Testing Snowflake Cortex Agents
Agents built on Snowflake Cortex are often answering questions directly against live data, which means a subtly wrong answer can look completely plausible. ContextQA tests these agents from the outside, checking whether answers are actually correct, not just well formatted.
Black-box, by design
A data team can validate that a Cortex agent connects to the right tables and returns a response. It is much harder to validate, at scale, whether the reasoning behind that response is actually correct across the range of questions people will really ask. 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.
“Two phrasings of the same revenue question.”
Checking both against the source data
Different, incorrect figure for one phrasing — flagged
What this catches before customers do
Catch a data accuracy error
“Does this test data accuracy or just response formatting?”
Accuracy. ContextQA checks whether the actual answer is correct, not just whether one was returned.
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
Accuracy. ContextQA checks whether the actual answer is correct, not just whether one was returned.
No, testing is based on the agent's responses, not its underlying queries.
Yes, this is a common failure mode ContextQA is built to catch.
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 →