place where] there’s a lot of openness to trying out new things… and the greatest thing about it is that you can try it and you can make a mistake and that’s okay. You can come up with a better alternative.

      • While Ivan agrees that academic labs are a great place for ideation and company incubation, it’s important to be vigilant and humble enough to realize when it’s time to take the next step. Industry and academia each have their respective strengths, and Ivan learned that both were crucial to the growth and future success of his companies.

      Insight #3: Stem cell therapies don’t have to be so risky: by cherry-picking the cells that a patient receives, long-term outcomes can be significantly improved.

      • In leukemia, cells in the bone marrow and lymphatic system become cancerous and rapidly multiply. To treat this type of malignancy, patients often go through multiple rounds of chemotherapy, radiation, or targeted immunotherapy and may receive an allogeneic stem cell transplant. 
      • Essentially, a conventional allogeneic transplant begins when the patient receives chemotherapy and/or radiation to wipe out all of the cancerous blood cells together with the patient’s healthy blood and immune cells. Once the cancer can no longer be detected, stem cells from the bone marrow of a healthy donor will be administered. These new cells can multiply and grow into mature, functioning blood and immune cells.
      • For some patients, this treatment is curative and wipes out any trace of cancer from their systems. However, even after chemotherapy and radiation, some cancer cells may go undetected and cause a patient to relapse.

      The problem with cancer is that if you leave even a little bit of it behind, even a single cell that hides and survives, it has the potential to reinitiate and restart your cancer from scratch… When you get into full remission–meaning we can’t measure any more cancer in you–it just means that our tests aren’t sensitive enough to see if it’s there or not there.

      • Once the stem cell transplant is complete, it takes a couple of weeks for the new immune and blood systems to get up and running. The hope is that these new immune cells can wipe out any remaining cancer cells that may be hiding out. 
      • In addition to the potential for relapse, patients frequently develop either acute or chronic Graft-vs-host-disease (GVHD), complications in which the new immune cells from the donor start to attack the patient’s (host’s) own cells and tissues. GVHD can affect many parts of the body and can even lead to death. 

      In a standard transplant, your chances of surviving for twelve months free of relapse or free from GVHD is somewhere around 30-40%. With Orca Bio… we can get rates somewhere between 70-80% ideal survival rates.

      • So how do they do it? Ivan’s goal at Orca Bio is to revolutionize the cell therapy space by creating a high-precision cell therapy that gives patients only the most efficacious donor cells. 
      • Orca’s unique platform identifies and sorts for donor cells that have the highest therapeutic benefit. By removing cells that either harm or don’t help the patient, the patient’s chances for relapse or developing GVHD are dramatically reduced.
      • With what they call their ‘designer immune system,’ Orca’s approach aims to help patients recover more quickly, prevent relapse, and be safe enough for older or sicker patients who can’t receive traditional stem cell transplants.

      Insight #4: To solve the problems of current allogeneic stem cell transplants, you have to balance killing the remaining cancer cells with protecting the patient’s own tissues and cells.

      • When designing an immune system to infuse into patients with blood cancer, it can be difficult to kill cancer cells without harming other cells in the patient’s body. 
      • In a healthy immune system, cells called regulatory T cells (T-regs) monitor and regulate what effector T cells are doing. Such effector T cells can help promote inflammation and eliminate cancer cells. However, when a patient has cancer, there is an imbalance between these two cell types, and the immune cells don’t effectively kill the cancer cells. 
      • These types of cells are often involved in autoimmune disorders and can also play a role in the development of acute GVHD shortly following the stem cell transplant or in chronic GVHD, long after the treatment has concluded. 
      • Orca Bio’s first product, Orca-T, helps to restore balance in the immune system by first bringing stem cells and T-reg cells into the patient’s body to let them set up the immunoregulatory environment. Once the T-regs and stem cells have had a chance to settle in and begin restoring the patient’s immune and blood systems, conventional T cells with cancer-killing capabilities are administered.
      • Orca-T has reached Phase III clinical trials for indications such as acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), acute lymphoid leukemia (ALL), and mixed-phenotype acute leukemia (MPAL) in patients with matched donors who are younger than 65. Matched donors are those that share the same human leukocyte antigen (HLA) profile, and this means that these cells are less likely to be identified as intruders in the patient’s body, thus reducing the risk for GVHD.
      • Patients receiving Orca-T first receive chemotherapy and/or radiation to target cancer cells and suppress their immune systems. The first dose of Orca-T is an infusion of stem cells that regenerate the blood and T-regs that help set the immune landscape. Two days later, the patient receives an infusion of conventional T cells that can begin to attack any remaining cancer cells. 

      What’s amazing about this approach is that by doing that, you’re not turning off the effector T cells from destroying the cancer. You’re just turning off alloreactivity in the key organ sites where you might create GVHD, but you’re still keeping it on for wherever the cancer might be.

