lean2automate

Products

Tools that earn their place on your floor.

Six product modules, each built around a moment that actually happens at work. Start with one as a pilot, connect it to your systems, and grow from there.

A technician in a hard hat and gloves servicing equipment after an early alert Failure risk: high · act now
AI & ML

Predictive Maintenance AI

Learns each machine's normal behaviour from its sensors, then flags the drift that comes before a failure — with the likely cause attached.

In real life The night-shift compressor starts running warm. Maintenance gets a ranked alert at 03:12 and swaps the bearing during the planned morning pause — no lost shift.
  • Anomaly detection on live sensor data
  • Risk scoring with suggested causes and parts
  • Alerts to phone, email, or your existing CMMS
An engineer with calipers working over technical drawings of a machine design Simulating shift 4 of 21
Digital twin

Digital Twin Studio

A living virtual copy of your machine, line, facility, or workflow — fed by live data, safe to experiment on, honest about consequences.

In real life Before moving three machines to speed up packing, the team runs the new layout on the twin. The simulation exposes a conveyor bottleneck — fixed on screen, for free.
  • Asset, line, facility, and process twins
  • Live data overlays and what-if scenario runs
  • Bottleneck, capacity, and downtime analysis
A team in an office discussing how their daily work actually flows Bottleneck: approvals · 5 days
Operations AI

Process Intelligence Engine

Maps how work actually flows through your teams and systems, then shows where it queues, loops, or leaks — and what fixing it is worth.

In real life Orders "take a week to process." The flow map shows five of those days are one approval inbox. One routing rule later, orders clear in two days.
  • Workflow mining and cycle-time analysis
  • Manual-task and rework detection
  • ROI-ranked automation opportunities
An inspector in safety glasses examining production quality up close Defect flagged · station 3
Quality AI

Quality Vision & Inspection

Camera-based inspection that never blinks. Defects are caught at the station where they happen, not at the customer's door.

In real life A scratched housing passes station three at 14:02. The camera flags it in milliseconds, the part is pulled, and the trend report later points to a worn fixture as the cause.
  • Image-based defect detection workflows
  • Instant reject signals to the line
  • Quality trends and root-cause signals
A busy team desk from above where routine tasks are handled by software Invoice matched · 18:41
Automation

Workflow Automation Bots

Approvals, reports, reminders, routing, and data entry handled by software — with audit trails, and a human in the loop wherever it matters.

In real life An invoice arrives by email at 18:40. By 18:41 it is extracted, matched to its PO, and queued for one-click approval — instead of sitting in an inbox for a week.
  • Email, spreadsheet, CRM, ERP, and API flows
  • Human-in-the-loop checkpoints
  • Full audit trails and operational controls
A live operations dashboard with charts and KPIs on a laptop screen All lines green · 1 warning
Dashboards

Operations Command Center

Machine health, workflow status, and business KPIs on one screen — so the morning meeting starts with the same facts for everyone.

In real life The 8 AM meeting no longer starts with "what happened yesterday?" The wall screen already shows it — including the one line that needs attention today.
  • Live dashboards with role-based views
  • Alerts, targets, and executive reporting
  • Connects to your existing data sources

Deployment models

Start with the right level of commitment.

Step 1

Discovery pilot

Validate the data, the workflow fit, and the expected payback on a small, real slice of your operation.

Step 2

Implementation sprint

Build the module, connect your systems, test with the people who will use it, and launch.

Step 3

Managed optimization

We monitor results, tune models, and expand automation as your operation evolves.

Not sure which module fits?

Describe the problem in one paragraph — the machine, the workflow, the report. We will tell you honestly what would help and what would not.

Discuss products