Standard pack
DECISION_SUMMARY.json · FINAL_REPORT.md · SUMMARY.csv ·
plot gallery (target 6–7 PNGs) · deliverable.zip.
Red lights stay in the pack. CSV beats narrative.
Axiom Workbench · offline characterization lineage · GABS-aligned
The evaluation system behind every public claim.
Most filter vendors ship demos. We ship Axiom Workbench — the universal evidence factory — plus offline characterization lineage (GSRF Audit Workbench class): pre-declared setpoints, frozen evaluators, deterministic governors, unvarnished verdicts, multi-method overlays, and red lights that stay in the manual.
Trial / NDA workbench access: Request Audit Pack · optional later: info@boonmind.io
Axiom Workbench — mission runner
Operator-facing loop co-located with the engine: mission packet → allowlisted factory → deliverable pack → download. Metrics come only from Workbench factory software. AI may format reports; it does not invent numbers. Orphan-number verify blocks the zip if a report invents a figure.
Status (honest)
Local service UI is available to operators when the process is running next to the engine. No public multi-tenant HTTPS host is claimed on this page until auth + deploy gates pass. Partners: Audit Pack and gsrf-bench first.
Operators
Start the service from the Axiom Workbench repo, then open the self-serve form
(default local: http://127.0.0.1:8790/ui/ — port may differ if busy).
Sealed evaluation requests stay on Zero Overshoot: Request a sealed evaluation
Partners
Self-serve receipts and local CSV eval stay the open path. Full mission runner / engine access is pilot or NDA — not a calendar gate for the public packs.
Binding: no AI-calculated metrics · no silent merge of 298/298 with DAMADICS ·
web_publish=false by default · path jail + factory allowlist on every run.
The browser never invents scores.
Request a sealed evaluation runner Contact with a Zero Overshoot sealed-evaluation subject
What the Workbench is
A desktop/local Python lab (not a public multi-tenant cloud SaaS) for Gradient-Stabilized Recursive Filtering. Agents and engineers load data and run packs — they do not invent metrics by hand. The optional Workbench Service is a mission runner around the same factories.
Frozen evaluators
Phase 5 MAIN, Phase 6.x oscillation, excellence hunt, characterization v4, delay/alarm probes — same code path that wrote the public claim ladder.
Pre-declared rules
Win criteria locked before runs. Thresholds are not relaxed after seeing scores. Failures stay on disk as JSON + Markdown reports.
Full artifact trail
metrics_summary.csv · DECISION_SUMMARY.json · all-methods PNGs · audit logs · executive summaries — per pack, per file.
What it has run (evaluation inventory)
Characterization & identity
- Step / frequency / gain plateau packs
- Excellence hunt multi-family (peak vs MAD)
- Mechanism ablations (k_return as product identity)
- Adaptive x* regime probes
- Delay & fixed-FA residual red lights
Industrial & real-public batteries
- Seven SCADA-style actuator files (+ remaps)
- 12-file adversarial Tier-1 pack (anti-complimentary)
- DAMADICS Lublin real plant valves (partial/loss published)
- Tennessee Eastman XMVs (simulated plant)
- VitalDB / phase mocks in research archive
Public surface: Evidence + Research notes. Full multi-GB experiment tree stays local / NDA — the site shows claim-safe slices and gallery plots.
Gallery — workbench multi-method overlays
Raw vs EMA family vs GSRF Practical / Reference. Captions claim-safe.
The claim ladder
Marketing may only climb what the Workbench locked. If it isn’t on the ladder, it doesn’t ship.
| Rung | Safe public wording | Unsafe wording we refuse |
|---|---|---|
| Identity | Soft thermostat / attractor stabilizer in log-space | “Universal optimal filter” / “better EMA everywhere” |
| Oscillation | Mid-band ring kill on locked packs (~+35% osc31 / ~−70% spectral sweet band) | “Always reduces oscillation on any signal” |
| Peaks | Peak compression toward normal (~38%; 49/52) | “Zero overshoot guarantee on all plants” |
| Industrial actuators | Regime-bounded synthetic batteries + real DAMADICS first look with partial/loss | “GSRF wins industrial actuators” without qualifiers |
| Tracking / delay / FA | Documented red lights (MAD, delay, fixed-FA residual) | “Best tracker” / “drop-in delayed command filter” / “alarm detector” |
| QEC path (BP preprocessing research — not a quantum computer product) | Separate ladder under NDA | Mixing LER heroes into industrial homepage |
Questions people actually ask
Snippet-ready answers. Deep numbers live on Evidence.
What is the GSRF Audit Workbench?
A local offline characterization lab: frozen evaluators, pre-declared rules, multi-method overlays, industrial batteries, DAMADICS staging. Agents load data and run packs — they do not invent metrics.
Is it a cloud SaaS?
No public multi-tenant cloud SaaS is claimed. Engine is desktop/local Python. Workbench Service is an operator mission runner co-located with the engine (not open internet without auth/deploy). Public path: Try + gsrf-bench. Full engine = trial/commercial.
What is the Workbench Service?
Mission form → allowlisted factory → locked pack (DECISION_SUMMARY, FINAL_REPORT, SUMMARY.csv, 6–7 PNGs) → download. AI does not calculate metrics. See #service.
What industrial data has it run?
Seven synthetic SCADA-style actuators (Phase 5 MAIN), adversarial Tier-1 pack, DAMADICS Lublin real plant (2/3 partial, 1/3 loss published), TE simulated XMVs. Not “wins industrial actuators” without qualifiers.
How do public claims relate to the Workbench?
Marketing only climbs the claim ladder. If it is not locked, it does not ship. See Evidence and methodology.
Public eval vs full Workbench
Public (now)
- Try snippet — notebook math
- gsrf-bench — local CSV vs EMA metrics
- Evidence + Research — claim-safe slices
- Workbench Service — operator mission runner (local / pilot; not claimed as public SaaS)
Full Workbench (trial / commercial)
- GUI + batch runners + frozen Phase packs
- Presets, NDA methodology, multi-GB experiment tree
- Partner / real-plant staging support
- Mission Service + engine co-located when pilots need full packs