LabGenius
Therapeutic-antibody discovery in a closed Design-Build-Test-Learn loop. EVA accumulates structured outcome data from each robotic experiment cycle and feeds it back to generative ML models directing the next design round. Genuine experiment-memory-as-training-signal.
Active · Verified 2026-10-29 · fresh as of 2026-10-29 · 31 cited facts, 4 with a third-party source · 1 recorded change · Suggest a correction
At a glance
- Type
- Autonomous experiment memory (EVA platform) vendor fix
- Tier
- T1
- Created
- 2012 (founded 2012 by James Field at Imperial College London) third-party fix
- Latest release
- not applicable — not OSS fix
- License
- not applicable — not OSS fix
- GitHub
- not applicable — no GitHub repo fix
- Pricing
- Enterprise only vendor fix
- Funding
- Series B £35M led by M Ventures / Octopus Ventures / LG Corp May 2024 third-party fix
- Freshness
- 2026-10-29 fix
- Layer
- agent-infra repo fix
- Licensing
- commercial vendor fix
Memory taxonomy
- storage
- proprietary
- retrieval
- agentic
- persistence
- long-term
- update
- extraction
- unit
- episode
- governance
- opaque
- conflict
- n/a
When to use
Optimised for: research-workflow integration + provenance + claim grounding
Anti-fit: not for non-research / non-academic use cases
Pros & cons
Pros
Closed-loop wet-lab + ML platform — memory is grounded in actual experimental outcomes, not just literature.
Cons
Niche to protein engineering / antibody discovery; not a memory product per se.
Claims & capabilities
Robotic wet-lab integration. London-based.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Managed-only
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- no MCP support advertised — vertical product, no MCP server / client integration documented
- A2A
- no A2A protocol support advertised — vertical product, no A2A integration documented
- OpenTelemetry
- no OpenTelemetry integration advertised — vendor logs/observability not publicly documented
Alternatives to LabGenius → live options ranked by shared design, licence, hosting and MCP support
Similar systems
Other vertical / domain-specific ai memory in the catalog, ranked by inbound references.
- Inworld AI T1
Formerly an NPC character engine with named Long-Term Memory; now sells realtime voice models (TTS-2, STT-1, speech-to-speech) and OpenAI-compatible open-model inference. Character/NPC memory is no longer the headline product.
- NVIDIA ReMEmbR T3
Builds long-horizon memory by captioning video segments with VILA, storing captions with timestamps + 3D position coordinates in MilvusDB. At query time, LLM iterates retrieval across text, time, and position modalities. Deployed on Nova Carter robot (Jetson Orin).
- Abridge T1
Clinician-assist ambient documentation. Source mapping: every AI-generated summary element traced back to the source utterance. Audit-and-trust layer over episodic memory. Built on proprietary 1.5M+ medical-encounter dataset.
- ASAPP GenerativeAgent T1
Treats memory as first-class architecture. Captures the digital footprint of every interaction; retrieves preference and history at engagement time. Public example: airline knowing a frequent flyer wants aisle seats with her son — preference-aware, not just history-lookup.
- BenevolentAI T1
Taken private: merged into Osaka Holdings (renamed BenevolentAI S.A.) and delisted from Euronext Amsterdam 2025-03-13. Target identification / drug repurposing / mechanism tracing. 85+ data sources, petabyte-scale, rebuilt every few weeks. Wet-lab results re-enter the graph and shift downstream predictions — institutional experimental memory closing a feedback loop. As of Oct 2026 benevolent.com leads with Qor, powered by BenevolentAI, a life-science intelligence service for biopharma decision makers and consultancies. Qor (qor.one) is a continuously updated decision-intelligence service built on BenevolentAI's knowledge graph and reasoning methods: it tracks evidence on an asset or indication (competitive position, rival readouts, comparable deals), source-verifies each claim and flags when an earlier conclusion stops holding. It targets biotech teams and life-science consultancies.
- Causaly T1
Agentic AI platform for life sciences: orchestrated scientific agents over a curated biomedical knowledge graph (plus Bio Graph and Pipeline Graph), an evidence-retrieval system and an enterprise data fabric over literature, trials and patents.
Sources (30 cited facts, 4 third-party)
Each fact links to the page it came from; the badge says who published it (how to read sources).
- What it is Autonomous experiment memory (EVA platform) vendor
- What it does & what's distinct Therapeutic-antibody discovery in a closed Design-Build-Test-Learn loop. EVA accumulates… vendor
- Claims / benefits Robotic wet-lab integration. London-based. vendor
- Modalities text + sensor vendor
- Created 2012 (founded 2012 by James Field at Imperial College London) third-party
- Mindshare below detection threshold for HN/press; Series B £35M led by M Ventures / Octopus Ventur… third-party
- Funding Series B £35M led by M Ventures / Octopus Ventures / LG Corp May 2024 third-party
- Pricing Enterprise only vendor
- Deployment Managed-only vendor
- HQ UK third-party
- Founders / pedigree LabGenius (James Field, founder/CEO; ex-UCL synthetic biology; London-based) vendor
- Memory volume / scale internal — undisclosed (continuous experiment loop data) vendor
- Consistency strong consistency required for clinical record integrity vendor
- Versioning immutable audit log (HIPAA + 21 CFR Part 11 require audit trails) vendor
- Tombstoning audit-logged soft delete (regulatory retention requirement) vendor
- Schema evolution FHIR/HL7-aligned schema (clinical standard); minor versioning vendor
- Namespace primitives tenant-per-customer (BAA-scoped); patient-scoped within tenant vendor
- Forgetting policy regulated retention (7+ years per HIPAA + state law); patient-requested deletion governe… vendor
- Validated verticals research only (academia + R&D in pharma / biotech / scientific publishing) vendor
- Time to running <10min (hosted SaaS) to <1day (enterprise integration) vendor
- Anti-fit not for non-research / non-academic use cases vendor
- Optimised for research-workflow integration + provenance + claim grounding vendor
- Adjacent infrastructure self-contained SaaS; some integrate with reference managers vendor
- Pros Closed-loop wet-lab + ML platform — memory is grounded in actual experimental outcomes, … vendor
- Cons Niche to protein engineering / antibody discovery; not a memory product per se. vendor
- Project & sources labgenius.app vendor
- cost-pricing-model subscription vendor
- cost-last-verified 2026-06-29 vendor
- licensing-bucket commercial vendor
- taxonomy-three-layer-rollup agent-infra repo
What changed
Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)
- 2026-10-29
- Homepage “https://www.labgenius.app/” → “https://labgeniustx.com/”