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The Problem: Across manufacturing plants, power grids, water utilities, and physical infrastructure, billions of dollars of critical equipment relies on legacy analog instruments — needle pressure gauges, thermometers, mechanical switches, and indicator lights. These instruments are completely dark to modern SCADA, telemetry, and cloud monitoring. Digitizing them typically requires shutting down active assembly lines, cutting pipes, installing expensive IoT transducers, and pulling miles of industrial wiring — costing upwards of $10,000 to $50,000 per control panel. The Solution: Retrofit Retrofit bridges this physical-digital divide with zero hardware modifications. Point any off-the-shelf camera or smartphone at an analog panel, and Retrofit instantly transforms every gauge, dial, and light into a live, typed, queryable WebSocket/REST data stream — complete with autonomous AI agents monitoring operations and diagnosing anomalies in real time. How It Works (The 5-Layer Architecture): 1. Perception (SAM 3.1): Multi-object segmentation identifies and tracks every instrument on the panel simultaneously across noisy physical environments without pre-existing CAD templates. 2. Understanding & Tool Compilation (Muse Spark 1.3): Muse Spark classifies instrument types, units, and calibration ranges. To avoid crippling cloud latency and per-frame API costs, Muse Spark implements our core breakthrough: "the model compiles itself out of the runtime loop." It writes deterministic, sandboxed Python reader algorithms on the fly, verifies them against a held-out test suite, and compiles them for execution on local camera frames at native FPS with zero marginal inference cost. 3. Autonomous Rule & Incident Agent (Muse Spark Open via Baseten): Operators write natural language rules ("alert when pressure goes above 80 PSI"). Meta's open-weight Muse Spark Open compiles these into executable predicate chips. When a threshold is breached, Spark Open acts as an autonomous incident agent, instantly generating concise operator diagnostics and remediation steps in the operational feed. 4. Voice Telemetry (Muse Voice Transcribe 1.0): Field engineers log spoken operational notes, which are converted to 16 kHz WAV and transcribed directly onto the live telemetry timeline. 5. Cross-Series Causal Reasoning (Muse Wonder 1.0): When engineers ask "Why did pressure spike?", Muse Wonder synthesizes the multi-instrument time series, rate-of-change statistics, and operator voice notes into grounded root-cause explanations citing exact numerical evidence. Real-World Impact: Retrofit democratizes industrial telemetry. For the price of a $20 webcam or a repurposed smartphone, any facility in manufacturing, agriculture, or energy can bring decades-old machinery into the modern AI era overnight.