Agents self verify to produce proofs that their answers came from the right source and were not changed, increasing reliability and security.
Proofs let downstream agents catch hallucinations or wrong source data without re-querying sources. Agents retry and self heal.
Add the SourceryKit SDK in minutes and verify across agents, tools, and networks without complex tracing or cross-team setup.
$ pip install sourcerykit
Traditional observability needs failures, traces and classification before teams can improve agents. SourceryKit verifies answers and detects errors in real time, powering faster evals and continuous learning loops.
Every run produces a clear pass, caught or error outcome without manual trace classification.
Feed deterministic, evidence backed results into evals instead of relying only on model judges.
Turn verified tool outcomes into trusted reward signals for training and continuous improvement.
Connect SourceryKit to your existing stack and every agent interaction becomes verifiable. Every API call, database query, and MCP server interaction is intercepted and turned into a proof downstream agents can verify in milliseconds.
Customers get answers they can trust, grounded in verified account, order and policy data.
Verifiability lets teams depend on agent operations during critical investigations, even when the full extent of an attack is still unknown.
Verify agent tool calls in payment and patient systems before agents act.
Verifiability enables accurate, safe cross organisational A2A workflows that teams can operate with confidence.
Verify agent operations when original source systems or raw logs are inaccessible.
Create machine verifiable audit trails for EU AI Act reporting, internal controls and independent audits.
AI answers can be fabricated, or cite sources that lead nowhere. Verifiable Search adds SourceryKit to a search engine, so you can check any claim against the text it came from.
Try VSearch