      • Moving forward, the company is continuing its work on Orca-T by expanding the age range of patients who can be treated with the drug.
      • The pipeline also includes next-gen cell therapy treatment, Orca-Q.
      • To solve the problem of limited matched donor availability, Orca-Q is a high-precision cell therapy that has been tailored for haploidentical, or half-matched donors. These donors are typically parents, children, or siblings and can be much easier to find. However, the risk for GVHD increases with a half-matched donor compared to a fully matched donor.
      • Orca-Q has so far shown positive results in Phase I in oncological indications and is being investigated for autoimmune and hematological indications, as well. 

      Insight #5: Sometimes science is personal: reflecting on Orca’s journey, Ivan and his team have a deep understanding of how their work can change lives.

      • Having treated more than 400 patients so far, Orca has seen firsthand how patients can benefit from their novel stem cell transplants. 
      • In particular, patients who are too old or too sick for traditional transplants now have a fighting chance.

      One of the most incredible stories was about my co-founder’s [Nate Fernhoff’s] father-in-law. He was 71 years old when he was diagnosed with myelodysplastic syndrome. He had an aggressive variant of the disease…however, physicians feel very skittish about treating folks at that age with a myeloablative allogeneic bone marrow transplant, so they’re offering a reduced protocol [with a much worse chance of controlling the cancer]. We started looking for clinical trials, anything that would cover folks of that age.

      • Dr. Fernhoff’s father–in-law, Mikhail Rubin, was diagnosed with a rare form of blood cancer and found that his options for treatment were extremely limited. The most successful and aggressive forms of treatment were offered only to younger patients. 
      • Meanwhile, Orca’s clinical trials had so far proven to be safe and effective. The Orca team sprang into action and started working to convince physicians and the FDA to allow them to treat patients older than 65 and expand the enrollment criteria for the trial.
      • Ivan noted that this exclusion of the most dire patients stems from the industry’s hesitancy to add further risk to clinical trials.

      In April of 2021, we were given the permissions, and were able to treat him. It’s been a phenomenal recovery. He recovered much faster than any of his younger counterparts even though a lot of physicians thought it would take months in the hospital for him to get out. Yet, in the first year after, he started riding his mountain bike and did 3,000 miles on his bike.

      • Not only is Mr. Rubin back to biking, he has also been cancer-free and GVHD-free for three years now. 
      • While science tends to be objective in nature, personal connections and motivations help drive the mission and make work like this possible. 

      PearX W25 applications are now open

      Posted on by jill

      The S24 batch of PearX is underway and the founders have been pushing hard to launch products, grow customers, and get their products to scale. This year we have seen a surge in AI companies with over 95% of S24 companies focusing on AI. Our AI team is ready and looking for companies in AI infrastructure and vertical applications. Read more about our AI thesis. We couldn’t be more excited about the S24 batch of companies, which we will share more about publicly in the fall.

      Simultaneously, we have been hard at work preparing for the W25 batch kicking off in January. Today, we’re opening applications for our W25 cohort and encourage all teams from idea stage to companies with traction to apply. Apply here now.

      Key Dates:

      Early applications and interviews: Early application deadline on August 30th. If you apply by this deadline, you will hear from us by mid-September.

      Regular Applications: Applications close on October 1st. You will hear from us by November 25th at the latest.

      PearX is an immersive small-batch 14-week accelerator which counts top performing companies like Viz.ai, Affinity, Xilis, Capella Space, Cardless, Nova Credit, Federato, Valar Labs among its alumni. Pear has also backed DoorDash, Dropbox, Vanta, Aurora Solar, Gusto, Guardant Health at the seed stage.

      At PearX, we provide custom services and support for each company. From capital, hiring, founder-led sales, to fundraising support, everything we do takes into account the unique needs that each company has.

      Here is what you get with PearX:

