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.
Access is restricted to approved organisations — no account yet? Request one.
