AI Governance & Evaluation
Prove your AI works and stays safe — evaluation harnesses, guardrails, drift monitoring, and EU AI Act-ready documentation.
The problem
AI in production without measurement is a liability. Leaders can’t answer “is it accurate, is it safe, is it compliant?” — and regulators (and boards) are starting to ask. Most teams have no evals, no drift monitoring, and no paper trail.
What it includes
The capabilities we build into this solution — engineered for production, not a demo.
Evaluation harness
Measure accuracy and quality against labelled sets, continuously.
Guardrails
Safety, scope, and policy controls tuned to your risk profile.
Drift & incident monitoring
Catch performance decay and failures before they hurt.
Bias & fairness testing
Test and document fairness where it matters legally.
EU AI Act readiness
Documentation and controls mapped to the regulation.
Model-agnostic
Works across models and vendors — no lock-in.
How we'd build it
The same method behind everything we ship: de-risked, measured, and in production in one quarter.
Feasibility
We validate the use case on your real data, define the accuracy bar and ROI, and give you an honest go/no-go — usually in weeks.
Build & evaluate
We engineer the system and score it against a labelled set until it clears the bar — quality is a measured number, not a promise.
Deploy
We ship to production, integrated with your systems and behind the right human-approval gates, with monitoring from day one.
Operate & improve
We watch it in production, handle drift, and expand scope as trust builds — feasibility in 6 weeks, production in ~90 days.
What you get
- A measured accuracy and safety bar for your AI
- Continuous drift and incident monitoring
- Audit-ready governance documentation (incl. EU AI Act)
- A model-agnostic evaluation setup you own
Production AI we've shipped
We'd build your solution with the same discipline behind these real, in-production engagements — described by sector under NDA.
A production document classifier — 5,000+ documents/month, built to a ≥95% accuracy target and live in 8 weeks.
Read the case studyBank-statement automation across 21 banks with a measured 0.24% transaction-direction error rate.
Read the case studyAI-at-POS recommendations running against live in-store transactions across every location.
Read the case studyWant to scope AI Governance & Evaluation?
Tell us the use case. We'll come back with a feasibility view and an honest go/no-go — a working prototype in about six weeks.
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Location
Barcelona, Spain • Lisbon, Portugal • Sheridan, WY, USA (incorporation)
Why Choose CONE RED?
- AI R&D lab & venture builder — production systems, not slideware
- Feasibility in 6 weeks, production in ~90 days
- Accuracy measured and evaluated — never invented or guaranteed
- Real engagements across financial services, healthcare & retail
- End-to-end support from strategy to deployment
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