EntroPi AI

NBot Horizon

The observability and training plane for the nbot cognitive pool — trace it, evaluate it, train it.

Trace

Every nbot session becomes an inspectable run → turn → span tree.

Debug

Drill into any step's raw payload; failures are surfaced first-class.

Evaluate

Score nbot against curated suites of cases, with full history.

Train

Turn real usage into RL datasets and train the live policy.

Routing · planning · decomposition

Optimise how the pool routes, plans and decomposes tasks — learned from real outcomes.

Prompt optimisation

Optimise prompts against a goal — quality within latency, token or cost budgets.

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