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AI Observability & Explainability

Observable and Explainable AI That Enterprise Teams Can Trust

Gain full visibility into AI agent behavior with conversation history, session replay, decision paths, prompt and context inspection, validation metrics, and audit-ready logs, built for enterprise scale, governance, and control.

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End-to-End Traceability

From First Message to Final Action

Every interaction is logged, timestamped, and indexed. Replay sessions, jump to the exact flow step, and inspect per-message integration logs to see precisely how an agent moved through tools and functions.

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Enterprise-ready Explainability

Decision Paths, Not Black Boxes

See an explainable “decision path” for each conversation, how intents were resolved, what data was retrieved, and why actions were taken, so authors can fix issues fast and prove compliance.

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Quality + Speed

Built-In QA & Regression Testing

Druid’s QA Agent auto-tests flows and knowledge answers with persona, A/B, and regression runs to catch hallucinations and edge cases before go-live, accelerating UAT without sacrificing quality.

See, Prove, and Improve

Total Visibility into Behavior, Decisions, and Outcomes

Druid combines observability, explainability, and QA so authors can understand behavior, validate outputs, and iterate confidently, backed by analytics and auditability.

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Decision Path Explorer

Follow every step, tool call, integration, and branch, complete with timestamps and total runtime, to explain outcomes and resolve issues faster.
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Conversation History & Replay

Search any session, then replay it with flow/step-level debugging. Inspect messages, transitions, and integration logs; pinpoint quickly where to optimize.
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Activity History & Explainability

Diagnose recognition issues with per-utterance match status and top-N scores; use LIME to see word-level contributions and fix utterances directly.
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Audit Trail & Compliance Exports

Retain change history (who/what/when) with visual differences and export conversation history for offline analysis, retraining, or review.

Questions & Answers

Frequently asked questions

Get answers to the most common questions about Druid's observability capabilities and the agentic AI orchestration engine that works in the enterprise.

How does Druid show an agent’s decision path without exposing raw model internals?

Through a step-by-step trace of prompts, integrations, retrieved data, and outcomes—plus LIME intent explanations—so teams can improve behavior without revealing.

Can authors replay and inspect past conversations for auditing?
Yes. Every interaction is logged, timestamped, searchable, and replayable; exports are available for offline analysis and review.
Can Druid run observability in regulated, on-prem environments?
Yes. Druid supports the governance and audit trails required for regulated reviews, with deployment flexibility across environments.
Do you support automated testing before release?
Yes. The QA AI agent runs regression, A/B, and persona-based tests to validate flows, knowledge answers, and actions pre-launch. 
What analytics are available out of the box?
Dashboards show usage, accuracy, containment, escalation, ROI, and more—with drill-downs to transcripts and events for root-cause analysis.

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Validate Before You Scale

Leverage AI Observability For Your Next Release

Schedule a guided session with our experts to see how you can trace AI agent decisions, inspect prompts, review validation metrics, and leave with a concrete plan to improve accuracy and governance in your environment.

Book a Guided AI Observability Session