IN THE FIELD GUIDE
deducedata
deducedata.solutions
Deducedata Solutions provides industrial process intelligence software that integrates AI with the physical process to optimize operations such as furnace power, reject rates, and production sequencing. Their models combine plant data, process physics, and operator knowledge without changing existing PLC logic, delivering actionable recommendations to plant operators.
THE PRODUCT, BEYOND THE PITCH
Editorially reviewed · Sources checked Sep 10, 2026
A good fit for
- Industrial plants seeking to optimize thermal processes and production sequencing with AI that respects existing control systems.
Know the limitations
- Models trained only on historical data fail when raw material or process conditions change; physics-informed models address this limitation.
What you can do
Not confirmed yet.
Features
- Models combine plant data with process physics and operator knowledge to generate recommendations.
- Energy optimization by proposing minimum furnace power to maintain output temperature.
- Predictive models identify causes of quality deviations hours in advance.
Integrations
- Integrates with SCADA (Siemens, Schneider, Wonderware, Ignition), historians (PI System, Wonderware Historian), MES, ERPs (SAP, Microsoft Dynamics, Odoo), CMMS, IoT cloud platforms (AWS, Azure, GCP), and databases via OPC-UA, Modbus, MQTT, REST, or flat exports.
Platforms & data export
- Supports on-premise, hybrid edge-cloud, and fully cloud deployments depending on client needs.
THE COST FOR YOUR TEAM
Go beyond the starting price.
Published plan prices for your team size and usage. Results update as you type. Taxes, currency conversion and unlisted add-ons are excluded, and anything the source did not state is called out rather than guessed.
Known monthly subtotal
$0.00/month
1 of 1 tools could not be priced with these inputs, so this is not the full cost.
| Tool / plan | Monthly | Per year | What this assumes |
|---|---|---|---|
| No pricing recorded yet. Check the official site, or ask the owner to add it. | |||
A practical workflow
- Models are built using existing plant data and physics, then recommendations are provided to shift supervisors who can discuss and test them before applying.
- Recommendations include variables influencing the decision, conditions triggering it, and confidence level.
- Recommendations can be written directly into control systems or displayed for human approval.
Based on the sources below. Editorial review does not imply hands-on product testing.
Alternatives to explore
Filter alternatives →Candidates based on category and primary feature. Check feature and pricing differences before switching.
Plan a switch from deducedata →What changed
Changes to the facts recorded here, not a live scan of every vendor update. Save this tool to follow updates in your account.
No changes recorded yet.