      • Capital to build your company, your way: We invest between $250k and $2M in all PearX companies. We know that some founders only need a small amount of capital to ideate and other teams are in more cost-intensive verticals that require more funding. All companies are unique so we’ll work with you. 
      • Credits: We provide up to $650k in credits from top providers like Azure, OpenAI, AWS, Google, Anthropic, and many more.
      • Founder to founder: Work 1:1 with a partner who has been in your shoes and knows your industry. Our team has started and sold 10 companies to the likes of Cisco, Instacart, Plaid, and Zynga.
      • Join the best community: Entrepreneurship doesn’t have to be a lonely journey. Joining PearX means joining a community of like-minded founders. We kick off each cohort with Camp Pear: a 3-day retreat for the entire cohort to come together, learn key company building tactics, and get to know one another. Not only will you work alongside your PearX batch for 14+ weeks, but you’ll also have the wider PearX alumni network to lean on. 
      • Access Pear Studio: Everyone in PearX receives dedicated office space in Pear Studio SF, our 30,000 square foot state-of-the-art office space with standing desks, conference rooms, phone booths, and more. This space is completely free to you for the first 12 months.
      • Build a scalable sales motion: Our go-to-market team, Pepe and Ana, will guide you through the critical steps of sales: nailing ICP, prospecting, customer discovery, messaging, and more. 
      • Recruit the best talent: Our dedicated PearX Recruiter, Nate, will find your founding engineer, co-founder, or whatever critical hire your team needs. In the last two cohorts, Nate has hired 25 people for our PearX companies. Nate leads the full cycle of recruiting for your team – from sourcing to closing candidates. This is an unprecedented level of support for an accelerator, but that’s how much we believe that hiring impacts company building. Last batch, Nate hired an average of two people per PearX company.
      • Fundraise strategically: We help you raise additional capital when you’re ready. From perfecting the story and creating a pitch deck to creating a target investor list and negotiating and closing your round. In fact, 90% of companies that go through PearX raise capital from institutional investors.

      Join us for PearX W25:

      Are you interested in joining our PearX W25 cohort? We’re looking for the next generation of category defining companies. Please apply at pear.vc/pearx.

      How three PearX S19 alums raised $50M this quarter

      Posted on by jill

      Today, raising capital is far more challenging than it was a few years ago. There are no fake Series A’s— most businesses require a good foundation, strong unit economics and growth as well as a moat to get there. We talked to three alums from our 2019 PearX cohort to hear how they raised capital this year: Andrew Powell from Learn to Win, John Dean from Windborne, and Parth Shah from Polimorphic. 

      PearX is our exclusive, small batch, 14 week program. 90% of our companies go on to raise a successful seed round from top tier investors. PearX alumni companies include Affinity (S14), Viz.ai (S16),  Cardless (S19), Federato (S20), Valar Labs (S21), and more. 

      Answers have been edited for brevity. 

      Learn to Win (PearX S19):

      Learn to Win is a training platform that empowers companies to design, deliver and assess the impact of employee training. They serve customers across commercial and government markets in primarily high-intensity training situations. Learn to Win closed a $30M Series A round in June 2024, led by the Westly Group and joined by Pear and Norwest Venture Partners.

      Windborne Systems (PearX S19):

      Windborne is a full-stack, vertically-integrated weather intelligence company. They operate the largest balloon constellation on the planet, running a base weather forecast with the data they collect from those balloons. Windborne raised a $15M Series A round, led by Khosla Ventures and joined by existing investors Footwork VC, Pear VC, and Convective Capital.

      Polimorphic (PearX S19):

      Polimorphic digitizes government operations, helping governments provide a great customer service experience to their residents and businesses. AI-powered search and voice software empowers municipal employees with saved time and resources, while delivering a modern service experience that delights residents. Polimorphic raised a $5.6M round, led by M13 with participation from existing investors Shine Capital and Pear VC.

      It’s been five years since you went through PearX. What did you learn from this accelerator program that still provides you value today? 

      Windborne: Mar played a big role in us even founding a company. Our very first check came from Pear Dorm. Fundamentally, we learned how to be entrepreneurs, and every connection in those early days came through Pear. 

      Polimorphic: One of the most interesting pieces of it was thinking about how venture-scale businesses are different. When we came into PearX, we didn’t even have a company yet, and we hadn’t even landed on this iteration of Polimorphic. 

      It takes time to find product market fit. PearX supported us during the exploration phase— you need to be nimble, trying stuff until you find what clicks. COVID interfered with a lot of our plans to work with the government in the early days, and recently we’ve really found product market fit.  

      Where has Pear helped your company the most? 

      Learn to Win: Hiring and fundraising. Pear has helped hire our first few engineers and our first few executives. 

      Windborne: Especially in the last year and a half, Pear’s talent team has been insanely helpful with hiring. Beyond that, they offer general advice on people ops: compensation, policies, equity splits— everything around managing people. We use Ashby for free through Pear. It’s very convenient to have a VC you trust a lot to help you get set up with these things. 

      One of the single biggest challenges that all companies face is talent. If you’re good at talent, you’ll win. If you’re bad at talent, you’ll lose. To have a VC that stands out in talent is incredibly valuable. 

      What’s a piece of advice for founders trying to raise a Series A? 

      Learn to Win: When it comes to Series A, there’s certainly more of an emphasis on metrics and scalability. Talk to other folks in your sector and ask them what key metric they were gunning for, what pieces of evidence they gave to investors to help them understand your business opportunity.

      At seed, we proved we could build a great product and deliver great value for customers. What needs to change is an engine that can repeatedly do that at scale. 

