Turn ExistingRobot Telemetryinto Production AI, Fast
Orca bolts onto your streaming infrastructure to orchestrate sensor-to-model pipelines in Days, not Months
Why Orca?
Build analytics that follow your intuition
Stop Orchestrating Analytics by Hand
Orca orchestrates AI pipelines on top of your existing telemetry streams. Your robotics team writes algorithms while Orca handles scheduling and data freshness.
Analytics-First Timeseries Orchestration
Built for high-frequency sensor data already flowing through your infrastructure. Apply custom ML to LiDAR, IMU, and motor telemetry without touching your ingestion layer.
Algorithm Engineer First
Python and Go SDKs connect directly to your existing telemetry infrastructure. Write analysis code and Orca orchestrates execution across your fleet data without infrastructure changes.
Capture the 10,000th Robot Action from Your Existing Streams
Event-driven triggers tap into your current telemetry store. When your robot arm enters an unmapped failure position, Orca detects it from your existing telemetry feed and launches diagnostics instantly.
Training Data Lineage from Ingestion to Model
Full provenance across your existing data stack-from event trigger to training label.
Reproducible Robotics Analysis on Existing Data
Versioned interfaces ensure your models train on consistent sensor streams from your current data infrastructure, eliminating data drift.
Label your Existing Telemetry, Train Models Instantly
The core orchestrator connects to your event pub-sub streams and triggers analyses when data arrives. This enables robotics engineers to annotate real-world failures from live sensor data and immediately generate training datasets - no data lake migration required.
In-Situ Annotation of Live Telemetry
Label robot sensor streams directly from your existing telemetry store. An arm position or motor anomaly becomes a training label without complex ETL pipelines.
High-Quality Labels from Your Current Streams
Reproducible pipelines mean your autonomous system's training data comes directly from operational telemetry already flowing through your infrastructure.
Close the Loop from Stream to Model
When an anomalous telemetry signal is emitted, Orca captures the telemetry from your existing topic, runs the analysis, generates labels, and triggers retraining - no data movement required.
Build Algorithms in your Preferred Language
Orca supports algorithm dependencies across programming languages so you can use the right tool for the job. Keep ML algorithms in Python and high-throughput metrics in Go!, keeping your stack efficient and lean - all without touching your ingestion layer.
Robot Fleet Reliability, Validated Before Deployment
Robotics pipelines can't fail during production. Orca's compile-time validation guarantees your telemetry analytics are correct before deployment, with automated backfills that query your existing data stores - no brittle glue scripts required.
Tap Into Your Existing Event Streams
Orca subscribes to your current Kafka topics or MQTT streams, triggering diagnostics the moment your robot's IMU detects anomalous vibration.
Freshness on Your Existing Data
Your autonomous vehicle's perception model always trains on the latest data from your existing message bus, not stale warehouse extracts.
Backfill from Your Existing Stores
Missed sensor data? Orca backfills automatically by querying your existing time-series database, isolating failures per robot without affecting fleet-wide operations.
Join robotics and IoT teams building AI on their telemetry infrastructure
Bolt Orca onto your stack and start building autonomous intelligence today
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