Domain Experts view
Govern every run, from trace to outcome.
See exactly what your AI did, and why it did it. Then prove it to anyone who asks.
Dashboard
Traces
Sessions
Observations
Avg. Latency
Avg. Session Duration
Scores
Traces
Traces Tracked
1,000
Report
Models
Cost
$0.07
Report
Every session on the record · Tied to the policy that fired · Analytics across runs · Export the audit report
Every turn
Traced and replayable
Every decision
Tied to a named policy
Every edit
Named, reversible, no ticket
OpenTelemetry
Open, no lock-in
Most AI platforms ship prompt logs. InteractiveAI ships a decision record.
Which policy fired, which tools ran, and the outcome that followed, captured per decision on every run.
Built to evidence EU AI Act Article 13 transparency and traceability obligations for high-risk AI, turn by turn. See Trust & Security →
Replay exactly what the AI did, in plain language.
Step through any session the way it happened: what the customer asked, which rule the agent followed, what it decided. No log lines, no engineering ticket, just the story of the run, ready to export as an audit report.
Step-by-step replay
Walk any run start to finish, in plain language.
Full conversations
Replay a customer's whole multi-turn session.
Plain-language view
Every step described in words, not log lines.
Every observation
Each step inside the run, captured as it happened.
Question
Analyze this refund dispute, ticket #8421.
Answer
See the operational pattern across thousands of runs.
Usage, containment, resolution, cost, and latency aggregate from the same record your auditor reads. The operational view of what production is doing, with nothing to reconcile and no second pipeline.
Usage and containment
Volume, containment, resolution, and transfer over time.
Cost and latency
Roll up across models and environments.
By use case
Compare operational health across teams and flows.
One source
The analytics read the same record the auditor does.
Prove which rule decided, and stand behind it.
Every answer traces back to the exact rule that produced it and the person who reviewed it. Roll any change back in one click, and hand the auditor a complete record. No engineering ticket, no waiting.
Which rule fired
Every answer linked to the policy that produced it.
Who changed what
Every edit logged with who, when, and what.
One-click rollback
Roll any change back to a previous version.
Auditor-ready
Generate the audit report on demand.
Bring any model
Any model you trust, run with governance and tracing.
Route any provider through one gateway with your own keys, every call attributed and on the record.
More on Governance
Read the thinking. See it shipped.
How to Build and Run AI Your Teams Actually Own
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How to Choose the Infrastructure Your AI Will Run On
Once a company decides to build its own AI, it inherits an infrastructure question nobody hands it upfront. Not compute. Not models. The layer that decides whether you own what you built.
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Jul 23, 202611 min readInfrastructurePlatformInsightRead
How to Manage Context for Production AI Agents
The hardest problem in production AI is not the model. It is getting the right rules and knowledge to the model at the moment of every decision, on every turn.
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Jul 13, 202614 min readContextInteractive AgentsInsightRead
How to Run AI in Regulated Industries
A strategic framework for 2026 and beyond: how to put production AI on regulated systems you can govern deterministically, prove on demand, and operate under your own control, before the obligations arrive.
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Betsson France: Production AI for Regulated iGaming Support
How Betsson France made ~75% of customer support autonomous, eliminated 30+% of tickets at root cause, and enforced compliance on every interaction.
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Governance
Trust the AI you put in production.
Walk your security, compliance, and operations teams through sessions, traces, observations, analytics, and the audit report in one operational view. One session, end to end.