Quality Commercial
Part of Synlogica Terminus
Terminus M4 reads the logger export and the stability documents, models what the excursion actually cost in shelf life, and returns a RELEASE / CONDITIONAL / HOLD recommendation with a stated confidence interval. The authorized reviewer makes the binding call; the sealed decision package records how.
The problem
A two-day excursion review is not slow because the maths is hard. It is slow because the evidence is scattered across a logger CSV, a stability report and a reviewer's spreadsheet, and because every reviewer reconstructs the assessment differently. The result is defensible only as long as the person who did it is still in the building.
What it does
Who it is for
QA and QP teams that assess cold-chain and ambient excursions every week, and the validation teams that have to defend the method at inspection. Advisory by design: batch disposition stays with the authorized human, recorded in your QMS.
Where it stands
Commercial Commercial — available under licence today. Onboarding starts with a working session on your own data, where the configuration baseline and the shared-responsibility split are agreed before anything goes live.
Key capabilities
Logger exports are parsed and screened before use — gaps, outliers, out-of-range readings, unknown formats confirmed by a person (ALCOA+). Every file is pinned into the audit trail.
MKT and Arrhenius k(T) run against the product's own stability model. The mathematics is GxP-frozen and pinned by a SHA-256 hash, so a result can be reproduced bit-for-bit years later.
Thousands of runs turn the kinetics into a probability with a stated 90% confidence interval and the data-quality flags behind it.
The advisory verdict is mapped by QP-approved rules; the binding disposition is signed per series by the Qualified Person with password-bound e-signature.
Customer excursion cases with roles for customer service, QA, QP and the stability expert, due dates, closure rationale and an append-only audit log.
Inside Terminus · illustrative UI
An illustrative preview on synthetic data — showing how a sealed decision package and the Decision Hub actually look. Not a customer screenshot.
Illustrative interface on synthetic data — representative of Synlogica Terminus, not a specific customer deployment.
M4 · Quality Analysis
Step 1 · Evidence in
Drop the logger export and the stability documents. Terminus parses and screens every input — gaps, outliers, out-of-range readings — before a single number is computed (ALCOA+).
Step 2 · Kinetics
The temperature profile becomes MKT and Arrhenius k(T) — how much of the product's stability budget the excursion actually consumed, not just “how long it was warm”.
Step 3 · Probability
10,000 Monte-Carlo runs turn the kinetics into a probability with a stated confidence interval — “96% within the stability budget”, not a point estimate or a reviewer's gut feel.
Step 4 · Decision
Terminus states an advisory verdict with the full sealed trail — inputs, model versions, ruleset. The authorized human (QA / QP) makes the binding release call, recorded in your QMS.
RELEASE · 2026-06-18 Illustrative interface on synthetic data — the same worked batch (PL-2026-0417-C) at every step.
The same chain of custody runs for freight (Terminus M1) and supplier negotiation (Terminus M5) — three modules, one governed platform.
Illustrative figures for this workflow. For the sourced, measured comparison and method, see “Measured, not estimated” below. ↓
Read how the engine works →Measured, not estimated
The numbers below come from comparing governed decisioning with typical manual QA excursion workflows. The full method and anonymized pilot data are in the white paper — so you can audit the claim, not just take our word for it.
100% of evidence traced, input-by-input
Read the method + anonymized pilot data →Compare
| Typical manual workflow | Terminus | |
|---|---|---|
| Excursion assessment | Spreadsheets, reviewer-dependent | Versioned model + stated uncertainty |
| Decision lead-time | ~2 days | under 60 seconds |
| Audit defensibility | Reconstructed by hand | Decision package, reproducible |
| Method consistency | Varies by reviewer | Same engine, tenant-configured rules |
| Validation posture | Ad-hoc | GAMP 5 Cat 4 — qualified once |
Three decisions, one engine
Three decision domains, each a Terminus module sharing one governed decision framework — so rules, versioning and the audit trail behave identically whether the question is a temperature excursion, a freight tender or a supplier price.
Temperature excursions assessed with Arrhenius + Monte-Carlo against the product's stability model — a recommendation with stated uncertainty, not a reviewer's guess.
See Terminus M4 →Tender leakage measured across SKU × lane × month, lanes scored by tail-risk — so spot-freight inflation is caught before invoices reconcile.
See Terminus M1 →MESO playbooks for API procurement — simultaneous-equivalent offers framed against a qualified BATNA when supplier qualification is the binding constraint.
See Terminus M5 →Terminus M4 is being validated under Synlogica's Integrated Management System (IMS) — ISO 9001 (quality), ISO 27001 (information security) and ISO 42001 (AI management) — on top of its GAMP 5 Category 4 lifecycle.
IMS certification target Q4 2026Every application in the portfolio carries the same controls, so an inspector who has seen one knows how to read the next.
Read more
Talk to us
Bring a real case — a recent excursion, an invoice you doubted, a procedure that just changed — and we walk it through together. If it is not a problem for software, we will say so.
