AI evaluations, guardrails, and observability are what separate an AI demo from an AI system you can put in front of customers. Software Depo builds the testing and monitoring that let you deploy an agent with evidence — measured behavior before rollout, and visibility into what it does in production.
You Cannot Ship What You Cannot Measure
“It seemed to work when we tried it” is not a deployment standard. Before an agent goes live, we measure it against golden test sets, check its tool calls, and probe the ways it could fail — so you make the go/no-go decision on data, not vibes. This is one of our strongest areas: our agents ship with the evaluation stack built in.
What We Test
- Golden test sets — known inputs with known-good outputs, run on every change
- Tool-call testing — does the agent call the right tool with the right arguments?
- Hallucination and citation testing — are answers grounded and verifiable?
- Prompt-injection resistance — can hostile input hijack the agent?
- Permission testing — does it respect access boundaries under pressure?
- Regression testing — did a prompt or model change quietly break something?
Observability in Production
- Production traces — see exactly what the agent did and why
- Cost monitoring — catch a runaway token spend before the invoice does
- Latency monitoring — know when responses are slowing
- Human escalation — a clean path for the cases the agent should not handle alone
Independent Review
For security-critical deployments, evaluation pairs well with independent assessment. Our sister practice BulletproofSoft reviews AI and MCP deployments from a security angle — a different team, by design.
Tell us what the agent must get right — and what would be unacceptable for it to get wrong. We will build the evaluations and monitoring that prove it before and after launch.