AI Agent Testing

Your agent is going live.
Nobody knows what it'll do next.

Test every response, guardrail, and tool call across model upgrades. No SDK, no instrumentation, no code access required. ContextQA probes your agent the way your customers do.

340K⁺

Adversarial scenarios generated against live agents

12%

Hallucination rate uncovered in production-bound agents

1,200⁺

Model-upgrade regression runs executed every week

Coverage

Every agent risk, covered

Agents fail in ways traditional testing never catches. ContextQA scores every response against functional, safety, and behavioral criteria before your customers hit the bug.

Response accuracy

Score factual correctness, tone, and policy adherence on every agent reply using configurable AI judgment combined with deterministic checks against your source of truth.

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Guardrail enforcement

Probe every safety boundary: PII disclosure, refund overrides, policy violations, unauthorized actions. Catch the bypass before a bad actor does.

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Tool-call validation

Verify every function call your agent makes: right tool, right arguments, right outcome. Catch broken integrations and silent tool failures before they ship.

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Red-team adversarial testing

Hundreds of hallucination traps, jailbreak attempts, and adversarial prompts auto-generated from your agent's docs, policies, and conversation logs.

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Model-drift regression

Re-run your full scenario suite against every model upgrade. Surface behavioral drift, tone shifts, accuracy drops, and policy regressions before rollout.

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Compliance & PII enforcement

Every response is scanned for leaked PII, unauthorized disclosures, and compliance violations including HIPAA, GDPR, and SOC 2. Catch the breach before audit does.

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How it works

How ContextQA makes your agent trustworthy.

From scenario generation to continuous regression, every response, guardrail, and edge case scored before it reaches production.

AI-Generated Test Scenarios

Analyzing agent docs...

Upload your agent's docs or describe its behavior and ContextQA generates hundreds of adversarial and functional scenarios including hallucination traps, edge cases, multi-turn conversations, and policy violations you'd never think to write by hand.

No SDK. No code access. No problem.

Bedrock Black-box test

4 probes · 1 failed

Your agent lives on Agentforce, Bedrock, Cortex, or another platform and you can't instrument the internals. You don't need to. ContextQA tests from the outside, the way your customers actually experience it.

AI-powered judging, deterministic proof

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AI Judgment

Deterministic Checks

Confidence 94%

When there's no single right answer, you need more than a string match. Every response is scored against configurable criteria using AI judgment and deterministic checks. You get a confidence score, not a gut feeling.

Continuous regression testing

Comparing model versions...

Every model upgrade is a regression risk. ContextQA re-runs your full scenario suite against each new version and surfaces behavioral drift before it ships.

Why it works

How ContextQA keeps agents trustworthy

Testing AI agents isn't testing software. ContextQA combines generative scenario discovery, platform-agnostic probing, and evidence-based scoring so confidence is measurable, not hoped for.

Scenarios write themselves

Your agent's docs, logs, and policies become hundreds of adversarial and functional test cases, updated as your agent evolves.

Black-box by design

Test any agent on any platform from the outside. No SDK, no instrumentation, no privileged access needed.

Evidence, not vibes

Every response gets an AI-judged quality score plus deterministic checks against your source of truth. Confidence you can ship on.

Always-on regression

Model upgrades, prompt tweaks, retraining: every change triggers a full regression run. Drift caught before deploy.

"ContextQA transformed our release workflow. What once took days or even weeks of manual testing now happens in a fraction of the time. Our team scaled automation 10x without needing specialist coders."

David Jin

Senior Software Engineering Manager

Clari

Breadth of coverage

Test every dimension

Agents don't fail in one way. ContextQA covers every surface, every input, every layer of your stack, so confidence travels with your agent wherever it runs.

Platform-agnostic

Works with every major enterprise agent platform: Agentforce, Bedrock, Azure AI, Cortex, Fin and custom agents. No SDK, no code access, no privileged hooks.

Modality-agnostic

Text, voice, file uploads, images, multi-modal: test agents the way your customers use them. Every input surface your agent exposes, ContextQA probes.

Deep verification

Don't just check the reply, verify the outcome. Run SOQL queries, call your APIs, inspect DB state, confirm downstream data was created or updated correctly.

Load & performance

Probe your agent under concurrency. Simulate 10, 100, or 1,000 simultaneous sessions. Measure p95 latency, SLA breaches, and degradation curves before customers feel them.

Multi-turn & stateful

20+ turn conversation chains with branching logic, escalation flows, and context carry-over. Catch the bugs that only emerge mid-conversation.