      Windborne: My biggest piece of advice is to be wary of advice that isn’t relevant to you. Think about where you want advice and where you don’t. For us, we disregard a lot of things people tell us when it comes to engineering and manufacturing when they don’t understand the way we run our business. You’re not going to win by only following commercial industry wisdom. 

      As the rounds progress, things definitely get harder— riskier, scarier, more challenging. But they also get so much more fun. 

      What sets Pear apart from other venture firms? 

      Polimorphic: Pear’s willingness to be involved. We were pre-idea, pre-company when we met Pear; we just knew we were interested in the political realm. Pear stuck with us as we started to explore government. Their ethos of investing in people manifested in sticking with us through a few different iterations.

      Learn to Win: Pear is an expert at early stage— even what comes before it. We were still students at Stanford working out of our dorm room, and Pejman and Mar were some of the first people to believe in the potential of our business. In the early days, there’s so many people that could point out a million reasons why your startup will fail. Pear believed in the one reason out of a million and helped us understand how to dig into it. 

      What are your goals for the next phase of your company? 

      Learn to Win: We’re trying to ramp up our defense business and grow aggressively across the board. We’re just scratching the surface, and we’re excited to see what we can do with this new capital.

      Windborne: We want to scale up data collection operations. We’re launching around 100 balloons a month, and we want to be doing a few hundred a month. By the next round, we want to be doing over 10 million a year in revenue. And more importantly, we want to be collecting more in situ weather observations than the rest of the world combined.

      Polimorphic: We’re on path to having 100 government clients, which is a big milestone. We started with cities and counties and are about to do our first state-level deal. That’s the next big phase: acquiring more customers, delivering a new paradigm for governments to provide customer service to their residents. 

      All three of these companies were in the same PearX S19 cohort. At the time, these startups were all just a few founders and an idea. It’s amazing to see their growth and to see them collectively raise $50M+ over the last quarter. Read more about PearX here. Applications for PearX W25 open on August 20th.

      Camp Pear: PearX S24

      Posted on by jill

      PearX is our accelerator for early stage companies and our S24 batch is officially underway. We welcomed 22 companies into PearX’s S24 class at Camp Pear: a 3-day immersive retreat for the entire cohort to come together, learn key company building tactics, and get to know one another. This class of PearX founders is overwhelmingly comprised of AI companies, with 21 of the 22 being AI-first. As is now our tradition, we kicked off the cohort with Camp Pear. 

      Practical advice from PearX alums

      The founders learned from expert speakers about key company building tactics – from hiring to go-to-market to fundraising and more. And they heard from Pear founders who have been in their shoes before – like Ray Zhou, Co-founder of Affinity (PearX S14), Scott Kazmierowicz, Co-founder and CEO of Cardless (PearX S19), Nicole Rojas, Co-founder of Lasso (PearX S22) and Lucia Huang, Co-founder and CEO of Osmind.  

      The power of community

      Camp Pear provides a unique way for founders to build community right from the beginning of each cohort. Through team building activities, bonfire conversations, and shared meals – founders got to know each other on a personal and professional level. Building a company from scratch is really hard, and we believe community plays a key role in the success of an entire cohort. 

      Kickoff to a fast 14-week company building sprint

      PearX starts at Camp Pear, but it’s really just the energizing start to a 14-week program. The 14 weeks between Camp Pear and Demo Day are all about company building. During the cohort, each startup will work closely with the Pear team to get their startup off the ground. This includes weekly 1:1 meetings with their primary Pear Partners, weekly talks from experts across the tech and startup world, hiring help from Nate, founder-led sales training from Ana, fundraising bootcamp from Mar, and loads of fun activities (like our upcoming founder Olympics competition!). It all culminates in Demo Day, where the PearX founders will pitch to thousands of top tier investors – and each batch, 90%+ of our companies go on to raise capital. 

      We’re so incredibly excited for this S24 cohort of PearX. If you’re interested in learning more about Pear, applications for our next cohort will open August 20th for W25. Stay tuned!

      Pear is built to support early-stage AI founders

      Posted on by jill

      2023 was the year that generative AI went mainstream. 2024 is shaping up to be the year founders put AI to work across the board. Here at Pear, we specialize in pre-seed and seed stage investing, backing AI-first companies and helping you go from 0 to 1. We provide deep technical expertise, we’ve built a first-of-its-kind GenAI studio, and we have a unique platform team that helps you take off.

