Research use only · auditable by design

Pay for the workflow. Inspect the evidence.

GaiaLab turns biological context into source-linked, testable research hypotheses with visible uncertainty and reproducible records. Plans scale the research workflow—not unsupported claims about model superiority.

Source-linked evidenceExplicit uncertaintyReproducible recordsNo clinical-use claim

Start with the level of workflow you need.

Public exploration remains easy to try. Paid plans add durable research workflow, exports and programmatic access. Institutional teams begin with a bounded validation pilot before broader deployment.

Free
$0
for public research exploration

Evaluate the basic GaiaLab workflow before committing to a paid plan.

  • Gene-panel research exploration
  • Up to 50 genes per analysis
  • Source-linked evidence views
  • Visible limitations and uncertainty
  • Research-use outputs
Start exploring →
Use public or non-confidential inputs.
Pro
$99 / month

For advanced users who need higher-throughput, programmatic, and audit-oriented workflows.

  • Everything in Researcher
  • 200 analyses/day (vs. 50/day on Researcher)
  • API / developer workflow access subject to plan limits
  • Batch and structured export workflows
  • Evidence and lineage artifacts
  • Priority product support
Subscribe — $99/mo →
Capabilities remain subject to deployed feature and quota status.
Runtime contractFreeResearcherProInstitutional pilot
Analyses per day1050200Negotiated
Maximum genes per analysis50505050
Biotech · pharma · CRO · research groups

Institutional adoption starts with validation.

Rather than asking a scientific organization to buy a broad enterprise promise, GaiaLab begins with a bounded 4–6 week evaluation against the team's own review process and predefined success criteria.

Review the Validation Pilot →
✓ Agreed question family
✓ Criteria frozen before review
✓ Source-linked evidence package
✓ Negative findings retained
✓ Independent team review
✓ Final go / no-go decision memo
Institutional data boundary.

Initial validation pilots should use public, published, synthetic, or otherwise non-confidential inputs. GaiaLab does not currently represent the public workflow as ready for PHI, patient-identifiable data, regulated clinical data, trade-secret datasets, or confidential institutional information. Confidential-data use requires separately agreed terms and verified enterprise controls.

No agent-count theater

Plans are described by buyer value and workflow. Internal model or agent configurations may change and are not represented as evidence of scientific superiority.

No brittle source-count promise

Evidence availability depends on source health, credentials, query context, licensing and deployment status. GaiaLab should report provenance and availability rather than market a fixed count as a scientific guarantee.

No self-improvement efficacy claim

Calibration, evaluation and workflow updates are versioned. GaiaLab does not claim that every analysis automatically makes the scientific system more accurate.

No unverifiable timestamp claim

Eligible prediction and research records are hashed into Merkle leaves and can be batched through OpenTimestamps. A record is described as Bitcoin-confirmed only after its stored receipt is independently verified; /verify exposes the exact proof status and boundary. Confirmed exact-name forward hits so far, reported honestly: see the live ledger at /new-trials.