Build and run transparently
Configure environments, scenarios, perturbations, seeds, and execution in Studio. Inspect the equivalent Python and JSON before anything is prepared.
OUTPUT / Validated workflow + generated codeReliability Studio / Product
From a run to the limit you can defend.
Design the evaluation, run it with explicit compute limits, inspect truthful simulation views, and carry the evidence all the way to a permanent regression guard.
EVIDENCE LOOP / POLICY–V17 ACTIVE EVALUATION
- 01ObserveRun captured
- 02ComparePairing exact
- 03LocateBoundary unresolved
- 04ReviewEvidence pending
- 05StrengthenRegression next
System versionpolicy-v17Declared scopecell-04 / occluded-pickCurrent findingUnresolved at boundary
The operating loop
Find the failure. Understand the change. Keep the evidence.
Reliability Studio connects workflow configuration, execution, simulation rendering, causal investigation, boundary mapping, evidence review, and regression in one traceable loop. Each result becomes evidence for the next decision—not another screenshot lost in a dashboard.
Core capabilities
One system for the questions between “it works” and “ship it.”
Render what was declared
See validated environment boundaries, scenario perturbations, and recorded trajectories without inventing geometry the simulator never supplied.
OUTPUT / Declared + recorded viewsExecute with limits visible
Run locally, on customer-hosted CPU or GPU, or on one isolated managed CPU worker after Studio shows the estimate and authorizes worker-hours.
OUTPUT / Metered execution + provenanceCompare and map coverage
Choose real baseline and candidate executions, locate behavioral divergence, and separate supported, unresolved, and failing condition regions.
OUTPUT / Comparison + coverage boundaryReview the complete evidence
Inspect versioned SDK reports with disposition, validity scope, limitations, uncertainty, and content-addressed lineage intact.
OUTPUT / Scoped decision recordPrevent the failure from returning
Preserve the scenario, seed family, perturbation envelope, and acceptance rule as a regression guard for the next candidate.
OUTPUT / Replayable regression assetTwo ways to work
Use the code. Use the interface. Keep the same evidence.
01 / SDK + CLI
Run where your system already lives.
Instrument local, CI, simulation, replay, or customer-hosted workflows. Keep models and environments under your control.
- Python-native evaluation
- Local and bring-your-own compute
- Versioned reports across the full evidence catalog
- MCP access for Claude and Codex
02 / STUDIO
See the evidence as a system.
Configure and launch workflows, render declared environments, inspect comparisons and coverage, review evidence, and keep release decisions connected to their provenance.
- Pro: guided Build & Run and generated code
- Pro + Team: environment and recorded-run rendering
- Team: editable manifests, roles, approvals, and replay
- Worker-hour estimates, progress, ETA, and memory
Studio receives only the telemetry and artifacts you authorize. The first 100 verified Pro trials receive two promotional worker-hours. Later trials can bring their own compute or purchase managed hours; every launch has an explicit runtime limit.
The output
Not a trust score. A decision record.
Every surfaced conclusion travels with the evidence required to interpret it. When the evidence is insufficient, the product says so.
EVIDENCE ARTIFACTREQUIRED CONTEXT
DispositionWhat the evidence supports
IntervalThe range, never a naked point
Validity scopeWhere the conclusion applies
LimitationsWhat remains unresolved
ProvenanceHow the evidence was produced
CONTENT-ADDRESSEDVERSIONEDABSTENTION-FIRST
Start with one system
Bring the behavior you need to trust.
We will help you define the first meaningful reliability question and build the evidence loop around it.