Comprehensive reporting

Regression diffs, confidence scores, audit trails, and executive summaries. Export to CI dashboards or share a read-only link with stakeholders: every run, every result.

How we compare

Purpose-built for agent validation

Most AI testing tools are either observability platforms watching production traffic or SDK-first libraries requiring code-level access. ContextQA is neither. It is pre-launch, black-box, and built for agents you don't control the source code of.

← Swipe to compare →

Capability	ContextQA	Promptfoo	Arize / Galileo	Manual QA
Primary focus	✓Pre-launch validation & regression	Pre-launch red-team	Post-launch observability	Pre-launch, manual
SDK / code instrumentation required	✓None	✓None (CLI + YAML)	Required. OpenInference / OTel SDK	✓None
Tests closed-source platforms (Agentforce, Bedrock Agents, Foundry)	✓Native black-box, any platform	Partial. Per-platform provider config	Not without agent-code access	Manual chat only
Auto-generated scenarios & personas	✓Hundreds, from docs & logs	✓Red-team synthesis from `purpose`	Manual notebooks / synthetic cookbooks	Hand-written
Deterministic checks (API, SOQL, DB state)	✓Native, hybrid with AI judgment	Partial. Custom assertions	Custom evaluator code	Not scalable
Tool-call validation (args + outcome)	✓Argument + outcome verified	Not a first-class primitive	Traced. You wire the checks	Manual check
Load & performance testing	✓Concurrency, p95 latency, SLA	Not a documented capability	Post-launch observation only	Not scalable
Multi-turn conversation chains	✓20+ turns, branching, escalation	✓Crescendo / GOAT strategies	✓Via trace capture	Slow & inconsistent
Model-drift regression on upgrades	✓Full suite on every version	Eval comparison across providers	Experiments module	Not scalable
Comprehensive reporting & audit trails	✓Regression diffs, exec summaries, signed reports	Dashboards + CI exports	✓Strong. Core observability	Ad-hoc

Integrations

Plugs into your stack

CI/CD, project management, cloud platforms, AI agents. ContextQA connects to the tools you already use.

Enterprise-grade agent evaluation

Run ContextQA in your environment with secure on-prem or private cloud options. Your data and your agents' secrets never leave your infrastructure.

99.9%+ uptime

Battle-tested infrastructure you can trust in production and at scale.

SOC 2, ISO 27001, GDPR

Enterprise-grade security, certified for sensitive and regulated data. View our security policies here.

Enterprise support & SLAs

Hands-on forward-deployed support and tailored SLAs to meet your enterprise needs.

Deploy in your environment

Run ContextQA entirely within your own infrastructure, ideal for strict security, compliance, and data residency requirements.

FAQ

Frequently asked questions

ContextQA tests your AI agents as a black box, the same way your customers interact with them. It generates adversarial scenarios (hallucination traps, policy violations, multi-turn edge cases), sends them to your agent, and scores every response using configurable AI judgment and deterministic checks. No SDK or code access required.

Any agent platform including Salesforce Agentforce, Amazon Bedrock, Azure AI Foundry, Snowflake Cortex, Intercom Fin, and custom-built agents. Because we test from the outside, there is nothing to instrument on the platform side.

Point ContextQA at your agent's documentation, system prompt, policy files, or conversation logs. It reverse-engineers behavior models and generates hundreds of functional, adversarial, and multi-turn scenarios automatically. You can also author custom scenarios in plain English.

LLM-as-judge alone is noisy and subjective. ContextQA combines configurable AI judgment (accuracy, tone, policy, factuality) with deterministic checks (API calls, DB queries, assertions against your source of truth). You get a confidence score backed by evidence, not a vibe.

Yes. ContextQA generates hallucination trap scenarios, questions whose correct answer ContextQA knows in advance, and deterministically verifies the agent's response. Fabricated pricing, competitor data, product facts, and policies are caught before they reach customers.

Yes. ContextQA simulates full multi-turn chains up to 20+ turns with branching logic and escalation flows. Critical for support, sales, and any agent that holds state across a conversation.

Every model upgrade triggers a full regression run. ContextQA compares v3.1 vs v3.2 across accuracy, tone, policy adherence, and factuality and surfaces behavioral drift before you deploy. Catches the silent regressions that cause real incidents.

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.

Stop guessing. Start shipping agents you've actually tested.

See how ContextQA validates every response, guardrail, and tool call before your customers find the bugs.

Your agent is going live.
Nobody knows what it'll do next.