Skip to content

SolutionsHealth

Health. Research pipelines with an audit trail.

Patient-cohort and clinical-pipeline work run as enforced, evidenced, replayable processes with compliance surfaces built in.

Signed evidenceReplayable audit trail

Runs as a service today.

01Capabilities

Research pipelines that keep their receipts.

Health research must answer for itself later. Every cohort, pipeline, and conclusion is recorded as it was made, and replays exactly.

Patient-cohort construction
Cohorts are built as runs against defined criteria, kept with the cohort so it can be reconstructed exactly.
Clinical-pipeline execution
Research pipelines run as enforced processes: a stage advances only when its gate's criteria are met.
Evidence in a signed graph
Evidence is captured as signed, append-only facts: what a run concluded, recorded with what it concluded it from.
Replayable history
Every decision reconstructs from the journal; an audit replays what happened.
Compliance surfaces
Access, provenance, and forgetting are first-class: facts can be retracted, entities tombstoned, bytes excised, each as a further signed fact.

Request a demo

02The audit trail

A journal that proves what it knew.

Evidence lands as signed, append-only facts; a query answers what was known at any past date, and a compliance erasure is itself a signed, provable act on the record.

APPEND-ONLYTYPED CONFLICTASOF(T)SIGNED · ED25519
Append-only strata of signed facts, sealed by hairline rules, with one typed conflict surfaced and an as-of cut across the stack.

Request a demo

03Walkthrough

One decision, replayed for an audit.

The audit question is always the same: why was this decided, and on what evidence. One cohort-inclusion decision answers it here.

replay health/cohort-inclusion: one decisionillustrative
decision.selected

An auditor picks one decision: the inclusion of a de-identified record in a study cohort.

replay.started

The run re-executes from the append-only journal. No memory of the original run is needed.

memory.asof

The memory answers with what was known at decision time, whatever has been learned since.

evidence.listed

The signed facts the decision read: the criteria, the source records, their provenance.

gate.checked

The inclusion criteria that held, with the outcome of each check.

replay.completed

Same inputs, same projection, same decision, rebuilt from the record.

Sample events, illustrative and de-identified. No patient data, no efficacy figures.

The week before an audit looks like any other week.

Request a demo

04Calibration

Calibrated conservatively.

The harness is tuned against evals on task correctness and process adherence. The claim is alignment to the process you defined; nothing promises a clinical outcome.

Evals on task correctness
Evals score clinical-task correctness and adherence to the required research process, separately.
Adjusted until the scores hold
Process, skills, and memory are tuned until runs hit the target score and hold it when the evals re-run.
Alignment to intent
Calibration aligns a run to the process you defined; the console never claims a clinical outcome.

Request a demo

05What this makes possible

The dosage question.

Take the best agent prompt engineering can build: skills, careful instructions, review loops, the works. Would you put it in charge of a patient’s medication dosage? No responsible team would.

That is the point: the trust never comes from better prompting; it comes from enforcement. Clinicians author the decision process, every step is gated, a human breakpoint holds before anything reaches a patient, every decision replays from the journal. Such a workflow could, potentially, be made trustworthy.

We imagine going further: with enough paired data, patient situations and the dosage a clinician chose for each, a harness could be trained to produce the right workflows, an expert validating each before use. An illustrative direction only; nothing here is a shipped capability or a regulatory claim.

Request a demo

06The console

What the console shows.

concept console (illustrative)
The Health console: a de-identified patient-cohort builder, a clinical pipeline with stages and gates, an evidence and provenance viewer backed by signed memory, compliance and authorization surfaces, and a replay affordance on a decision.
A concept rendering of the Health console. No real patient data, no efficacy figures; cohorts are de-identified and generic.
  • A patient-cohort builder working on de-identified, generic data.
  • A clinical pipeline with stages and gates.
  • An evidence and provenance viewer, backed by signed memory.
  • Compliance and authorization surfaces: access, provenance, retraction.
  • A replay affordance on any decision.

Every audit-trail property above is open source. What a download cannot give you is the calibration to your protocols and a pipeline operated alongside your clinical team.

Request a demo

A pipeline you can answer for later, with signed evidence behind every decision.

Replay one cohort decision, evidence and provenance in view.

A Health demo replays one pipeline decision end to end, evidence and provenance included.

Or emailhello@a5c.ai

The intro call is 30 minutes and free.

Or write it here.

Compose opens Gmail in a new tab; copy works with any mail app.

or copy:hello@a5c.ai

A founder reads every message.