      At Pear, we’ve been backing AI builders for over a decade, including these companies:

      Historic Pear investments include: Gradio (acquired by Hugging Face), Solvvy (acquired by Zoom), Viz AI, Federato, Valar Labs, Orby AI

      Since closing our fourth $432M fund in May 2023, we’ve doubled down on investing in the AI space. Below are just a few of our recent investments, with many more in stealth mode and 21 of our current 22 PearX S24 companies currently building in AI:

      Recent Pear investments include: Cognition Labs, Guardrails AI, Ideogram, Kindroid

      We believe that we’re just scratching the surface when it comes to what’s possible with AI. While we’re not alone in investing in the AI space, I do think we’re uniquely positioned to help early-stage AI founders for a few major reasons:

      We’re deep AI experts and operators

      Our AI partners are all former senior engineering leaders (Robinhood, Stripe, Dropbox, Cisco) and highly technical founders who have built high growth successful startups that were acquired by leading tech companies. As true experts, we’re able to deeply understand your technology and operating environment— and then work in the trenches with you. While many VCs can advise you on AI, Pear will dive in to actually help you whiteboard ideas, build out product roadmaps, get through difficult pivots, and scale out your company.

      Pear’s AI team: Arash Afrakhteh, Arpan Shah, Shravan Reddy

      We work as a team

      Pear’s vertical experts, like Eddie in biotech, Vivien in healthcare and Arpan and Shravan in fintech, are also here to support you, combining their industry expertise with our AI team’s long standing AI competency. Having founded, built, and scaled over 13 companies, when you get one of Pear investors, you get all of us.

      We offer unparalleled resources at the early-stage

      We’re an early-stage firm with the platform team of a much larger firm. Our talent team has four experienced recruiters, dedicated to help our founders find the best people, fast. They’ve already made over 116 hires for Pear companies, including 80 R&D hires such as AI engineers, NLP specialists, AI researchers, and more.

      Similarly, our go-to-market team equips our founders with all they need to successfully navigate founder led sales: providing support with determining ideal customer profile and messaging, pricing and contract strategy, call coaching, co-piloting deals, and more. The team has supported technical founders like Streamline and Orby AI in getting their revenue engines going. Results of this support include doubling one AI company’s ARR in just one month and seeing a 150% increase in close rates and sales representatives efficiency.

      We’re running Pear Studio: a first-of-its-kind GenAI studio and an elite founder network

      Earlier this year, we opened Pear Studio SF, a first-of-its-kind 30,000 square foot working space in Mission Bay. This unique community includes over 200 entrepreneurs working alongside one another to launch the next generation of AI companies. We also host events like the Pear VC + Open AI Hackathon, where 150 developers and entrepreneurs brought their AI-powered ideas to life. We also help startups grow with unique access to perks like credits from Open AI, Microsoft Azure, AWS, and Google Cloud, discounted legal formation packages, and payroll and HR benefits. 

      Work with us, even if you are early in your journey

      PearX is our elite accelerator for early-stage builders. We back companies early, when it’s often just a co-founder with an idea. Through PearX, you can with with the Pear team in Pear Studio to refine your MVP, design your GTM plan, expand your team, and launch successfully.

      AI Spaces we’re especially excited about

      Over the past year, Pear’s AI team has developed a thesis covering 16 pivotal areas in AI. We have already begun backing companies within many of these areas and look forward to meeting more exceptional founders innovating in these fields:

      1. Human-Simulating Agents: AI agents that simulate human interactions, from companions to customer support.
      2. Security and Assurance: AI leveraged solutions for defense through risks detection, prioritization, and automated mitigation, as well as evaluation and improvement of LLMs reliability
      3. Synthetic Data Pipelines: Automated data gaps detection and synthetic data generation to train and improve LLMs performance.
      4. Video: GenAI enabled creation, efficient editing, and enhancement of videos, revolutionizing both the movie and marketing industries.
      5. Robotics: The era of robots has arrived. Standardization across hardware and software as well as model proliferation, allowing growing adoption of AI powered robots.
      6. Domain-Specific Agents: Industry specialized AI agents capable of making intelligent decisions independently in code, healthcare, marketing and more.
      7. Data is the New Code: Advanced data pipelines and integration solutions for AI orchestration layer.
      8. Healthcare and Biotech: AI solutions that enhance and automate both non-clinical and clinical workflows, optimizing efficiency and quality of patient care and accelerating drug discovery, development, and access.
      9. Enterprise Apps: Lean and customized apps built and powered by AI, delivering improved performance with minimal implementation effort.
      10. New Models Modalities: Generative AI models capable of processing new, varied inputs such as biological and sensors data.
      11. Dev Tools: Highly reliable and productive dev tools to detect bugs, test, and fix code, as well as to build new internal AI applications.
      12. Simulations: AI-driven simulations allowing high accuracy and fidelity in complex simulations in a shorter time and less labor involved.
      13. Application Layer: AI-based applications enhancing employee performance, saving time, and reducing manual work.
      14. Marketplaces: AI-enabled marketplaces supercharging demand, supply or both sides with AI.
      15. Evolution and Observation: New CI/CD platforms for AI systems.
      16. Automations: AI-powered automation of workflows for process discovery, abstraction, and improved execution.

