Incolo Systems brings production-grade custom AI solutions built for your specific needs — running within your infrastructure. Inspection, maintenance, planning and monitoring, all private by design.
To make AI genuinely useful in daily plant operations — fast, private and agentic — helping manufacturers automate inspection, predict failures, plan production and monitor the floor in real time, without ever exposing process or quality data to the public cloud.
Every program follows the same disciplined path — Assess & Design → Pilot & Validate → Scale & Govern — with clear quality gates and a measurable business case at each stage.
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Pharma · Automotive · Discrete
Edge-deployed computer vision trained on line-specific defect libraries — surface, dimensional, print and assembly-completeness — with sub-second inference and a human-in-the-loop review queue.
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Discrete & Batch · Pre-Dispatch QC
Vision-based AI counts each piece as it is placed and checks the final count against target before a container is sealed — with an auditable photo record and a logged override for exceptions.
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Rotating Equipment · Utilities · Critical Assets
Vibration, temperature, current and pressure data streamed to on-premise ML models trained on asset-specific failure signatures — with remaining-useful-life alerts and CMMS/EAM work-order integration.
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Multi-Product · Batch & Discrete
Agentic re-planning that proposes revised schedules when an order changes — with a plain-language interface so planners can request a build plan or dispatch report, checked against the BOM and live stock before anything is committed.
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Multi-Line Visibility · OEE
Real-time OEE, throughput and quality dashboards built on your existing SCADA/MES data, deployed on-premise — with an AI copilot that flags anomalies as they emerge and Andon-style escalation.
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Automotive Thermal · Heat-Exchangers
ML models trained on furnace zone temperatures, belt speed and atmosphere against downstream leak-test results — recommending parameter adjustments to hold the optimal thermal profile as load and product mix vary.
Each pillar is adapted for the realities of a live production environment — deployed on edge gateways, line-side compute, or private plant servers.
Computer-vision inspection, predictive maintenance and monitoring engineered for the shop floor — integrated with your existing PLCs, SCADA, and MES/ERP systems.
A hands-on consulting practice that helps plant and IT/OT leadership design and deploy secure AI across production, quality and maintenance — from feasibility study to full rollout.
Convert manual, paper-based or spreadsheet-driven shop-floor processes into AI-assisted operations — with human-in-the-loop governance, audit trails and measurable throughput gains.
On-premise and edge inference means production, quality and process data never leave the plant. No server-side logging of proprietary parameters, no training on your production data, no third-party broker in the pipeline.
Most industrial-AI vendors are staffed by researchers who have never run production systems under enterprise SLAs. Our founders have spent decades doing exactly that — and mean it when they say a system is production-ready.
We don't leave leadership with a roadmap and a retainer. Our three-phase model gets a working pilot running on your line within weeks, with quality gates and a measurable business case at every step.
“Security, privacy, and model accountability are built into architecture decisions from day one. We call this Trust by Design.”— Incolo Systems, Core Principles
A world where AI amplifies human potential on the factory floor without compromising data sovereignty — where every plant, from a pharmaceutical clean room to an automotive brazing line, can deploy intelligent systems it owns entirely.
To deliver on-premise, edge-deployed intelligence that is fast, private and agentic — helping manufacturers automate inspection, predict failures, plan production and monitor the shop floor in real time.
We engineer privacy into the foundation, not as a feature. On-premise inference is the standard for production data — not a compromise.
In regulated plants, trust is earned through qualification protocols, audit trails and traceability — before a pilot touches live production.
We prioritize working pilots on the actual line, with measurable OEE, quality and downtime impact — over strategy decks.
We embed with plant IT/OT and quality teams, transfer capability and build long-term delivery discipline — not dependency.
AI that only runs in a data center excludes the plant floor. We engineer for edge hardware because that is where production happens.
Model accountability, cybersecurity and change-control governance are built into every deployment from day one — audit-ready by design.
Engagements typically begin with a scoping call and a short plant walk-through — no obligation, just a focused conversation about your priorities and whether we're the right fit.
