The AI-Native Operations Platform for Robot Fleets

Predict failures. Resolve incidents. Automate ops.

The first platform that combines fleet-wide telemetry with Agentic AI. Detect silent degradation, auto-diagnose root causes, and automate recovery workflows—without touching your control stack.

🧠 Agentic AI Research 🔮 Predictive Analytics ⚡️ Workflow Automation 🏭 Mixed-Vendor Support
Zero ROS-in-the-cloud required. Works with VDA 5050, ROS 1/2, and vendor APIs.

Don’t read about it—explore it.

These interactive pages are designed to give operators and leaders a real “feel” for the platform in under 2 minutes.

Operations dashboard

Fleet KPIs, alerts, mission efficiency, and “what changed?” summaries.

Telemetry → insights

See how noisy signals become explainable incidents and ranked actions.

ROI calculator

Translate reliability and utilization gains into dollars and payback.

Mixed-vendor robots. Mixed telemetry. Mixed results.

Today’s robot fleets rarely come from a single vendor. Each platform exposes different metrics, formats, and APIs — if they expose anything at all. Operations teams end up stitching together screenshots, exports, and one-off dashboards. Teams lack a dedicated observability and monitoring layer for the fleet as a whole.

Telemetry silos everywhere

Each vendor tool shows part of the picture: battery here, fault codes there, throughput in another tool. No single view of fleet-wide robot health and performance.

Control stacks are fragile

Nobody wants another dependency inside the robot’s control loop. “ROS in the cloud” adds latency and failure modes your production team doesn’t need.

Scaling is painful

As you add robots and sites, dashboards buckle, exports grow to TBs, and it becomes harder to answer basic questions like “Which robots are dragging down throughput right now?”.

Beyond simple dashboards: The AI-Native Platform.

Old school monitoring tools just show you graphs. RobotOps uses Agentic AI and Predictive Analytics to tell you what is happening, why it's happening, and how to fix it.

🔮 Predictive Analytics

Don't wait for a robot to stop. Our baseline engine tracks degradation in real-time.

Silent Degradation Detection: Catch failing motors and batteries before they fail.
Z-Score Anomaly Detection: Spot statistical outliers in any telemetry signal.
Prevent Downtime Extend Lifespan

🤖 Agentic AI & Research

Your fleet comes with an expert AI engineer built-in.

Proactive Alerts: AI monitors 24/7 and explains anomalies in plain English.
Deep Research Agent: Ask "Why did throughput drop?" and get a multi-step root cause analysis.
Smart Knowledge Base: Instant answers from your uploaded manuals and docs.

⚡️ Automation & Workflow

Turn insights into action automatically.

Workflow Rules: "IF battery < 20% AND status is IDLE THEN create charging task."
Mission Tracking: Monitor lifecycle performance across any vendor.
Maps & RTLS: Real-time location visualization.
Universal Ingestion: We support VDA 5050 (MQTT), ROS 1 & 2, and Vendor APIs out of the box. Normalize any robot into one unified view. View integrations

Built for operations, data, and robotics teams.

RobotOps gives each stakeholder the views and data they need, from day-to-day incident handling to long-term capacity and ROI planning.

Operations & site leaders

Live fleet status, at-risk robots, and throughput trends across vendors and sites, without logging into five portals or exporting CSVs.

Single pane of glass across mixed-vendor fleets.
Alerts for robots impacting SLAs or critical throughput across sites or customers.

Robotics & software teams

A normalized telemetry firehose and APIs, so you can build your own analytics, test new algorithms, and debug vendor issues with real fleet data.

Unified schema across ROS and non-ROS robots.
No need to maintain custom log exporters for every vendor.

Ops strategy & finance

Quantify the real impact of robotics investments with uptime, utilization, and ROI views that span vendors, contracts, and sites.

Compare vendors using normalized KPIs.
Support renewals, expansions, and new pilots with hard data.

A structured 4-week pilot to prove value quickly.

We know robotics teams are busy and production systems are sensitive. Our pilot is designed to be low friction: small scope, clear success criteria, and no changes to your control stack.

Pilot structure

Week 1: Connect to 1–2 robots or a test fleet via vendor APIs or topics. Validate telemetry and schema.
Week 2: Stand up dashboards for health, incidents, and throughput. Agree on alerts and views that matter.
Week 3: Tune rules and anomaly thresholds. Fold feedback from operators and engineers into the setup.
Week 4: Summarize impact and next steps: what insights we surfaced, what incidents we caught, and where it fits long-term.

What we’re proving

Rather than promising magic AI, we focus on a few concrete outcomes during the pilot:

Can we unify telemetry across your current robots safely?
Can we help your team see issues earlier or with fewer tools?
Does a fleet-wide view change how you prioritize work or investments?
We’re actively recruiting design partners for early pilots.
Curious if RobotOps makes sense for your fleet? Share a bit about your robots and sites, and we’ll respond with a tailored pilot proposal. Start a pilot conversation

RobotOps in a few straight answers.

Is RobotOps another robot orchestration platform?

No. RobotOps does not schedule jobs or control robots. It is an observability and analytics layer focused on telemetry, health, uptime, and throughput across your fleet.

Do we need to run ROS in the cloud to use RobotOps?

No. RobotOps connects to your existing robots and systems via vendor APIs, topics, and industrial protocols. We avoid putting control logic in the cloud entirely.

Does RobotOps work with non-ROS robots in production?

Yes. Most production fleets are not pure ROS. RobotOps is designed for mixed-vendor fleets, including non-ROS robots in production as well as ROS-based systems.

What does “vendor-neutral” really mean?

We expect you to use multiple robot vendors over time. RobotOps normalizes telemetry into a common schema so you can compare health and performance across vendors, sites, and contracts.