# What is Agentic Investigation?

> An AI agent working a ticket the way an engineer would: hypothesis, evidence, conclusion.

Canonical: https://www.decimal.app/glossary/agentic-investigation · Last reviewed: 2026-09-23

Agentic investigation is the use of an AI agent to diagnose a customer issue rather than just retrieve an answer. The agent forms hypotheses, queries logs and traces, reads the relevant code, checks recent deploys, and narrows down to a root cause with the evidence attached.

## Why it matters

Retrieval tools stop at what's already written down. The hardest tickets are about things nobody has documented yet: a new regression, an edge case in one customer's config. Those are the tickets that end up in engineering's queue, and investigation is the only way to close them faster.

## Best practices

1. Start from the customer's symptom. Feed the agent the ticket, the account, and the time window so it can scope its search.
2. Show the trail. A good investigation reads like a short incident note: what was checked, what was ruled out, what was found.
3. Measure on escalations. Judge it by how many engineering escalations it prevents or shortens, not by deflection alone.

## How Decimal helps

Investigation is Decimal's core. It connects to code, observability, ticketing, and data sources so each ticket gets a cited diagnosis, not a guess.

## Related terms

- [AI Agent](https://www.decimal.app/glossary/ai-agent): Software that plans, uses tools, and acts toward a goal instead of answering one prompt.
- [Root Cause Analysis (RCA)](https://www.decimal.app/glossary/root-cause-analysis): Finding the underlying reason a problem happened, not just its symptoms.
- [Engineering Escalation](https://www.decimal.app/glossary/engineering-escalation): A ticket support hands to engineering because it needs code-level investigation.
- [Retrieval-Augmented Generation (RAG)](https://www.decimal.app/glossary/retrieval-augmented-generation): Having an AI model look up relevant documents before generating an answer.

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