      In the coming weeks, we’ll share more around each of these 16 areas and why we’re excited to back founders building in these spaces. If you want to learn more, visit our AI page.

      Orby AI closes $30M Series A to continue building AI Agents for the Enterprise

      Posted on by lucy lee

      Orby AI recently announced its $30 million Series A round, co-led by NEA, Wing Venture Capital, and WndrCo, with participation from Pear VC. We are proud to be Orby’s earliest investors (when a LinkedIn message from their CEO first connected us) and we are thrilled to continue our support now.

      Orby’s Enterprise AI Automation tool automates complex workflows by observing users at work, identifying repetitive tasks, and writing the code to automate those tasks. Within minutes, a custom automation is ready to be implemented with user approval. 

      This is game changing.

      Orby AI is Changing the Game by Disrupting Process Automation Market

      Co-founder and CEO Bella Liu was heading AI Product at UI Path, a leading business automation software company, when she was first inspired with the idea behind Orby. At the time, the RPA (robotics process automation) software being used relied on human users to input specific “if this, then that” rules, which turned out to be rather fragile. For example, a user who frequently opens invoices and transfers numbers to a spreadsheet must specify exactly which buttons to click and where on the screen those buttons will be— a system that is prone to error, slow, and hard to scale. 

      Orby AI’s Model Learns and Implements Without User Input

      Orby’s approach to business automation is a huge leap forward. Unlike traditional RPA models, Orby’s LAM (Large Action Model) approach means their product doesn’t need to be told which tasks to automate, or how. Orby simply observes a user at work, learns what could be automated, and creates the actions to implement it. The user just approves the process and can correct the model at any time, thus continuously helping Orby improve.

      Why We Chose Orby AI

      We’re very excited about Orby’s team. Co-founders Bella Liu and Will Lu bring deep experience and expertise in the AI and automation technology space. Bella (CEO) was previously the AI product leader at UiPath, from early-stage to post-IPO. Will (CTO) was previously the data platform leader at Google Cloud AI and was involved in three AI products with real world deployments within Google. Orby’s team was a great founder-market match for Pear’s thesis on AI automation for human to machine and machine to machine automation. We are pleased to have backed Orby early on, and remain certain they are the right group to work on this problem.

      What Orby AI Does

      Before partnering with Orby, the Pear team was already deeply interested in AI automation for enterprise applications, aiming to solve specific problems within distinct industries one vertical at a time. They believed that the kinds of AI tools which could understand specific use cases, gather necessary datasets, and execute targeted solutions were the future. Additionally, they had a thesis that semantic understanding of workflows, enabled by backend interaction data, could enhance the generalizability of RPA.

      Orby’s team embraced a similar approach but expanded it to build a horizontal enterprise AI automation platform applicable across many verticals. Initially focusing on widely used workflows like invoice processing and expense auditing, they aimed to enhance their action-based foundational models. This led to the creation of a platform that delivers immediate value in various enterprise scenarios while achieving general-purpose AI automation.

      Orby is pioneering a Generative Process Automation (GPA) platform, leveraging the industry’s first Large Action Model (LAM) for enterprise use. This platform enhances efficiency by enabling teams to automate complex tasks independently. Orby’s multimodal large action model, combined with an AI agent capable of symbolic reasoning and neural network analysis, seamlessly handles intricate automation requests.

      When tasked with an assignment, Orby’s AI autonomously generates workflows, integrating with specialized AI agents for sub-tasks such as data analysis or customer interaction. By learning and automating workflows contextually and semantically, Orby surpasses traditional RPA systems. The LAMs empower Orby’s AI to understand and automate repetitive processes across unstructured datasets, emulating human capabilities.

      This neuro-symbolic programming captures standard process flows and ensures robust exception handling, making AI-driven automation accessible and efficient for enterprises. Orby’s patented technology, which combines LAMs with advanced programming techniques, empowers workers to automate tasks without needing technical assistance. The system continuously learns and adapts, improving productivity and efficiency over time.

      Market Opportunity

      The market potential for automation in enterprises has been evidenced by the success of Robotic Process Automation (RPA). However, AI Process Automation, like that offered by Orby, goes beyond traditional RPA by making previously uneconomical use cases viable. The return on investment (ROI) for RPA is often hindered by high implementation and maintenance costs, limiting its applicability.

      Orby’s innovative approach addresses two critical challenges of RPA:

      1. Semantic understanding of automatable workflows versus fragile rule-based systems.

      2. Hands-off, continuous online learning and improvement of both workflow discovery and implementation.

      By discovering automatable repetitive workflows and generating maintenance-free AI automations, Orby significantly reduces implementation and maintenance costs. This makes a much larger share of repeatable workflows candidates for automation, substantially improving ROI and expanding an already large market.

