By Gilad Cohen, CEO at Imubit
Verdantix recently released its Green Quadrant: Industrial AI Analytics Software (2025), which benchmarks providers of industrial AI analytics software. We appreciate the report's recognition of Imubit's contribution to industrial performance, and we welcome the discussion it starts about where the industry is heading.
What Verdantix got right
The report highlights themes that matter to us.
- Scaling beyond pilots. Industrial companies want value they can measure and repeat across units and sites. That has been our aim from the start.
- Domain expertise. AI has to carry the knowledge of the process it runs on. Our work with Oxbow on petroleum coke calcining is one example, where closed-loop control raised yield and cut natural gas use while holding product specifications.
- Trust and explainability. Predictions that plant experts can explain are key to adoption. We have always built transparency into our models, so plant experts can understand and validate what the AI does before they rely on it.
Beyond the quadrant
Imubit does not fit neatly into an analytics category. The Verdantix framework gives a useful snapshot of the market, and like any framework it weights some criteria, analytics breadth in particular, above others. Imubit's difference lies in execution, with control that acts on the process and stays tied to the plant's operating strategy.
Closed-loop control, from insight to outcome
Many analytics tools stop at a dashboard, a recommendation or a one-off optimization study. Imubit takes critical decisions to closed loop. Deep Learning Process Control® (DLPC®) learns a nonlinear dynamic model of each unit from its own history, guided by first principles. A controller trained by reinforcement learning across millions of simulations then writes setpoints to the existing APC or DCS minute by minute, around the clock, inside limits set by plant engineers. Because the controller keeps adjusting as conditions change, the margin gains are sustained. Whether the AI acts on its predictions in production is an axis the quadrant does not fully capture.
Execution tied to the operating strategy
Imubit is not an analytics tool in the usual sense. Plant performance depends on operating strategies that planning, operations, process control and economics teams carry out in different systems, on different KPIs and at different rhythms. Even when everyone does their job well, the plant behaves inconsistently, and leaders feel it as a gap between the plan and the plant. More analytics does not close that gap. Imubit works on it with Map, Model, Control:
- Map: trace plan-to-plant gaps to the recurring decisions behind them.
- Model: model the causality with learning process models.
- Control: take the critical decisions to autonomous execution, inside limits set by plant engineers, on top of APC and DCS.
That ties the AI directly to the plant's business objectives.
Looking ahead
We appreciate Verdantix's independent perspective and the attention it brings to industrial AI. Reports like this help customers ask sharper questions and push vendors to keep raising the bar.
Our aim is unchanged. We help the process industries improve profitability and sustainability with AI. Imubit has over 100 closed-loop controllers deployed worldwide, the largest install base in the industry, delivering measurable margin improvement and energy efficiency gains across refining, chemicals and polymers, cement, and mining and minerals. The measure that matters is whether our customers' results hold over time.
