Wysa vs Insitro

Insitro has a disclosed valuation of $2.2B, while Wysa's valuation is not publicly available, making a direct size comparison difficult. Insitro employs 300 people.

Insitro has raised more in total funding at $743M, compared to Wysa's $30M — a gap of $713M. Combined, the two companies have completed 6 known funding rounds.

Insitro leads with an Awaira Score of 73/100, while Wysa sits at 63/100. That 10-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Wysa was founded by Jo Aggarwal in 2015. Insitro was founded by Daphne Koller in 2018. Visit each company's profile on Awaira for a full founder biography.

Wysa: Wysa is an AI mental health platform that provides evidence-based cognitive behavioral therapy techniques through a conversational AI chatbot, offering anonymous, stigma-free mental health support accessible via smartphone at any hour. The platform uses clinically validated CBT, DBT, and mindfulness exercises delivered conversationally, and provides a step-up pathway to licensed human therapists for users requiring more intensive support.\n\nThe company raised approximately $30M in Series B funding and has deployed its platform to over five million users globally, including through enterprise employee wellness programs, NHS partnerships in the UK, and healthcare system integrations in the United States and India. Wysa has published peer-reviewed clinical evidence demonstrating statistically significant improvements in depression and anxiety scores.\n\nMental health care access is a global crisis with a severe therapist shortage that AI can meaningfully address at the first-line support level. Wysa's combination of clinical validation, enterprise and payer relationships, and scalable AI delivery model positions it as one of the more credible players in the crowded digital mental health space. Insitro: Insitro is an AI-driven drug discovery company founded in 2018 that applies machine learning to accelerate pharmaceutical development. The company combines computational biology, artificial intelligence, and wet-lab experimentation to identify and validate drug targets more efficiently than traditional methods. Insitro's platform uses proprietary algorithms to analyze complex biological data, predict drug efficacy and safety profiles, and optimize candidate selection across therapeutic areas including metabolic disease, oncology, and immunology. The company has raised $743 million across multiple funding rounds, achieving a valuation of $2.2 billion as of its Series C stage. This positions Insitro among well-capitalized AI healthcare startups addressing the structural inefficiencies in drug discovery. The company partners with pharmaceutical institutions to apply its technology to their pipelines, utilizing both internal discovery programs and collaborations. Insitro's competitive approach differs from pure software platforms by integrating experimental validation, reducing the translation gap between computational predictions and real-world drug performance. The company operates in a crowded but expanding market of AI drug discovery platforms competing against both established pharma AI initiatives and other venture-backed startups. Its growth trajectory reflects investor confidence in AI-enabled drug discovery models, though clinical validation remains ongoing for internally developed candidates. Insitro uniquely combines machine learning with integrated wet-lab capabilities rather than operating as pure software, bridging computational predictions to experimental validation.

Wysa got there first, launching in 2015 — that's 3 years of extra runway. Insitro didn't arrive until 2018. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Wysa has about 50-200 employees; Insitro has about 300. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Wysa and Insitro compete in AI Healthcare, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.