Tool selection
Whether the agent chooses the right tool, avoids unnecessary tools, and handles unavailable or failed tools.
AI Agent Testing
Agents fail differently from chatbots.
AI agents introduce a wider risk surface than simple LLM interfaces. They choose tools, manage state, handle permissions, chain actions, recover from errors, and sometimes act before the user fully understands the consequence. Qualura tests those agentic paths before they become production incidents.
The risk is not only what the agent says. It is what the agent does.
An AI agent can give a reasonable explanation while calling the wrong tool, using stale memory, skipping a confirmation step, or continuing after a partial failure. These are workflow failures, not just language failures.
We test agents through realistic tasks, ambiguous instructions, interrupted flows, bad tool responses, permission boundaries, retries, and state transitions.
Agent testing coverage
Focused coverage for teams that need evidence, not generic QA theater.
State and memory
Session state, long-running tasks, memory carryover, stale context, and incorrect assumptions from prior interactions.
Permissions and boundaries
User authorization, sensitive actions, approval gates, account boundaries, and data leakage paths.
Workflow completion
Whether the agent completes the task correctly instead of producing plausible partial progress.
Error handling
Tool errors, network failures, malformed responses, retries, and recovery without silent corruption.
User control
Stop, undo, confirm, edit, regenerate, and escalation paths for high-risk actions.
How we test AI agents
We map the agent's tools, permissions, memory, and user journeys.
We create task scenarios that combine normal use, ambiguity, adversarial input, failed dependencies, and repeated attempts.
We report where the agent acted incorrectly, failed to verify, skipped a safety step, or left the user without a clear recovery path.
What you get
- Agent risk map
- Tool-use failure findings
- State and memory defect report
- Permission boundary findings
- Workflow completion analysis
- Remediation priorities
Related services
Prompt Injection Testing
Adversarial testing for prompt injection, data leakage, and tool misuse.
AI Safety Testing
Safety, abuse, refusal, and harmful-output testing for AI products.
LLM Testing Services
Testing for prompt adherence, hallucinations, refusals, and model drift.
FAQ
Common questions before we scope the work.
Can you test agents connected to real tools?
Yes, usually in staging or with safe test accounts so we can validate behavior without risking production data.
Do you test autonomous agents?
Yes. We test both autonomous and human-in-the-loop agents, with special attention to confirmation gates and recovery paths.
What makes agent testing different?
Agents can change external state. That means tool choice, permissions, memory, and workflow recovery become as important as response quality.
Work With Us
Need AI testing before your product ships?
Book a 30-minute discovery call. We will understand your product, identify the riskiest AI surfaces, and recommend whether a sprint or custom engagement fits best.
Qualura
Senior-led. Evidence-first. NDA-bound.
We test AI products, LLM features, agents, RAG systems, and automation workflows the way real users interact with them.
infas@qualura.com