Manufacturing software development
that survives the shop floor.
MES, SCADA integrations, digital twins, predictive maintenance, and the shop-floor-to-top-floor data fabric. Built for plants that run 24/7 where a bad release stops the line.
Downtime is denominated in money per minute.
Manufacturing software runs on a different clock. A 30-second API outage is a tolerated incident in SaaS and a stopped production line in a plant. The engineering discipline has to treat the real world (PLCs, sensors, OT networks, union rules, maintenance windows) as a first-class part of the architecture.
We've delivered MES rollouts, OEE platforms, predictive-maintenance pipelines, and digital twins for discrete and process manufacturers. Every project has an ops playbook signed off by plant engineering before go-live, because the people paged at 3am aren't our engineers. They're the night shift.
Things we've shipped
in manufacturing.
A sample of what we've built in this sector. We omit client names by default and share them under NDA when you want to dig into a specific engagement.
Manufacturing · North AmericaAetherData: enterprise data fabric.
Business teams self-serve integrations and dashboards that previously needed engineering.
React · Django · Django REST Framework · PostgreSQL
Manufacturing · North AmericaProcuraForge: AI procurement automation.
A single source of truth for POs, commitments and supplier conversations.
React · Django REST Framework · PostgreSQL
ManufacturingPixelkit: Operations platform.
A web and mobile app for operations, built with React Native and Django. Core workflows, records and reporting run through one validated data model that non-technical staff operate day to day.
React Native · Django
ManufacturingGeopulse: Operations platform.
A web app for operations, built with React, Flask, GCP and Python. Core workflows, records and reporting run through one validated data model that non-technical staff operate day to day.
React · Flask · GCP · Python
ManufacturingFactorlytics: Custom application.
A web app for a focused workflow, built with React, Django, AWS, Python, Jenkins and Kafka. The core workflow is modelled properly once, so data stays consistent and the product is straightforward to extend.
React · Django · AWS · Python
ManufacturingSalesight: Operations platform.
A web app for operations, built with Angular, amCharts and DevExtreme. Core workflows, records and reporting run through one validated data model that non-technical staff operate day to day.
Angular · amCharts · DevExtreme
The problems manufacturing teams bring to us.
MES modernisation and rollout.
Replacing paper, Excel, and legacy MES with a modern platform. Multi-plant, multi-line, with governance the corporate team can trust and flexibility the plant manager needs.
OT/IT data fabric and historians.
Sensor ingestion, protocol bridging (OPC UA, Modbus, MQTT), time-series storage, and the analytics surfaces that turn the data into decisions, not just dashboards.
Predictive and prescriptive maintenance.
Vibration, thermal, and process-variable models with alerting that the maintenance team actually acts on. Measured in downtime hours avoided, not model accuracy.
Digital twins and simulation.
Plant, line, and process twins for throughput planning, what-if analysis, and operator training. Built on Omniverse or bespoke stacks depending on the fidelity required.
What we've built for manufacturing, more than once.
MES and shop-floor apps.
Work-order execution, quality capture, traceability, production scheduling. Designed around the tablet in a glove, not the desk in an office.
OEE and performance platforms.
Availability, performance, quality, measured honestly. With the plant-manager cockpits and corporate rollups the leadership chain actually uses.
Integration middleware.
ERP-to-MES-to-PLC glue. SAP, Oracle, Dynamics on one side, Siemens, Rockwell, Schneider on the other. With the data model discipline to make the glue outlive the vendors.
Supply-chain and planning tools.
Demand forecasting, S&OP, constraint-based scheduling. Models the planners trust because they can interrogate the assumptions.
Three ways to work with us
in manufacturing.
Pick the shape that matches the commitment. Each model ships the same engineering standard. The difference is commercial and operating fit.
Dedicated teams
A cross-functional pod owning a workstream end-to-end.
Offshore development centre
A fully-managed engineering arm built in-region.
Staff augmentation
Senior engineers plugged straight into your team.
AI in manufacturing & industrial.
Assistants that answer engineers' questions from manuals and maintenance history, visual quality checks, and procurement workflows that draft, compare and route supplier documents.
Explore AI developmentOur journey with them has been nothing short of exemplary, far exceeding our initial expectations.
Answers for manufacturing & industrial buyers.
Still wondering something? Ask an engineer
Yes. Manufacturing execution, OEE and performance monitoring, quality and traceability, predictive-maintenance pipelines, and digital twins. Plant software has to survive an environment where the network is imperfect and a stopped line costs money every minute, so resilience beats elegance in every trade-off.
Yes, through the standard industrial interfaces such as OPC UA and MQTT, and through historians where they are already in place. The operational-technology boundary is respected: analytics and reporting workloads read from a clearly defined interface rather than reaching into control systems directly.
By making the plant able to keep running without us. Edge buffering so data survives a connectivity loss, staged rollouts with a tested rollback, and an ops playbook signed off by plant engineering before go-live — because the people paged at three in the morning are the night shift, not our engineers.
14 published case studies in this sector, with more work we can only discuss under NDA. We staff engagements with engineers and delivery leads who've shipped in Manufacturing & industrial before. The domain literacy is learned, not looked up.
We work to ISA-95, traceability law, safety standards per sector, and export-control rules. Every engagement starts with a compliance review so there's no ambiguity about which regimes apply. Every release ships with the audit trail your compliance team needs.
Yes. Most of our engagements connect to MES, SCADA, historians, OPC UA, PLCs (Siemens, Rockwell, Schneider), and ERPs (SAP, Oracle). We adopt your existing integration patterns rather than imposing a new one, and we write data contracts before we write integration code.
We design for 24/7 shop-floor deployments, plant-safe releases, and OT/IT segmentation from day one, not as a post-launch afterthought. Performance budgets, SLO commitments, and ops runbooks are written into the statement of work.
Either. Manufacturing & industrial engagements run under all three of our engagement models. Dedicated teams, offshore development centres, or embedded staff augmentation. We pick the shape that matches your operating model, not our preferred one.
Discovery typically runs two to four weeks from first call to signed statement of work. First-engineer start dates follow within another week or two. The exact timeline depends on the shape and on the clearance or onboarding your environment requires.
Let's build from here.
Thirty minutes with an engineer who builds. No sales, no drip campaign. If we're the wrong fit we'll tell you and point you somewhere better.