Predictive Maintenance Platform

Stop Robot Downtime
Before It Happens

RobotOps predicts failures, diagnoses issues in plain English, and routes alerts to the right people. One platform to keep your entire fleet running.

40%
Less unplanned downtime
3x
Faster issue resolution
5+
Vendors supported
RobotOps — Predictive Analytics
Predictive Analytics
Learning Active
🤖
AMR-007
Locus Origin
87%
Confidence
Motor bearing wear detected
Left drive motor showing early vibration patterns consistent with bearing degradation
Schedule maintenance within 72 hours
Est. repair: 45 min
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AMR-012

Battery health optimal

Healthy

Robot fleets are hard to maintain

Your robots throw cryptic errors. Your experts are stretched thin. And downtime costs a fortune.

🔴

Failures happen without warning

Robots go from "fine" to "dead" with no warning. By the time you know there's a problem, throughput is already impacted.

Error codes mean nothing

When a robot fails, it throws opaque codes nobody on shift can interpret. "Error 0x4F2A" doesn't tell your team what to do.

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Too few experts, too many robots

Modern robots require expertise in mechanics, electronics, and software. Those people are expensive and can't be everywhere.

AI that keeps your fleet running

RobotOps combines predictive analytics, AI diagnostics, and smart routing to solve your maintenance problems.

Problem: Surprise failures

Predict failures before they cause downtime

RobotOps learns your fleet's normal behavior and spots anomalies that indicate upcoming failures. Get actionable predictions with confidence scores and recommended maintenance windows.

ML-based anomaly detection learns from your telemetry
Confidence scores help you prioritize maintenance
Suggested maintenance windows minimize disruption
Live from Predictive Analytics
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AMR-003
6 River Chuck
92%
Confidence
Battery capacity degradation
Charging cycles showing 15% reduced capacity vs. baseline. Recommend battery replacement.
Order replacement battery
Lead time: 5 days
Problem: Cryptic error codes

AI Copilot that speaks your language

When something goes wrong, RobotOps translates error codes into plain English and walks your team through diagnosis step by step. Like having a robot expert on every shift.

Natural language explanations of any error
Step-by-step troubleshooting guidance
Links to official manufacturer documentation
Live from AI Repair Copilot
👤
AMR-007 is showing error 0x4F2A and won't move. What's wrong?
🤖
Error 0x4F2A: Motor Overtemperature

The left drive motor has exceeded safe operating temperature. This is usually caused by:

1. Dust buildup in motor vents (70% of cases)
2. Overloaded tasks exceeding weight limits
3. Bearing wear causing friction

Recommended: Let motor cool for 15 minutes, then inspect vents for debris. Your team can handle this.
Problem: No visibility

Real-time fleet dashboard across all vendors

See your entire fleet in one view, regardless of manufacturer. RobotOps normalizes telemetry into a unified schema so you can compare health and performance across vendors.

Unified view of Locus, 6 River, MiR, Fetch, and more
Real-time status, battery, location, and health
Compare vendor performance with normalized KPIs
Live from Fleet Dashboard
12
Online
2
Warning
1
Offline
98.5%
Uptime
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AMR-001 (Locus)
Active
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AMR-007 (6 River)
Low Battery
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AMR-012 (MiR)
Active

Alerts where your team already works

Get the right information to the right people through Slack, Teams, email, or embedded in your WMS.

💬

Slack

Slash commands, interactive alerts, and fleet status right in your channels.

/robotops-status Interactive buttons
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Microsoft Teams

Adaptive Cards with rich formatting and one-click actions for your team.

Adaptive Cards Action buttons

Email Digests

Daily or weekly summaries with fleet health, incidents, and predictions.

Scheduled reports Custom recipients
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Embeddable Widgets

Drop fleet status into your WMS or internal dashboards with one script tag.

CORS enabled JSON API

How RobotOps connects to your fleet

1

Edge Agents

On-prem agents execute workflows locally with sub-second latency. Works offline, syncs when connected.

2

Context Graph

Events link into causal chains. When a battery dies, see the temperature spike that caused it.

3

Pattern Learning

Every repair teaches the AI. The pattern library learns which fixes work for which symptoms.

4

Safety Recommendations

AI recommends E-Stop or Safe Stop when needed. Operators acknowledge and track actions taken.

Ready to stop chasing robot failures?

Book a demo to see how RobotOps can predict problems before they impact your operations.