You're missing one layer
— and AI can't fix what it can't understand
Build the AI Data Layer that turns raw PLC data into AI-ready information. Open source, €8/month, no vendor lock-in.
Used by factory engineers worldwide
From raw data to AI-ready information
Sound familiar? This is why factory AI projects fail — and how to fix it
The Problem
TIC-001 = 67.3 — your historian stores this every second. Nobody knows what it means.
Your AI project fails because your data has no context — just numbers without structure
AVEVA Connect costs €40,000/year for what's essentially a JSON model
Every client is a new project — no reusable framework, no structured data layer
Your dashboards show data. Not information. Not insight. Not action.
The Solution
Build the AI Data Layer — give every data point context, structure, meaning
ISA-95 model in JSON — semantic layer built in hours, not months
Open source stack for €8/month — same result, no vendor lock-in
Reusable IDP framework — deploy at every client in less than 1 hour
Raw data → Information → Insight → Action — the complete ladder
Build the AI Data Layer your factory needs
Seven steps from raw sensor data to AI-ready information. Open source. No vendor lock-in.
⭐ Step 3: Model — The Missing Layer
Build the ISA-95 semantic model that gives every data point context. This is the layer AVEVA charges €40K/year for. You build it yourself in JSON.
Step 1 & 2: Connect + Condition
Connect your PLCs via OPC-UA, MQTT, or Modbus. Condition your data: engineering units, timestamps, quality flags.
Step 4 & 5: Store + Orchestrate
Store time-series data in MongoDB. Orchestrate automated pipelines — interval-based and event-driven. Data flows without manual intervention.
Step 6: Visualize
Build Grafana dashboards that show information, not just data. AI-ready context means your dashboards actually make sense.
Step 7: Distribute
Go live on a €8/month VPS with Docker + HTTPS. Same capability as AVEVA Connect. Full ownership, no recurring licence costs.
The Full Stack
OPC-UA · MQTT · MonsterMQ · MongoDB · Grafana · Docker. Vendor-agnostic. Reusable. Deploy at every client in under 1 hour.
These 7 steps are HOW. Solve is WHY.
Solve — raw data triggering a real decision or action — is what makes the layer worth building. Without Solve, you stay trapped in the middle: beautiful dashboards, no ROI. You can build all 7 steps perfectly and still fail if the architecture doesn't flow all the way through to a real decision on the floor.
See the AI Data Layer in action
Watch how raw PLC sensor data gets transformed into structured, AI-ready information. The same layer AVEVA charges €40,000/year for — built with open source tools in hours.
IDP Demo
Live
Calculate your savings
How much are you paying for vendor lock-in? Compare AVEVA Connect to the open source IDP stack.
Your situation
IDP Foundation — fixed cost
€97/month · all clients included
Annual savings vs AVEVA
€ 0
€ 0
€ 0
ROI
0%- Deploy at every new client in under 1 hour
- No per-client licence fees — ever
- Full ownership of the stack
- 5 clients on one IDP subscription
Ready to build the missing layer?
Download the free 7-step framework and start building your AI Data Layer today. Open source, €8/month, no vendor lock-in — and built so PLC engineers can actually learn the Python, Docker and APIs that go with it.
100+
Engineers worldwide
30
Steps to AI-ready
4.9/5
Open source