Decisyon

What the product is

Decisyon is an enterprise platform for manufacturers that joins 3 things on one platform, which its home page lists as "AI Workforce + Manufacturing Applications + Industrial Data." It is a low-code system in a narrow sense. The company's own guide to low-code manufacturing apps says Decisyon App Composer uses agentic AI to interpret natural language requirements and generate application structures that users can then refine and extend. The audience is plant managers, supervisors, quality leads and the central IT teams who govern many plants. The pages do not state where the company is based.

This is a vertical platform, so it fits best where the thing you want to build is a manufacturing execution tool, a daily management routine or a maintenance application, not a customer portal or a marketing site.

What you build and how

The company frames the product as closing "the gap between knowing and doing across every role in the operation." Manufacturers already have data, alerts, dashboards and decisions, it says, and Decisyon turns them into accountable action. The home page assigns each role a job. The plant manager connects operational risks and decisions to measurable plant performance. The operator sees problems early and gets context and a recommended response. The supervisor turns decisions into ownership, escalation and follow-through. The quality lead detects deviations earlier and drives corrective action. The continuous improvement lead verifies that improvements hold and scales proven practices across lines and plants. The site says Decisyon "works with your existing technology stack."

Packaged applications. 5 applications sit on the platform. LOOP handles connected daily management for tier meetings, actions and accountability across every shift. Agentic MES is described as AI-assisted manufacturing execution with orders, quality, traceability and OEE. Predictive Maintenance aims to predict failures before they stop the line and prescribe the next action. Manufacturing Control Tower gives one live picture of every plant, from line coordinator to plant director. Asset Performance Management shows each critical asset's condition, cost, risk and performance. The company's advice is to start with the operational challenge that creates the most value, prove the results, then expand across lines, plants and applications on the same platform.

The AI workforce. Instead of handing people another AI tool, the company says it puts specialized agents inside the operational workflow to monitor, search, coordinate, document and follow up. The home page lists 11 of them. Meeting Sense captures decisions, actions and owners from operational meetings, and Meeting Insight searches past discussions and outcomes across the enterprise. Fix Finder surfaces the corrective action applied to a similar issue. Deep Find runs natural-language search across SOPs, manuals and operational records. Process Conformance checks operations against your own procedures and flags what it finds. Issue Coach checks a fault description while the operator writes it (who, what, where, when, how) and asks for what is missing. Task Pilot opens a task or a maintenance call straight from the stop page, carrying the stop with it. Shift Pilot writes the shift handover, covering stops, losses and open actions, for the operator to correct. Asset Health Agent watches condition, operating behavior, anomalies and emerging risk. Reliability and Root Cause Agent predicts degradation and sizes the operational and business consequences. Prescriptive Maintenance Agent recommends the next best action from asset history, engineering knowledge, risk, cost and operating constraints.

Building your own. The company's guide to low-code manufacturing app development describes the builder side. Visual, drag-and-drop tools and AI assistance let engineers, operations managers and domain experts create dashboards, workflow tools and monitoring systems. The guide says AI helps in two ways, by interpreting natural language descriptions to generate application structures, data connections and workflow logic, and by embedding agents that monitor operations and recommend actions. It describes moving from idea to working prototype in hours. The guide names OEE dashboards, downtime triage, quality escalation workflows and predictive maintenance as typical applications of this kind.

Governance across plants. The guide describes a federated model where each plant builds and modifies its own applications within enterprise governance standards. Central IT defines data models, security policies and component libraries that local teams use as building blocks. It says Decisyon has demonstrated this at scale, "supporting deployments across hundreds of plants and tens of thousands of users from a single architecture."

The evidence from the pages

Scale and customers. The home page shows "218 plants," "100K+ Users" and "4 hrs To bring a new plant online." Under a use case about preserving operational knowledge it cites "110K+ registered users" at Schneider Electric, and under standardizing across plants it cites 218 plants connected at Schneider Electric. A plant general manager at Schneider Electric's Carros site is quoted saying "Used every day by 100% of our employees. It improved our site performance by 4 to 5%." The page also describes Italfarmaco improving efficiency with the Agentic MES application, with under 3 months from kickoff to production deployment, and Abafoods (Ecotone) bringing production, quality and traceability into one live MES with 980+ SKUs in the traceability scope. A line on ADEO cites "50%+ less data entry & audit cycle time." A multinational food and beverage manufacturer is credited with "$3.4M added value per plant in year one."

Claimed results. The home page states "3-5% Higher OEE," "20-30% Less Downtime," "50%+ Faster Resolution" and "Up to 300% Modeled ROI." The company's guide adds that customers running multi-site programs "have reported average ROI of 250%." These are the company's figures, and the 300% figure is labeled as modeled.

Pricing and trial. The navigation has a Pricing entry, but the pages held show no prices, plan names or usage limits. What the home page does offer is a pilot, "Prove Measurable Value in 14 Days," described as one plant, one use case, real data and clear success criteria. A pilot call takes 30 minutes, and an ROI report comes from a 2-minute form. No free plan is mentioned.

Where it is used. The industry navigation lists Packaged Goods, Food & Beverage, Industrials and Pharmaceutical. The home page says hundreds of plants are live on 6 continents.

What the pages do not say. They give no integration list, no compliance certifications, no hosting options and no code-export or self-hosting details, so those need to be asked about before a security review.

Who it suits and who it does not

Decisyon suits a manufacturer with several sites that wants one governed system for daily management, MES, maintenance and meeting follow-up, and an IT team that would rather supply data models and components than build every screen. The pilot format also lets an operations lead test one plant and one use case before committing wider.

It does not suit a founder or freelancer who wants a general-purpose app or site builder, a services business, or a team outside manufacturing. A single small plant may find the multi-site governance and 5-application structure more than it needs. And because the company publishes no prices in the pages held, a buyer should expect to go through a sales conversation and the pilot to get a figure.