Recursion
AI-native drug discovery: phenomics, robotics, and a 50+ petabyte dataset to de-risk medicines.
Recursion is a legitimate techbio partner with proprietary data, automated labs, and clinical-stage candidates. If you're a large pharma or biotech seeking to accelerate early discovery and de-risk pipelines, the partnership model is compelling, especially with the Genentech validation. However, it's not a software subscription — expect a custom, high-investment engagement. For smaller teams or academics, alternatives like Insilico Medicine, Schrödinger, or open platforms may be more accessible, though they lack Recursion's integrated wet-lab data engine.
Verified 4d ago · liveness 62/100 · cite: rightaichoice.com/tools/recursion
- Large pharmaceutical companies seeking to accelerate early discovery
- Biotech firms with capital to invest in long-term R&D partnerships
- Investors evaluating AI-driven pipelines with clinical assets
- Research teams in oncology and rare diseases needing novel targets
- Startups or academics needing a low-cost, self-service AI tool
- Teams focused solely on computational design without wet-lab validation
- Companies expecting a software subscription or API access
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Skip Recursion if you are a startup, academic lab, or individual looking for a quick, low-cost, self-service AI drug discovery tool — this is a deep partnership with custom pricing and no API access.
Pricing is custom and likely requires a multi-year, high-value partnership with significant upfront investment — expect contract minimums and resource commitments, not a monthly subscription.
Recursion's pricing is custom and partnership-based, suited for large pharma and biotech with deep R&D budgets. It's likely more expensive than software-only platforms like Schrödinger or Benchling, but offers integrated wet-lab data generation. For small teams, cheaper alternatives like Insilico Medicine or academic tools may be more appropriate.
In short
Recursion — AI-native drug discovery: phenomics, robotics, and a 50+ petabyte dataset to de-risk medicines. Best for Large pharmaceutical companies seeking to accelerate early discovery, Biotech firms with capital to invest in long-term R&D partnerships, Investors evaluating AI-driven pipelines with clinical assets. Contact Sales pricing.
What's new in Recursion
Checked 4 days agoAcross the latest 1 update: 1 launch.
What people actually say about Recursion — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
68 mentions across 4 sources (Reddit, Hacker News, Stack Overflow, Lemmy) · researched Jul 31, 2026.
- +Massive dataset integration (50+ petabytes) for deep biological insights
- +Automated wet lab enables millions of experiments weekly, accelerating discovery
- +Strategic NVIDIA partnership provides cutting-edge compute power
- +Multiple clinical trials with early positive data validate approach
- +End-to-end capability from target ID to clinical trials
- −Highly complex platform requires advanced technical expertise to use
- −Proprietary algorithms and data limit external validation and trust
- −Clinical success still unproven; most programs in early phases
- −High cost likely restricts access to well-funded organizations
- −Community feedback is sparse; minimal direct user experiences shared
Viability Score
How well maintained and how widely used is Recursion? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- AI-native drug discovery platform (Recursion OS)
- Automated wet lab with robotics and computer vision
- Up to 2 million weekly cell experiments
- 50+ petabyte proprietary dataset: phenomics, transcriptomics, proteomics, ADME, patient data
- Generative de novo chemistry for molecule design
- Target identification and validation via machine learning
- High-throughput phenotypic screening
- Lab-in-the-loop feedback between experiments and AI models
- Pipeline of first-in-class and best-in-class candidates
- Clinical trials: REC-4881 (Phase 1b/2 positive), REC-3565 (Phase 1), REC-1245 (Phase 1)
- De-identified patient data integration for precision medicine
- Fit-for-purpose dataset generation including ADME and safety
- Real-world evidence generation through clinical trials
- End-to-end drug development from preclinical to pivotal studies
- Strategic partnerships with pharma and technology leaders
About Recursion
Recursion is a techbio company that builds medicines using an AI-native drug discovery engine. Founded over a decade ago on the idea of using cellular imaging to train AI, the company now runs the Recursion OS platform: a continuous lab-in-the-loop system that combines physical automation, machine learning, and a proprietary dataset of over 50 petabytes. The platform runs up to 2 million weekly experiments in automated wet labs, generating phenomics, transcriptomics, proteomics, ADME, and de-identified patient data that feed back into AI models for target discovery, generative chemistry, and translational insights. This approach aims to cut the 90% failure rate of traditional drug discovery by improving speed, efficiency, and cost from hit identification through IND-enabling studies. Recursion's pipeline spans oncology and rare diseases, with clinical assets like REC-4881 (advanced solid tumors, positive Phase 1b/2 data), REC-3565 (B-cell lymphoma, Phase 1 dosed), and REC-1245 (Phase 1). Strategic partnerships, including with NVIDIA for BioHive-2 supercomputing and Genentech for neuroscience, validate the platform. The platform is not a software product; it's a deep partnership model for biopharma and investors. As of 2026, Genentech has optioned the first neuroscience target.
Behind the Verdict
Recursion stands out by closing the loop between wet-lab experimentation and AI. Unlike pure computational shops, they run millions of experiments weekly, and that data becomes a proprietary moat. The 50+ petabyte dataset spans phenomics and more, feeding generative chemistry and target discovery. The BioHive-2 supercomputer, co-built with NVIDIA, gives them serious compute for large-scale model training. Strengths include: end-to-end capability from target to clinic, clinical validation (REC-4881 positive trial), and deep pharma partnerships (Genentech, Bayer, etc.). The recent Genentech neuroscience option (August 2026) is a strong external validation. Weaknesses: this is not a tool you can try out. Pricing is custom (likely high), and the platform is closed. For a small startup, the barrier to entry is prohibitive. There's also a reputational overhang — a July 2026 Hacker News post alleges misrepresentation of capabilities, though no concrete evidence is in the scrape. Where it fits: large pharma and biotech with serious capital looking for a deep R&D partner. Where it doesn't: academic labs, solo researchers, or companies wanting a quick software fix. If you need a self-service AI drug design tool, look at platforms like Benchling or Schrödinger; if you need full-scale discovery, Recursion is a heavyweight option.