      This advancement is not merely an efficiency gain for high-volume, repeatable workflows. Imagine an AI capable of automating any workflow, regardless of volume, simply by demonstrating the process. This capability would enable enterprises to innovate their workflows at an accelerated pace, shifting focus to strategic improvements. In this competitive landscape, no enterprise can afford to ignore such technology, as those who adopt it will innovate faster.

      To provide a baseline, a 2017 McKinsey Future of Work report estimates that 60% of jobs involve at least 30% repetitive tasks that can be automated. Orby has already demonstrated massive productivity gains in several Fortune 500 companies through successful use cases. This is just the beginning; the market opportunity is far greater.

      How we partnered together

      After funding Orby’s seed round in July 2022, in addition to our close partnership on product and vision, we leveraged the full Pear team to partner with them in the following two years. Ana Leyva and Pepe Agell worked with the Orby team on their product-market fit and GTM strategy, and Jill Puente helped them in marketing and PR, including landing the Business Insider piece announcing the initial seed round. Nate Hirsch from Pear’s talent team helped Orby hire eight out of their first ten team members (eight engineers, two designers, and a recruiter). When it was time for Orby’s Series A raise, the company went through Pear’s fundraising bootcamp with Mar’s full support behind them. As we say to founders at Pear: if you get one of us, you get all of us as partners.

      We’re excited to have been supporting Orby AI since day one and look forward to their promising journey ahead!

      Arash and Bella at our AGM summit in March 2024.

      OnRamp announces $14.2M in funding to automate B2B customer onboarding

      Posted on by jill

      Today, Pear’s portfolio company OnRamp announced its $14.2 million in funding across a seed and Series A round, led by Javelin Venture Partners and Contour Venture Partners, with Quiet Capital, Correlation, Flybridge and angels Louis Beryl, Claire Hughes Johnson, and Steve Fredette. 

      We first met OnRamp’s Co-founder and COO, Ross Lerner, when he was an MBA student at Harvard Business School. As we got to know Ross and his Co-founder and CEO Paul Holder, we were convinced of the critical onboarding problem they aimed to solve—an issue we had frequently observed within our own portfolio companies. 

      The B2B customer onboarding process is a significant pain point for many companies, often leading to delays in revenue recognition and decreased customer satisfaction. OnRamp addresses this underserved market by automating and streamlining the post-sales process, which is crucial for accelerating value, reducing costs, and protecting revenue. 

      OnRamp transforms a traditionally cumbersome task into a seamless experience through a no-code customer portal that allows businesses to automate complex onboarding workflows. This solution means any deal team or account relationship stakeholders can collaborate to reduce time to value for its customers and improve customer engagement and visibility.

      Ross presented OnRamp to a handpicked investor audience at the PearX S22 demo day ahead of closing OnRamp’s seed round. Along the way, we’ve loved working with Paul and Ross on key hires, especially in building out pipeline and closing candidates in engineering and go-to-market roles.

      Ross presented at PearX S22 Demo Day to hundreds of investors

      Pear has also been a partner to OnRamp as they have expanded their product offerings to best serve large enterprises. We couldn’t be more proud that OnRamp now counts three of the Fortune 15 as its customers, serving industry leaders like Cardinal Health, CVS Health, and McKesson. OnRamp has tripled its revenue in each of the past three years and is on track to do so again this year, meaning that Paul and Ross have had plenty of opportunity to become power users of their own product. 

      To book a demo with OnRamp, visit onramp.us and experience firsthand how they can transform your customer onboarding process!

      PearX S20 alum Seven Starling raises $10.9M to expand access to specialized women’s healthcare

      Posted on by jill

      Today, PearX S20 alum Seven Starling announced a $10.9M Series A round to expand access to specialized women’s healthcare. The round was led by RH Capital and supported by Pear, Emerson Collective, March of Dimes, and others. 

      We’ve been backers of Seven Starling since day one of their company, and we’re excited to double down on them in this round. Not only have they proven to be an unwavering team but they have built an important and high growth business.

      We met the Seven Starling founding team (Tina Keshani, Sophia Ritcher and Julia Cole) over a Zoom call in March 2020. At the time, they were students at Harvard Business school working on a startup called June Motherhood at the time, an on-demand support service for expecting mothers, providing personalized care at home and online throughout pregnancy, birth, and early motherhood. 

      Tina, Sophia and Julia when they were students at HBS

      Ten days after our first meeting, COVID-19 shutdowns began. Despite the uncertainty at that moment in time, we decided to not only award them the Pear Competition, but also to invite them to join our PearX S20 cohort. 

