Testing Amazon Bedrock Agents
Every time you swap or upgrade the underlying model behind a Bedrock agent, behavior can shift in ways that are hard to predict from the model card alone. ContextQA tests the agent's actual behavior, not the model's specifications, so version changes get validated against real scenarios before they reach customers.
Black-box, by design
Teams building on Bedrock often discover a model upgrade changed agent behavior only after a customer notices, because there is no standing scenario suite that runs automatically on every version change. Most AI testing tools are either observability platforms watching production traffic or SDK-first libraries requiring code-level access. ContextQA is neither — pre-launch, black-box, and built for agents you don't control the source code of. See how ContextQA tests AI agents →
1. Define
Point ContextQA at your agent's documentation, system prompt, policy files, or conversation logs.
2. Probe
ContextQA generates adversarial and functional scenarios and runs them against your live agent, no SDK or code access required.
3. Score
Every response is scored with configurable AI judgment plus deterministic checks — a confidence rating backed by evidence, not a guess.
“Re-run the standing suite after a model upgrade.”
Comparing against the prior model version
Compliance question now answered inconsistently — flagged
What this catches before customers do
Catch a model-upgrade regression
“Does this catch regressions when I switch Bedrock model versions?”
Yes — one of the main use cases this integration is built for.
Hallucination-trap scenariosMulti-turn consistency
"Does it handle multi-turn conversations?"
Yes. ContextQA simulates full multi-turn chains of 20 or more turns with branching logic and escalation flows.
Multi-turn evaluationModel-upgrade regression
"What happens when I upgrade the underlying model?"
Every model upgrade triggers a full regression run, surfacing behavioral drift before you deploy.
Regression runsNo SDK, no code access
"How are test scenarios generated?"
Point ContextQA at your agent's docs, prompts, or policies. It models the behavior and generates scenarios automatically.
Black-box by designNo SDK, no code access
- Your agent's docs, system prompt, or policy files
- No dev-org or source access needed
- About 30 minutes for the first scenario set
- Share your agent's documentation, prompts, or policies
- ContextQA generates adversarial and functional scenarios automatically
- Scenarios run against your live agent, scored with a confidence rating
On-premises deployment is available for strict security or data-residency requirements. Contact sales for details.
"No SDK, no instrumentation, no code access required."
— ContextQA's black-box testing model
Tested before it reaches a customer
Works with Salesforce Agentforce, Amazon Bedrock, Azure AI Foundry, Snowflake Cortex, Intercom Fin, and custom-built agents.
Common questions
Yes, this is one of the main use cases this integration is built for.
No, testing happens from the outside, based on how the agent actually responds.
Yes, scenario suites can be re-run on a schedule or triggered by a version change.
Any agent platform, including Salesforce Agentforce, Amazon Bedrock, Azure AI Foundry, Snowflake Cortex, Intercom Fin, and custom-built agents. Because ContextQA tests from the outside, there is nothing to instrument on the platform side.
Yes. ContextQA can be deployed entirely within your own infrastructure, ideal for organizations with strict security, compliance, or data-residency requirements. Contact sales for details.
See a real scenario catch a real failure
Book a 20-minute demo and watch ContextQA probe a live agent.
Book a Demo Testing a different agent platform? See how ContextQA tests AI agents →