Testing Intercom Fin Agents
A support agent that makes up a plausible sounding but false policy answer creates a real customer trust problem, not just a bad interaction. ContextQA tests Intercom Fin the way a customer actually experiences it, catching these failures before they reach someone who will act on the wrong answer.
Black-box, by design
Support teams can review transcripts after the fact, but that only catches problems after a customer has already been given wrong information. There is rarely a standing process to proactively test the agent against edge cases and policy questions before they happen. 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.
“A refund exception outside documented policy.”
Checking the response against policy docs
Agent invented a plausible but false answer — caught
What this catches before customers do
Catch an invented policy
“Can this catch a support agent making up a policy that does not exist?”
Yes — one of the primary scenarios this integration is built to catch.
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 primary scenarios this integration is built to catch.
No, testing is based on the agent's actual responses to real scenarios.
Most teams run it on a schedule and again after any change to policies or the agent's configuration.
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 →