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Get a custom proposalAI for industry: understand before optimizing.
Deduce Data Solutions is a scientific team specialized in Industrial Process Intelligence (IPI): we apply artificial intelligence and advanced analytics to help industrial plants understand what really drives their processes before optimizing them. We work under one principle: understand before optimizing. Instead of deploying generic software, we start by modeling the physics and the data of a real process, identify the root cause behind energy waste, instability or quality loss, and only then intervene. This lets us deliver measurable improvement on existing infrastructure, without heavy new investment. Our work is organized around three pillars: Energy and thermal efficiency (reducing consumption and thermal losses in energy-intensive processes); Process stability and quality (cutting variability, defects and downtime); and Industrial decision intelligence (turning plant data such as SCADA, MES, ERP and sensor readings into decisions operators and managers can act on). A typical engagement begins with a short, focused diagnostic: we measure the current baseline of one concrete process and prove, with data, how much can be improved or saved. Every engagement is run by scientists and data engineers. We serve energy-intensive and manufacturing industries that need to trust the result before contracting a data project.
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Min project size
$10,000+
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Hourly rate
Undisclosed
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Employees
10 - 49
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Year founded
Founded 2020
- AI Development
- 40%
- AI Consulting
- 30%
No Focus Areas have been added yet…
- Manufacturing
- 50%
- Automotive
- 25%
- Energy & natural resources
- 25%
- Enterprise (>$1B)
- 80%
- Midmarket ($10M - $1B)
- 20%
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Our Story
Deduce Data Solutions is a scientific team specialized in Industrial Process Intelligence. Founded in 2020, we bring academic rigor to industry, working with researchers from IFCA (University of Cantabria) and Ecole des Mines (Paris). A stable, highly qualified team, we model the physics and data of real processes to help plants understand before optimizing, because automating a process without understanding it only scales its errors.
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