50+ teams already building on mlops.dev — free for fleets under 10 devices.
4 devices online — fleet healthy

ML models. At the edge. In production.

Deploy, monitor, and heal ML models across Jetson boards, Raspberry Pis, and custom ARM hardware — even when the internet is gone. The MLOps platform built for the real world.

4
devices online
<8MB
agent binary
99.7%
sync uptime
<90s
deploy latency
mlops.dev — fleet monitor LIVE
TOTAL
6
ONLINE
4
OFFLINE
1
DRIFT⚠
1
The problem
Your CI/CD pipeline
works perfectly
until the Jetson
goes offline.
We built for that.
PROBLEM 01
Offline devices, stale models
Traditional CI/CD fails silently when devices lose connectivity. Models drift for weeks — no alert, no rollback, no visibility.
PROBLEM 02
SSH scripts aren't operations
Bash loops and cron jobs get you to 10 devices. They collapse at 100. No audit trail, no rollback, no canary.
PROBLEM 03
Flying blind in production
W&B tracks training. MLflow tracks experiments. Nothing tells you what's actually running on 3,000 boards right now.
Platform specification
MLOps.dev Edge Runtime
REV 3.2 · PRODUCTION
Agent binary
<8MB
ARM64 / ARMv7 / x86_64
Fleet scale
10K+
devices per deployment
Sync uptime
99.7%
tested on 2G cellular
Deploy latency
<90s
edge to production
Drift detection
Statistical monitoring on input distributions. Fires Slack, PagerDuty, or any webhook before users notice degradation.
Canary deployments
Roll to 1%, 10%, or any device group first. Automatic health gate blocks rollout if accuracy drops.
Offline-first sync
Devices buffer telemetry locally during outages. Delta-compressed sync reconvenes on reconnect. No data loss, ever.
Getting started

From training to fleet in under 10 minutes.

01
Push your model
Register any TFLite, ONNX, or TensorRT model. CLI or Python SDK. One command.
$ mlops push ./model.onnx --tag v3.2
02
Install the agent
One-line install on any Linux ARM device. Open-source agent handles everything autonomously.
$ curl -fsSL get.mlops.dev | sh
03
Deploy to fleet
Target by hardware type, location, or device group. Canary rollout with health checks before full fleet.
$ mlops deploy v3.2 --canary 10%
04
Monitor everything
Drift, latency, accuracy — live. Roll back in one click. Sleep through the night.
$ mlops status --fleet production
What teams say

Engineers who've shipped models to the edge.

We were managing 800 factory cameras with SSH scripts. MLOps.dev replaced that in 10 minutes. The offline sync works on our factory floor where Wi-Fi cuts out constantly.
AK
Ananya K.
ML Lead · Manufacturing
Drift alerting caught a data pipeline regression before it hit accuracy on our shelf cameras. That would have been a retailer SLA breach. This is the tool that was missing.
TR
Tom R.
VP Engineering · Retail AI
We're a medical device company. Our FDA submission needed immutable audit logs. MLOps.dev was the only platform that had a real answer to that question.
SP
Sarah P.
CTO · MedTech AI
Pricing

Start free. Scale when it matters.

OPEN SOURCE
Starter
For your first edge deployment. The agent is free, forever.
$0
Free forever · up to 10 devices
  • Up to 10 edge devices
  • Open-source agent SDK
  • Basic fleet dashboard
  • 7-day telemetry history
  • Community support
ENTERPRISE
Enterprise
For regulated industries that need to stay on-premise.
Custom
Unlimited devices · on-premise
  • Unlimited devices
  • On-premise control plane
  • FDA SaMD / ISO 42001 compliance
  • SSO + RBAC
  • Dedicated ML infrastructure engineer
Early access

50 teams are already building on mlops.dev.

We're onboarding design partners — teams deploying their first or fiftieth edge models who will co-build the platform with us. First 100 get lifetime Starter free.

Free forever for fleets under 10 devices
No credit card required
Open-source agent — audit every line
Direct access to founders for setup
Request early access
We'll reply within 24 hours with onboarding instructions.
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Your models are at the edge.
Start managing them.

Free for small fleets. No credit card. Open-source agent.