Klarna publicly rehired human agents after customers hit wrong answers; a court held Air Canada liable for a refund policy its chatbot invented. The first person to discover an agent failure should never be a customer.
One prompt tweak or provider model update can silently change behavior everywhere. Across the industry, quality is the #1 blocker for agents in production — yet only about half of teams have any systematic testing before release.
Research on frontier AI agents shows one that passes a task once often fails when asked to do the same task eight times in a row. Reliability, not intelligence, is the gap between demo and production.
What the agent must never say or do exists as your team's judgment, not as anything written down and testable. When people leave or models change, the judgment doesn't transfer.
5 questions. 60 seconds. See where you stand.
We sit with the people who know what the agent must and mustn't do. Every judgment becomes a written, testable rule you keep.
Realistic, difficult, persistent simulated customers run your real scenarios against your agent, before release — like a flight simulator for your support experience.
Before a prompt, tool, or model change ships, you see exactly which behaviors changed, with conversation evidence.
If the audit doesn't surface at least 5 things you didn't know about your agent, you don't pay.
Answer 5 questions, see where you stand.
Your rulebook as 50+ testable checks, plus every surprising behavior we find in your real conversations, ranked by customer impact. Pay on delivery — if we don't surface at least 5 things you didn't know, you don't pay.
Everything in the Audit, plus a go/no-go report on your next real agent change before it ships. 50% escrowed at start, 50% on delivery.
A hands-on partnership for one team shipping a real agent. We work your releases side by side, and Sims takes shape around what we learn together — you get a direct line to the people building it.
89% / 52%
of agent teams have monitoring; only about half have systematic testing before release
LangChain, State of Agent Engineering
Most fail
frontier agents that pass a task once fail the majority of the time when asked to repeat it 8 times in a row
τ-bench, Sierra research
NuBank, DoorDash, Sierra
all built agent-testing infrastructure in-house. Sims brings it to teams that can't spend quarters building it.
Monitoring tells you what happened, after customers experienced it. Sims tells you what will happen, before they do.
So did DoorDash — it took them quarters. The audit delivers the equivalent starting point in two weeks, in open formats your team keeps, no lock-in.
The best time. We build your rulebook before day one so launch day isn't the first test.
Talk to us before launch →No — a conversation export is enough. No SDK, no integration, NDA standard.
Any. We work from your conversations, whatever framework or model is behind them.