The GxP operating system. Learns from every run.

neil (Seal's AI) transforms procedures into executable workflows, unifying change-control, validation, training, data, and reporting. Every run builds process intelligence, so your life-changing technology reaches patients faster.

Turn one procedure into a GxP workflow you can run in 48 hours.

Your process already exists. It's just split across documents, validation work, training, and execution. neil, Seal's AI, drafts the controlled workflow, validation pack, and training requirements together. QA approves the release. Training gates control access, and each run captures values, signatures, and decisions as work happens.

T+00:00
Start with one procedure

Use a sample first, or bring your own after an NDA.

T+02:30
neil proposes the build

Records, steps, checks, and gates, mapped from your own clauses.

T+26:00
Your team reviews and signs

Nothing goes live without named, signed human approval.

T+48:00
Live, with evidence

Evidence generated from the build. Execution gated per operator until training is current.

See the 48-hour build
One connected ontology
1,842 objects · connected
PATIENT×217COI-2214APHERESIS×217AP-2214VECTOR×14LV-118INSTRUMENT×9Prodigy-3POTENCY×217412 pg/mLOPERATOR×28S. ReyesRELEASE×217QA ✓DEVIATION×19DEV-08CAR-T RELEASE217 patients

All your data, one connected record.

Every apheresis lot, vector, potency result, instrument reading, and signature — tied to the patient it belongs to — lands in one connected graph, not five systems stitched by integrations that break. neil sees the whole ontology, so nothing stays a fragment.

How neil connects it

Validated doesn't mean frozen.

Because execution, validation, training, and records live together, neil can help change the process itself: scope impact, propose the next version, route approval and retraining, and produce the validation pack. The live process changes only by approved version.

Legacy stacks turn every improvement into a revalidation project. Seal lets operations evolve one governed version at a time.

Change set
Live
11m 32s
Elapsed
34
Checks
12/12
Gated
Change
Review by exception
neil proposed · v04
Scope
QC release step · 12 reviewers
neil scoped the impact
Verify
34 checks passed
Training assigned. QA review captured
Release
v04 live
Evidence pack sealed
Change set / QA-Procedure-014 v04
Live
Scope
QC release step / 12 reviewers
mapped
Validation
34 checks passed
pack ready
Training
12 reviewers gated
assigned
Release
v04 live
approved
Timestamp
Event
Signed by
 
neil proposes review by exception
neil
 
Scope: QC release step · 12 reviewers
neil
 
Validation pack: 34 checks
neil
 
All 34 passed
 
Reviewed and approved
Marcus Chen, QA
 
Training assigned: 12 reviewers gated
 
Evidence pack sealed
 
v04 live
How changes stay validated

Every run improves the next.

Most AI reads documents beside the work. neil learns from the work itself: approved workflows, execution evidence, deviations, approvals, and release state. It turns repeated problems into governed changes QA can approve.

How neil works
Process memory
217 patients treated
QA-PROC-014 · CAR-T MANUFACTURING · v04APHERESISACTIVATETRANSDUCEEXPANDFORMULATEQC RELEASERELEASE TIME · VEIN-TO-VEIN · DAYS28d21d14-DAY TARGETv02 · rapid sterilityv03 · in-line potencyv04 · review by exceptionPT-218 · PREDICTED

Friction is not rigor.

Medicine needs proof before it reaches patients.

Paper and document tools turn that proof into rework: retyped values, reconstructed evidence, disconnected review.

neil runs the work and captures the proof inside it — as it happens, not after.