Enterprise AI. Engineered to operate.
We keep AI agents working in production, within the rules, and prove what they return.
What you get
Three things your board will ask about.
Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027, citing cost, unclear value or weak risk controls. Gartner, 2025
01 · Reliability
It keeps working
Every agent is tested before release and watched after launch. Quality does not decline unnoticed, and failures in production become new tests.
Live quality
- Tested before release
- Watched after launch
- Failures become tests
02 · Compliance
It stays within the rules
Safety, data protection and EU AI Act requirements become test cases that run on every release. A failed critical check stops the release.
Release checks
- Safety
- Data protection
- EU AI Act
- Company policy
New release
Checking
Running checks
03 · Proof
It shows its return
One scorecard reports time saved, cost per task, quality and compliance against a baseline set before launch, in numbers finance can check.
Scorecard
- Time savedvs. baseline
- Cost per taskvs. baseline
- Qualityvs. baseline
- Compliancevs. baseline
Success stories
Work we've shipped.
FGS Global
Test · Protect · Monitor
One scorecard for 30+ agents across different use cases.
Sourcera
Test · Prove
Saving opportunities scored against a benchmark, not by opinion.
Industries
Where we keep agents reliable
The same practice, adapted to each industry's inputs and review steps.
Keep supplier scoring accurate as suppliers change.
Procurement teams move requests, supplier context, quotes, policies, approvals, and spend data through manual comparison and follow-up.
Would your AI agents survive a budget review?
A call to review one agent: what it does, how it is tested, what it costs and what you can show.
Free first meeting
Real examples, not slides
A clear next step, or none