      Here are a few characteristics that made Seven Starling stand out to us:

      • Exceptional consumer DNA: The Co-founders, Tina Beilinson (CEO), Sophia Richter (CPO), and Julia Cole (COO), were a fantastic group. They were exceptional, clear thinkers and communicators, scrappy operators that had spent months researching the space, and had strong consumer DNA, having worked at great consumer brands like Warby Parker and Kind.
      • Proof of execution. During the time in business school the team had tirelessly worked to validate their idea. By the time we met them, they had built a no-code prototype and had enrolled their first patients. 
      • Strong mission and product vision: Seven Starling took flight to help women navigate the most meaningful transitions in their life.
      • Untapped opportunity in Women’s Health: 33 million suffer from mental health conditions every year. Women are also 2x more likely to suffer from depression than men. Just last year, one in three new mothers suffered from perinatal mood disorders. Maternal mortality in the US is higher than our peer countries and is actually worsening. According to the CDC, the number one leading cause of maternal deaths in the US is undiagnosed mental health problems. Seven Starling saw this gap four years ago and has reinvented the clinical standard for women’s behavioral health.

      The summer of PearX S20, we worked together over Zoom. In just 12 weeks, they built an app, closed key partnerships and achieved their first revenue. They closed a Seed round right after demo day that included Pear alongside top-tier VCs such as  Emerson Collective, Magnify Ventures, and Expa. They were off to the races. 

      This was a Zoom check-in during PearX S20. The S20 cohort also included great companies like Expedock, Federato, Gryps, Sequel, Interface Bio, wagr, and rePurpose. 

      Our partnership with Seven Starling went beyond PearX. We’ve worked closely with their team over the last four years to help them build the foundations of a long lasting company. Here are some of the ways we partnered with Seven Starling over the last four years:

      Navigating to product market fit and working through a pivot:

      A year after PearX, we realized that scaling the initial product was not going as planned. Despite the customer love, the acquisition costs were too high and healthy unit economics seemed elusive. We had a difficult call where we aligned that “it was not working” and decided to iterate again on the product. We worked together very closely for a few months and we went back to listening to the customers. As part of this exercise, we realized our most loyal customers were looking for mental health support. OB-GYNS were also desperate for solutions for their patients – most couldn’t offer that mental health support themselves. 

      We decided to initially focus on a very narrow value proposition: maternal mental health. Then, we figured out that we also needed to innovate in the acquisition channel. We partnered with OB-GYNs to build a trusted referral network that delivered high intention patients.

      By focusing on a large but narrow value proposition ($8B+ maternal mental health market), we achieved product market fit and Seven Starling can now effectively grow into the nearly $55B+ women’s mental health opportunity. By innovating in the acquisition channel, we were able to grow rapidly with little cash spent: today 90%+ of Seven Starling’s patients are acquired through OB-GYN referrals, a key wedge into this market. A core value proposition to Seven Starling’s patients and referring providers is that they’re in-network with most major health plans including UnitedHealthcare, Cigna, Aetna, Kaiser Permanente, and Blue Cross Blue Shield. 

      Hiring: 

      Our team has helped Seven Starling make critical hires. Early on, our partner Vivien introduced them to a key advisor: Dr. Amy Roskin. She was so bought into the team’s vision, she joined as their Chief Medical Officer in 2022. Amy was an OB-GYN for over 20 years, was previously the CMO of The Pill Club, and was also an attorney who specialized in Telemedicine law. Laura from our Talent team also jumped into hiring for Seven Starling, helping them hire their founding engineer. This was their first technical hire and they’ve had a tremendous impact on their journey.

      Vivien helped connect Seven Starling with Dr. Amy Roskin, Seven Starlin’s Chief Medical Officer, pictured on the left. 

      Fundraising: 

      Since we started our partnership, we have helped the Seven Starling team navigate each of their fundraising rounds from  determining the fundraising strategy, to pitch creation to coming up with the target investor list. We are happy to have a phenomenal group of investors around the table, all of which believe deeply in the vision of the company. 

      Tina pitched live to hundreds of investors in Pear’s network in 2022.

      Where are they today? 

      Seven Starling  has grown tremendously over the past year, they have also delivered industry leading time to care with seven days to first appointment (industry average is three-six months) and 90% statistically significant reduction in PHQ-9 score after completing the program. Over 85% of patients are in-network plans which means patients access care for just their copay. This is all a result of the incredible clinical and operational execution horsepower the team has demonstrated.

      What is next? 

      We are excited about Seven Starling’s impact on women’s health. The space is still a huge untapped opportunity and behavioral health impact is inseparable from a woman’s overall health outcome. Seven Starling is positioned to meet the specialized needs of women throughout every stage of their lives, empowering them to thrive and achieve their fullest potential. I’m excited to join their board to support them on this ambitious and admirable mission. 

      It has been a privilege to partner with the Seven Starling team – their operational excellence and clarity of thought has made the journey to date an exhilarating one. 

      However, we realize the work is not over; we still have a lot to build! All of us at Pear VC are excited to continue our partnership with them.