OpenAI builds and deploys advanced AI models like GPT-4o for autonomous agents and workflows.
QAgent
$2499Starting price
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About QAgent
QAgent is an automated quality assurance suite designed for AI agents, enabling developers to test correctness, hallucination rates, and policy adherence before deployment. It connects to an agent via webhook or endpoint URL without requiring an SDK, allowing tests to run in under two minutes. The platform evaluates agents across eight deterministic dimensions including answer quality, anti-hallucination, policy adherence, RAG faithfulness, and multi-turn context memory. Tests are structured around three core ingredients: ground truth rules, test rubrics with RFC 2119-style requirements, and the actual agent responses. This approach eliminates subjectivity by cross-examining each response against predefined criteria using high-speed Groq LPUs. QAgent is particularly suited for solo developers and agile teams who lack dedicated QA resources but need reliable validation of AI agent behavior. Typical use cases include verifying compliance with pricing policies, detecting prompt regressions, and ensuring accurate citations in retrieval-augmented generation systems.
Key features
- Webhook-based agent connection in under 2 minutes
- 50+ automated test cases per evaluation
- RAG citation verification across knowledge chunks
- Multi-turn conversation context memory testing
- Prompt regression tracking on every release
- Adversarial attack simulation for guardrail testing
- Deterministic LLM-as-a-judge scoring engine
- Custom ground truth and RFC 2119 test rubrics
Use cases
- Validating compliance with pricing and refund policies
- Detecting silent prompt regressions before customer impact
- Ensuring accurate citations in retrieval-augmented generation systems
Pros
- Zero-setup integration via webhook without SDK
- Deterministic scoring across eight evaluation dimensions
- Automated detection of hallucinations and policy violations
- Parallel execution of adversarial and edge-case tests
- Transparent audit trails with step-by-step failure analysis
Cons
- No free tier beyond 100 evaluations per month
- Requires webhook or endpoint URL for integration
- Limited to automated testing without manual review options
Frequently asked questions about QAgent
What is QAgent and what does it do?
QAgent is an automated quality assurance platform designed to test AI agents for correctness, hallucination rates, and policy adherence before deployment. It evaluates agents across eight deterministic dimensions using high-speed Groq LPUs.
Who is QAgent designed for?
QAgent is built for solo developers and agile teams who lack dedicated QA resources but need reliable validation of AI agent behavior. It is particularly suited for those who want to ensure their AI agents meet strict compliance and accuracy standards.
How does QAgent work?
QAgent connects to an agent via webhook or endpoint URL without requiring an SDK. It evaluates agents using three core ingredients: ground truth rules, test rubrics with RFC 2119-style requirements, and the actual agent responses, cross-examining each response against predefined criteria.
What are the key dimensions QAgent evaluates?
QAgent evaluates agents across eight dimensions, including answer quality, anti-hallucination, policy adherence, RAG faithfulness, search quality, contextual relevancy, completeness, and multi-turn context memory.
Does QAgent require an SDK to connect to an agent?
No, QAgent does not require an SDK. It connects to an agent via webhook or endpoint URL, allowing for a quick two-minute setup.
How can I get started with QAgent?
To get started, paste your agent endpoint URL, LangChain workflow, or webhook into QAgent, define your ground truth rules and test rubrics, and run the automated tests to receive a quality score and detailed audit results.
