Ship AI agents you can prove.
You built the agent. AgentProof makes it production-ready and provable — with reasoning-level evaluation, reliability engineering, and audit-ready evidence for high-stakes teams.
Built on NIST AI RMF · ISO/IEC 42001 · EU AI Act · SR 11-7
Your agent works in the demo. Can you prove it in production?
Building an AI agent is easy now. Proving it is safe to ship is the hard part — and it is where teams get stuck.
Reliability is the blocker
Most agents that pass a demo never ship, because no one can prove they will hold up in production.
Right for the wrong reasons
An agent can guess, skip a step, or ignore contradicting evidence. That passing answer is a time bomb that fails silently later.
Accuracy is not evidence
A high test-set score will not satisfy your customer’s security review, your auditor, or your board.
The market repriced onto a number nobody audits.
AI service contracts are now written per resolved outcome — Zendesk at $1.50 a resolution, HubSpot’s Breeze at $0.50, Intercom’s Fin guaranteeing a 65% resolution rate or paying out. Enterprise procurement has followed, writing automation minimums and audit-trail requirements into core contract language. The outcome is now the invoice. Almost nobody can independently confirm it happened.
Agent pilots that never reach production. Leaders name evaluation gaps (64%) as the top blocker, ahead of governance friction and model reliability.
Organisations that fully trust the automated evaluations making their release decisions — while 66% already deploy, or plan to, without human review.
The distance between the outcome on the invoice and the outcome the customer received. Every per-resolution contract sits on top of it.
Gartner, 2026 · enterprise contact-centre AI
AI deflects more than 45% of queries; roughly 14% reach genuine self-service resolution. The gold band is work that is counted, invoiced and reported as complete — and is not. Re-contact within 72 hours runs 11.3% on AI-resolved tickets against 8.7% on human-resolved: the customers come back, but the dashboard has already gone green.
This is what AgentProof measures. Read our analysis of the verification gap
The proof layer between building and shipping.
Pernicia is the Proof Layer for Enterprise AI. Through our AgentProof practice, we turn "we think it works" into "here is the evidence it works" — engineered on your stack, in your environment. Not a platform; a practice, with the methodology and evidence your team keeps.
A right answer is not a reliable agent.
We grade the answer — and the reasoning.
Outcome-only evaluation cannot tell a sound decision from a lucky one. The Double-Rubric scores both.
Was it right?
- Accuracy and completeness
- Grounding in evidence
- Citation faithfulness
- Task success
Was it reached well?
- Path selection and evidence sufficiency
- Step validity and sequencing
- Coverage of contradicting evidence
- Stopping criteria — graded against your own SOPs
Evidence your auditors, regulators, and customers already recognize.
Every AgentProof component produces evidence mapped to the standards that define trustworthy AI — so the evaluation is the audit trail, not a second project.
NIST AI RMF
Govern · Map · Measure · Manage, plus the GenAI and agentic profiles.
ISO/IEC 42001
The first certifiable AI management system standard.
EU AI Act
High-risk requirements, Articles 9–15: accuracy, oversight, logging, data governance.
SR 11-7
Model risk management — validation and ongoing monitoring.
Tool-agnostic. Runs in your environment.
We sit on top of your existing stack — Braintrust, LangSmith, MLflow, Langfuse — and never move your data out of your environment. We bring what the tools do not: the Double-Rubric scorers, a judge calibrated against your experts, a customer-checked evaluation dataset, and a standards-mapped evidence pack.
Start small. Prove value. Scale to a trusted retainer.
AgentProof Scan
Fixed feeAn eval-readiness diagnostic. We baseline your agent, find the gaps against the standards, and hand you a reliability roadmap.
AgentProof Build
ProjectWe stand up the proof layer: the Double-Rubric, a customer-checked dataset, a calibrated judge, runtime guardrails, and your first audit-ready evidence pack.
AgentProof Continuous
RetainerOngoing evaluation, regression on every model upgrade, drift monitoring, and evidence refresh.
Plus AgentProof DD — reliability due-diligence for investors evaluating AI-agent startups.
We prove the evaluator — not just the agent.
Our hero metric is judge-to-expert agreement: proof our scores match your people. Alongside it — citation faithfulness, reasoning-rubric coverage, and standards coverage.
“We do not promise your agent will never fail. We promise you will know — measurably — how reliable it is, why, and whether it clears your bar and the standards’ bar, with evidence you can defend.”
Built for teams shipping high-stakes AI.
Who it is for
- Heads of AI and VP Engineering — the builders shipping the agent, with the evidence to clear their own risk and compliance gate.
- Regulated and high-stakes enterprises.
- VC-backed AI-agent startups that raised on the demo and now have to prove it.
Focus markets: North America and Europe.
Why Pernicia
- A North American firm with verifiable data residency.
- Compliance-first DNA — regulated AI is our home turf.
- Tool-agnostic — we amplify your team and your stack, we do not replace them.
- Built for the second day in production, not the demo.
Make your AI agent provable.
Start with an AgentProof Scan — a fixed-fee eval-readiness diagnostic.
Or write directly: engage@pernicia.in