Independent AI-agent evaluation · Support & service
AgentDiligence turns your real support workflows into replayable, evidence-backed tests. We independently compare the agents you’re considering and show what’s safe to automate before you make a buying decision.
The gap
Evaluating an AI agent answers three different questions. Only one of them tells you whether it's safe to put on your work.
Can the vendor show a convincing happy path?
Which model wins on shared, generic tasks?
Can this agent safely do your work, to your standards, with evidence you can inspect?
How it works
We don't hand you a generic test set. We replay the work your team already did — the tickets, timelines, and actions behind it — and turn it into proof.
Tickets, timelines, status and assignee changes, internal notes, backend actions, and outcomes — exported, read-only, and handled privately. No prior eval set required.
Each trace becomes a replayable AgentDiligence Task Spec: the situation, the hidden business state, your policies, the allowed and forbidden actions, the expected final state, and the evidence bar it has to clear.
Packaged vendors, a cheaper challenger, a reference agent, and your current process all face the same specs under identical constraints, with repeated runs where consistency matters. We test the agents — we never sit between you and your vendors.
Every run produces an Evidence Packet — transcript, vendor source and handoff records, and independent backend final-state proof — scored from Level 2 to Level 4.
A plain-English recommendation: which categories are safe to automate, assist, human-gate, or avoid — and which agent, if any, is worth buying or piloting.
Evidence
Every run becomes a decision-ready report: what passed, what failed, what's safe to automate, and how to route the rest. Every figure links to the evidence behind it.
Illustrative — sample figures, anonymised arms. In a real engagement, arms are named, every figure links to its transcript, tool calls, policy match, and final-state proof, and cost is per safe resolution.
A pass-rate or a slick demo — the vendor's word, nothing behind it. Not evidence; packets start at Level 2.
What the agent said and showed the customer, captured verbatim.
Vendor-side evidence: where answers came from, what was logged, how it escalated.
We check the backend itself: was the refund actually issued, the case actually resolved?
“Vendor PoCs are free. Choosing wrong isn't.”
Every vendor runs its own proof-of-concept — on its own tickets, scored its own way. AgentDiligence turns them into one fair decision: same tasks, same bar, same evidence format.
Engagements
Productized evaluations, scoped to the decision in front of you. Most teams start with a Vendor Decision Report.
What's safe, risky, or worth evaluating?
Which vendor or route should we buy or pilot?
What's safe to automate across the org?
Does the deployed agent still clear the bar?
Engagements are priced to the decision — typically a small fraction of the first-year agent spend. Ask for a scope.
Who it's for
Support and service leaders at scaleups choosing — or second-guessing — an AI agent on customer-facing work.
Support is the first proving ground. The same Task Spec → Evidence Packet engine applies anywhere humans leave a work trail — finance ops, claims handling, contract review.
Send us a slice of your support history. We'll show you what's safe to automate, and what isn't.