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Real-world workflow fit
Concrete scenarios for the personas Recursion actually fits — and what changes day-one when you adopt it.
Needs to accelerate target discovery for a oncology program.
Outcome: Engage Recursion for a partnership: within weeks, the platform runs phenotypic screens on your targets, generates data, and AI models identify novel candidates, reducing hit identification time.
Evaluating AI-driven pipelines for investment.
Outcome: Assess Recursion's clinical data and platform (e.g., REC-4881 positive trial, Genentech option) to gauge validation and potential for returns.
Needs novel targets for a rare disease with no existing treatment.
Outcome: Collaborate with Recursion to leverage phenomics data and AI models, generating potential drug candidates for preclinical testing.
Use Cases
- Identify novel drug targets by analyzing phenomics data from millions of cell imaging experiments.
- Design optimized preclinical molecules using generative AI trained on proprietary datasets.
- Accelerate hit-to-lead and IND-enabling studies with automated wet-lab validation.
- Partner with Recursion to co-develop treatments for oncology or rare diseases.
- De-risk pipeline decisions with AI-driven predictive models and translational data.
Models Under the Hood
as of 2026-08-30
Limitations
- Recursion's platform is proprietary and closed; there is no public API or self-service option.
- The platform is designed for deep partnerships, not individual projects.
- The scale and cost of the infrastructure (robotics, supercomputing, data generation) make it unsuitable for small teams.
- Additionally, a July 2026 Hacker News post raised concerns about capability misrepresentation, though no verified facts support that claim.
as of 2026-08-29
Verification history
We have re-verified Recursion 18 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 18 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Recursion's pricing actually pencils out — and where peers do it cheaper.
Recursion's pricing is custom and partnership-based, suited for large pharma and biotech with deep R&D budgets. It's likely more expensive than software-only platforms like Schrödinger or Benchling, but offers integrated wet-lab data generation. For small teams, cheaper alternatives like Insilico Medicine or academic tools may be more appropriate.
Setup time & first value
How long it actually takes to get something useful out of Recursion — broken out by persona, not the marketing-page minute.
For pharma partners, initial scoping and legal agreements may take 1-3 months; first data from pilot studies can arrive within 3-6 months. For investors, due diligence can be done in weeks using public clinical data. For research collaborations, expect 6-12 months for meaningful results.
Switching to or from Recursion
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From internal R&D: Shift to Recursion's AI-native approach for hit identification and de-risk early pipelines, leveraging their automated labs and data.
- ↗To a different AI drug discovery partner: Transfer your proprietary data and models, though you may lose access to Recursion's proprietary dataset and wet-lab capabilities.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Recursion
Common stack mates teams adopt alongside Recursion, with the specific reason each pairing earns its keep.
Iktos
Generative AI and robotics for autonomous drug discovery, compressing the DMTA cycle to under two years.
Recursion Pharmaceuticals
AI-native drug discovery platform turning 50+ PB of cellular imaging data into clinical-stage therapies
Evotec
Tech-driven drug discovery and biologics manufacturing platform
Featured Head-to-Head Comparisons
Lojong vs Recursion
If you're a pharma company aiming to slash drug failure rates, Recursion's integrated platform and clinical assets are unmatched, but it requires deep partnership and investment. For personal mental wellness, Lojong offers an accessible, Portuguese-language meditation app with proven user outcomes. These tools serve entirely different needs — choose based on whether your goal is therapeutic discovery or personal tranquility.
Codametrix vs Recursion
If you're a pharma company looking to accelerate early-stage drug discovery with a platform that combines massive phenomics data, automated wet labs, and AI modeling, Recursion is your choice. For large health systems aiming to cut coding costs by 30% and reduce denials by 60% with enterprise-wide automation, CodaMetrix leads. These tools serve completely different markets, so your decision hinges on whether you prioritize drug R&D or revenue cycle efficiency.
Juno vs Recursion
Recursion and Juno serve entirely different needs. Recursion is a high-investment platform for pharmaceutical companies aiming to accelerate drug discovery with massive datasets and wet-lab validation. Juno is a freemium, user-friendly app for individuals managing chronic illnesses to track symptoms and generate reports for doctors. If you're a patient, Juno is the clear choice; if you're a pharma R&D team, Recursion's custom partnership is the path forward.
Recursion vs Semrush One
These tools are incomparable: Recursion is a techbio platform for drug discovery with custom pricing and a massive wet lab, while Semrush One is a SaaS for SEO and AI search visibility with fixed enterprise pricing. Your choice depends entirely on your domain—biotech vs. digital marketing. Neither is a substitute for the other; pick Recursion if you're a pharma company seeking novel therapeutics, or Semrush One if you need to optimize brand presence across traditional and AI search.
Alternatives to Recursion
View allIktos
Generative AI and robotics for autonomous drug discovery, compressing the DMTA cycle to under two years.
Recursion Pharmaceuticals
AI-native drug discovery platform turning 50+ PB of cellular imaging data into clinical-stage therapies
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