AGENT EVALUATION & REGRESSION ENGINEBETA

Test Your AI Agent Before Production

Generate realistic test scenarios, run them against your AI agent, evaluate responses and tool calls, and automatically build regression tests from failures.

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Evaluation Tools & Testing Modules

Choose a specialized evaluation framework to inspect your agent, model, or retrieval pipeline.

FLAGSHIP

Agent Evaluation Lab

Systematically test chatbots, RAG systems, and tool-calling agents with synthetic test cases. Evaluates responses, tool selections, parameter accuracy, and automatically generates regression tests from failures.

Open Tool REST / API Ready
BENCHMARK

LLM Evaluation

Benchmark raw LLM completion performance across Anthropic Claude Sonnet 5.5 LLM, OpenAI, and Llama models for adherence, token efficiency, hallucination rate, and instruction-following.

Open Tool REST / API Ready
ACCURACY

RAG Evaluation

Evaluate RAG retrieval pipelines against golden question-context-answer triples. Measures Faithfulness, Context Relevance, and Answer Groundedness without hallucinations.

Open Tool REST / API Ready
CONTINUOUS EVALUATION LOOP

How Sylvaera Evolves Your AI Agent Workflow

Turn evaluation into continuous production readiness. Instead of one-off chat testing, build persistent regression suites that protect every code commit and prompt change.

1
Generate Dataset
Create edge cases in AI Training Dataset Studio.
2
Execute & Evaluate
Run tests against HTTP agent, track latency & tools.
3
Diagnose Failures
Pinpoint tool mismatches and safety violations.
4
Synthesize Regressions
Generate 8+ adversarial variations and retest.
Free Plan: 1 Project, 1 Run, up to 6 Test Cases • Developer Pro: Unlimited Projects & Runs + Claude Sonnet 5.5 LLM-as-a-Judge
Launch Evaluation Lab