The observability platform built for ML engineers. Monitor model performance, trace inference pipelines, and catch regressions before they hit production.
From real-time inference monitoring to comprehensive model performance analytics, Prism gives you the full observability stack your ML pipeline demands.
Instrument your inference pipelines with zero overhead. Trace every request from input to output with sub-millisecond latency.
Automatically detect data drift and concept drift. Get alerts when model performance degrades before your users do.
Build tailored dashboards with drag-and-drop widgets. Monitor latency, throughput, error rates, and model metrics in one place.
Set up intelligent alerts based on model metrics, not just system metrics. Get notified when accuracy drops or latency spikes.
SOC 2 Type II certified. End-to-end encryption for all traces. Role-based access control and audit logging for compliance.
First-class SDKs for Python and TypeScript. Native integrations with LangChain, LlamaIndex, and popular ML frameworks.
Three simple steps to full observability. No infrastructure changes, no configuration files, no complexity.
Drop our SDK into your project. One line of code instruments your entire inference pipeline. No service mesh, no sidecars.
Define your model endpoints, set baseline metrics, and configure drift thresholds. Prism auto-discovers your pipeline topology.
Watch real-time traces, get alerts on anomalies, and use our AI-powered recommendations to optimize model performance.
Start free. Scale as you grow. No hidden fees, no surprises.
Perfect for side projects and experimentation.
Get Started FreeFor teams shipping ML to production.
Start Free TrialFor organizations with advanced needs.
Contact SalesSee why thousands of ML engineers trust Prism for their production AI pipelines.
"Prism caught a 15% latency regression in our production model that our existing monitoring completely missed. It's become indispensable for our MLOps workflow."
"The drift detection is a game-changer. We went from manually checking model performance weekly to getting automated alerts the moment something goes wrong."
"We integrated Prism into our LLM serving pipeline in under an hour. The traces are incredibly detailed and the UI is beautiful. Best observability tool we've used."