> ## Documentation Index > Fetch the complete documentation index at: https://docs.archetypeai.app/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Start with /introduction/getting-started. Use the Direct Query API (POST /query) with the Newton Fusion model (text, image, and video reasoning) or the Newton Omega encoder (time-series embeddings). ATAI_API_ENDPOINT must include the version path: /v0.5 for most APIs, /v0.6 for the Fine-Tuning Service. Pages whose descriptions are marked (Archived) document the legacy Lens runtime — do not use them for new projects. # Anomaly Discovery Agent > Discovers novel anomalies and failure modes by distinguishing meaningful issues from normal variation, with no labeled failures required. Every sensor data time window comes back with an anomaly score, flagging behavior that falls outside the norm. The Anomaly Discovery Agent is especially useful for new assets, equipment with long life cycles, and unreachable assets such as deep-ocean or satellite systems where labels cannot be collected. ### Use Cases * **Detect previously unknown equipment issues:** The agent scores every window for how far it departs from normal, so problems you didn't know to look for surface from the data alone. * **Identify emerging process abnormalities:** The agent gives every window a continuous anomaly score, so behavior drifting away from normal shows up as a rising score before it becomes an outright fault. * **Surface novel failure modes:** The agent attaches an anomaly score to every detection, so the most unusual windows can be surfaced first for a person to look into. * **Monitor assets without labeled failure history:** The agent builds its baseline from normal-operation data alone, so an asset with no recorded failures can be monitored from day one. ## See an Interactive Example Try out the Anomaly Discovery agent with a predefined data set using our interactive example. Monitors bearings from a rig and detects when one fails because sensor output deviates from normal. No exemplar data is required. ## Using the Archetype AI Python Client How to use the [Archetype AI Python client](https://github.com/archetypeai/python-client/) to work with the Anomaly Discovery agent. An example that runs an Anomaly Discovery agent on input data using a canonical blueprint and a newly created bundle.