AuraOne / Foundry
Loading hill-climbing and sealed suite options.
AuraOne / Foundry
AuraOne Foundry improves systems you already run through a repeatable measure-and-fix loop, and licenses sealed evaluation suites built from reviewed work.
Two streams on one foundry: climb the benchmark you care about, or license a sealed suite and score against it.
Two streams, one foundry
Stream A improves a system you already run through a repeatable measure-and-fix loop. Stream B licenses sealed evaluation suites built from reviewed work. Both end at the same place: evidence you can defend.
Your prompt, workflow, agent, or data goes through measure, diagnose, bridge, improve, re-measure, and certify — on a loop, against a locked benchmark.
See the engagement flowProprietary Task Foundry Output, reviewed by experts and held to a freshness bar, packaged as evaluation suites you can license.
Browse the suitesStream A — Measure → Diagnose → Bridge → Improve → Re-measure → Certify
Each cycle starts from locked evidence and ends with a certification decision. Practice material never leaks into the sealed evaluation.
Measure the system as it runs today. Lock the task, the baseline, and the quality bar before anything changes.
Name the failures worth fixing. Expert review classifies failure modes and traces them to representative cases.
Build targeted practice material. Proprietary Task Foundry Output aimed at the diagnosed failures, kept separate from sealed evaluation sets.
Fix the prompt, workflow, or data. Apply the smallest change that addresses the diagnosed failure mode.
Score the same locked benchmark again. Repeated rollouts under identical criteria show whether the change held.
Issue the regression report. Certification is granted only when the re-measured result clears the bar with no regressions.
Stream B — Sealed suites
Representative fixture baselines below; program briefs confirm scope and sealed content. Baselines only — tasks, solutions, and scoring internals stay sealed.
Classify, route, and resolve representative customer support requests.
1,200 tasks
| Baseline resolution rate | 61% |
|---|---|
| ARIS (reliability-adjusted) | 0.58 |
| Known-failure coverage | 34 modes |
Extract terms, flag risk, and summarize representative business documents.
2,500 tasks
| Baseline extraction accuracy | 74% |
|---|---|
| ARIS (reliability-adjusted) | 0.71 |
| Known-failure coverage | 41 modes |
Complete multi-step operational workflows against representative inputs.
800 tasks
| Baseline completion rate | 52% |
|---|---|
| ARIS (reliability-adjusted) | 0.49 |
| Known-failure coverage | 27 modes |
Why the numbers hold up
ARIS is a single reliability-adjusted score: how often the system succeeds, weighted by how much each failure matters, with shaky results discounted.
Every benchmark runs multiple times under locked criteria, so the reported number reflects steady behavior.
Sealed evaluation sets are held to a 0.1% overlap tolerance against seen material. Anything above the line is quarantined, never scored.
Qualified reviewers adjudicate disputed cases and sign off on every suite before it ships.
Engagement shapes
Every shape is scoped in a sales conversation — no public rate card. Talk to us and we will fix the scope, the evidence, and the commercial shape together.
Two ways in
Bring one benchmark and the system that must beat it. We will show the loop on your work.
Book a demoTell us the domain and the decision the score must support. We will confirm the sealed suite and its terms.
Contact salesStart a program
Tell us what data your AI system needs or which recurring workflow your enterprise already performs. AuraOne will carry that context into the project brief.
