AI-assisted incident investigation from first signal to next action
Merlin is designed to help engineers reconstruct an incident from operational telemetry, identify related symptoms and keep the investigation focused on verifiable evidence.
Reconstruct the sequence, not just the latest error
When a service fails, the loudest alert is often not the first useful signal. A downstream component may report thousands of errors even though the initiating condition appeared minutes earlier somewhere else. Incident investigation therefore depends on reconstructing the sequence around the failure.
Merlin’s investigation model is intended to help an operator move backwards and forwards through that timeline, connect symptoms across systems and ask targeted follow-up questions.
A practical investigation flow
- Define the symptom. Start with the affected service, error window or user impact.
- Expand the evidence window. Look before the visible failure for changes that may have initiated it.
- Correlate systems. Compare events from dependencies and neighbouring services.
- Test the explanation. Check whether the proposed cause consistently explains the observed sequence.
- Choose the next action. Prefer actions supported by the strongest evidence and verify recovery afterwards.
Why natural-language investigation can help
Once the relevant evidence set is established, conversational follow-ups can reduce the friction of repeatedly rebuilding queries. The important requirement is that each answer remains traceable to the operational evidence.
Related Merlin topics
Turn operational noise into a clearer investigation.
Merlin is being built to help operations teams connect log evidence, operational signals and natural-language investigation in one workflow.