Text classification
Tabular classification
Tabular regression
Introduction video

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Just announced

Powerful testing, evaluation, and observability for LLMs

No more guessing whether or not your prompt is good enough. Treat your LLM product like traditional software development.

1. Push your workflow with a few lines of code

import os
os.environ["OPENLAYER_API_KEY"] = "API_KEY"
from openlayer import llm_monitors
# With publish=True, every row is published to Openlayer
monitor = llm_monitors.OpenAIMonitor(publish=True)

2. Create tests

Suggested tests for LLMs with Openlayer

3. Keep track of your progress

Graph of test results over time in Openlayer

Iterate on agents using
custom workflows
direct API calls

The OpenAI logoThe Cohere logoThe Anthropic logoThe Gemini logo

Automatic testing for your models

Choose from our suite of data quality, drift, and performance tests. They run on each version of your model and data, so you always know where you stand.

A grid of tests that Openlayer offers

Monitor with real-time alerts

Keep a close eye on your models in production and receive alerts wherever you spend your time — email, Slack, or in the Openlayer app.


Deployment status changed
To 🟢 Ready to deploy  From 🔴 Not ready


@sophia commented on No duplicate rows
– thoughts on changing the threshold?


Test status updated for No output drift
To 🔴 Failing  From 🟢 Passing

Overview of monitoring dashboard in Openlayer

Track and version

Say goodbye to disorganized folders and spreadsheets. All your models, datasets, and prompts live in a familiar commit system so you can effortlessly track and compare versions.

Overview of experiment tracking in Openlayer

Designed to be developer-first

60-second onboarding

Upload your models and datasets straight from your training notebooks or pipelines. With one simple call to our API, your models are auto-magically loaded and deployed.

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Openlayer logo with dashed lines

Commit-style versioning

Effortlessly track every change, just like you do with code. Our commit-style versioning system enables quick, continuous iteration on your models.

Onboarding code for adding a commit to Openlayer

Seamless notifications

Stay in the loop without breaking your workflow. Receive real-time updates on model performance, data anomalies, and team activities directly to Slack, email, or in-app.


@sophia commented on No duplicate rows
– thoughts on changing the threshold?


Test status updated for No output drift
To 🔴 Failing  From 🟢 Passing

Secure deployment

Secure your data with our SOC 2 Type 2 compliant platform and on-premise hosting option. Take control of your models and datasets, ensuring they never leave your infrastructure.

SOC 2 Type 2 compliant logo

Read the documentation

Get started with setup instructions, walkthrough tutorials, and the API reference.

What others are saying

Debugging error cases is the highest leverage way to improve ML systems. Openlayer makes it easy to debug those cases and, more importantly, helps fix them as well. I highly recommend using it in all ML workflows

Gautam Kedia

Head of Fraud ML at Stripe

The Openlayer team deeply understands the challenges faced by the ML community. Their platform is the best way to streamline the evaluation and analysis of models to drive continuous improvement in AI.

Max Mullen

Founder of Instacart

Openlayer is building the critical infrastructure for the safe deployment of AI at planetary scale.

Guillermo Rauch

Founder & CEO of Vercel

Openlayer has been a valuable asset to our team. The platform's timeline feature is excellent for tracking progress, and collaborating has become effortless. This is a top-notch platform for gaining insights into ML models.

Rishabh Gupta

Lead Data Scientist at Zuma

I've witnessed first-hand the critical importance of error analysis in the world of machine learning. The Openlayer platform can save countless debugging hours and significantly improve model performance for data scientists worldwide.

Mark Belvedere

Data Science Director at Meta

Openlayer is a unique, data-centric ML solution that supports test-driven development and data quality analysis. This tackles a critical problem around ML data intelligence that only grows with the increased ubiquity of AI.

Astasia Myers

Enterprise Partner at Quiet Capital