Connect your AI system
Use supported MCP, API, RAG, model, and agent target adapters.
AI Release Assurance
Know if your AI system is ready to ship.
Prooflane turns complex AI testing into a guided assurance workflow.
Connect your system, let Sammy recommend the regression coverage it needs, review the plan, and run security, RAG, prompt, contract, performance, and model assurance from one place.
Then Prooflane turns the evidence into a clear READY · REVIEW · BLOCK decision.
30 days · No credit card · Local execution
MCP · API · RAG · Model · Agent
THE SPINEAI RELEASE ASSURANCE
01 / QUALITYDoes it work?
02 / SECURITYCan it resist?
03 / INTEGRITYCan it be trusted?
SHARED EVIDENCE PLANEFACT → POLICY → DECISION
DEPLOYMENT GATE
● READY◆ REVIEW■ BLOCK
Guided assurance
AI assurance without the evaluation learning curve.
You shouldn’t need an AI evaluation specialist every time QA wants to add regression coverage.
Prooflane guides teams from connection to a governed release decision.GUIDED ASSURANCEOne governed workflow
- Connect
- Discover
- Build
- Review
- Run
- Decide
Connect → Discover → Build → Review → Run → Decide
Prooflane guides the complete assurance process.
You don’t start with an empty test suite. You start with a proposed assurance plan.
Map what is available
Prooflane maps capabilities, schemas, retrieval surfaces, tools, boundaries, and execution behavior.
Start with a proposed plan
Sammy analyzes the discovered system and recommends the assurance coverage it needs.
Keep humans in authority
QA, Product, Security, and engineering review the recommended regression coverage.
Execute the coverage
Run deterministic and model-assisted evaluations through the appropriate local or governed path.
Apply release policy
Turn the resulting evidence into a governed READY, REVIEW, or BLOCK decision.
Built for the whole AI release team
Guided when you want it. Powerful when you need it.
Two experiences operate on one governed assurance system.
For QA, UAT, Product, Security, and release teams
You don’t need to learn an AI evaluation framework before you can start testing.
Connect→Discover→Generate→Review→Run→Decide
Sammy recommends the coverage. You review it. Prooflane executes it.
For developers and platform engineers
Work directly with targets, assurance configuration, Suites, Policies, Gates, Runs, evidence, CLI, and CI/CD workflows.
$ prooflane gate --suite release
FACT → POLICY → DECISIONAnything created through the guided experience resolves to the same underlying Prooflane contracts developers can inspect and automate through Command Deck.
Sammy Intelligence
You don’t need to know every test to write.
Sammy learns the system first and coordinates assurance planning across specialized intelligence while deterministic controls remain mandatory.
Sammy reasons. Prooflane proves.
Explore governed intelligence →GOVERNED INTELLIGENCECoverage proposal
- DiscoverUnderstand the available target surface.
- Deterministic MinimumEstablish mandatory assurance coverage.
- Fast · Deep · SpecialistInvestigate gaps requiring additional reasoning.
- Independent ReviewChallenge the resulting model-assisted plan.
- Deterministic ValidationValidate structure, bindings, assertions, provenance, and mandatory coverage.
- Human Review & ApprovalHumans retain authority over governed assurance.
HUMAN APPROVALImmutable Suite + Policy
Fact → Policy → Decision
A score isn’t a release decision.
An AI system can perform well overall and still contain one failure that should stop deployment. An aggregate score should not average that failure away.
ILLUSTRATIVE EXAMPLEAggregate score vs. critical evidence
SECURITY SCORE96
BUTCRITICAL AUTHORIZATION BOUNDARY FAILURE1
FACT
↓A cross-tenant tool invocation succeeded.
POLICY
↓Cross-tenant access is prohibited.
DECISION
BLOCK until the boundary is fixed and the Gate is rerun.
Real fixture run
See the Gate as decision-grade evidence.
Open a sanitized report generated from Prooflane’s deterministic test fixture. It is not a customer result.
View sanitized Gate report →Illustrative example, not a customer result. Prooflane decisions remain governed by the approved release policy and available evidence.
One regression workflow
Build regression coverage for the entire AI system.
Traditional regression testing asks whether something that worked yesterday broke today. AI systems need the same discipline across more surfaces.
Prompt Regression
Refusals, output contracts, policy behavior, instruction hierarchy, and semantic quality.
Explore prompt testing →RAG Evaluation
Retrieval, grounding, faithfulness, relevance, citations, hallucination, tenant boundaries, and drift.
Explore RAG Evaluation →Security Regression
Authorization, MCP and tool abuse, prompt injection, agent resistance, destructive boundaries, and controlled exploit verification.
Explore security →Contract Regression
Schema compatibility, required fields, types, boundaries, negative inputs, and breaking changes.
Explore contracts →Performance Regression
Latency, throughput, concurrency, and SLO behavior.
Explore performance →Model & System Benchmarking
Quality, latency, cost, security, RAG behavior, and system-level performance across deployment candidates.
Explore benchmarking →
See retrieval quality and regressions across repeatable runs.
Trace resisted and breached attack paths to evidence.
Compare complete deployment candidates, not isolated models.
Follow a release decision back to its blocking evidence.
One governed assurance system
One platform instead of disconnected AI testing tools.
Prompt testing, RAG evaluation, AI security, MCP and tool assurance, contracts, performance, benchmarking, and model assurance all produce evidence for the same governed release workflow.
One regression workflow. One evidence system.EVALUATE
↓Test the complete AI system
EVIDENCE
↓Preserve what happened
POLICY
↓Apply approved release rules
DECISION
READY · REVIEW · BLOCK
Same evidence · different depth
Deep evidence for engineers. Clear decisions for everyone else.
Prooflane reports support three levels of understanding without requiring every reader to learn LLM scoring methodology.
What happened, why it matters, and what must happen next.
BLOCK
1 Critical · 2 High · 4 Review
- Security — Blocking
- RAG — Review
- Prompts — Pass
- Contracts — Pass
- Performance — Pass
Understandable regression outcomes.
40 RAG cases
34 passed · 3 failed · 3 require review
The answer was correct, but the cited source did not support the response.
The system selected the wrong retrieval tool for two finance-related queries.
An expected refusal was not produced.
Technical drill-down when you need it.
evaluation caseassertiongraderjudge provenancemodel relationshipraw scorethresholdlatencytool callsretrieved contexttraceevidence fingerprintsSuite / Policy / Gate identity
Local-first trust
Your system stays yours.
Sensitive execution remains local by default. Synchronize only the governed evidence required by the Prooflane architecture.
Sensitive execution data
- Credentials and OAuth state
- Raw prompts and raw responses
- RAG documents and retrieved context
- Tool outputs and MCP execution
- Detailed raw execution evidence
Only what the workflow requires
- Identity and entitlement
- Policy, Suite, and Gate governance
- Sanitized findings where applicable
- Evidence fingerprints and summaries
- Signed Gate decisions
Any optional feature that requires external data egress should require explicit disclosure and consent.
One assurance layer
From technical complexity to a release decision anyone can understand.
Prooflane connects the people who build, prove, secure, define, and release the AI system.
Contact
Talk to the Prooflane team.
Tell us about the AI system and release decision you need to make.
AI Release Assurance
Find what your current AI testing is missing.
Connect your system. Let Sammy recommend the assurance coverage it needs. Review the evidence. Make the release decision.
30-day full-access trial. No credit card required.