INDUSTRIAL AI PARTNER · DATA & OPERATIONS
THE INDUSTRIAL DATA PROBLEM
Industrial companies generate more operational data than ever — and act on less of it than they should.
The bottleneck isn't sensors, connectivity, or storage. It's the missing layer between operational data and operational decisions — the models, systems, and workflows that translate what your machines tell you into what your teams do next.
OT and IT systems still live in silos. Models built in the lab never reach the floor. Pilots succeed and never scale. The gap between data and decision costs industrial companies millions in preventable downtime, waste, and missed optimization.
QuasarZero exists to close that gap, end-to-end.
AT A GLANCE
YEARS · SENIOR TEAM
Cumulative senior experience across energy, automotive, aerospace and logistics.
ML SYSTEMS IN PRODUCTION
Industrial deployments — from predictive maintenance to process optimization and supply chain AI.
CONTINENTS · ONE TEAM
A core team in Paris, with delivery partners across Africa, Europe and North America.
PRACTICES · ONE ENGAGEMENT
Industrial DataOps, AI for Operations, and Platform Engineering — delivered as one integrated team.
OUR PRACTICES
01 / PRACTICE
We connect OT and IT data into a unified, contextualized foundation. Sensor streams, historian data, ERP systems — structured for AI, not just storage. The right data layer is what separates a pilot from a platform.
02 / PRACTICE
Predictive maintenance, process optimization, anomaly detection, demand forecasting. Models built for industrial constraints — real-time, reliable, explainable — and deployed where operators actually work.
03 / PRACTICE
The infrastructure that makes AI stick: data pipelines, MLOps, operational dashboards and decision tools. Built to last beyond the engagement and scale to the next facility.
OUR PROCESS
01
We audit your operational data landscape — OT systems, historians, ERP, existing models — and identify where the highest-value AI use cases are. You get a clear, ranked roadmap before any build begins.
2–3 weeks02
Our team embeds with yours to develop, test, and deploy AI systems built for your industrial environment — not a lab prototype. Every model is validated against real operational constraints.
6–12 weeks03
A working model at one site is a start. We stay through the scale-out — monitoring, retraining, knowledge transfer — until your team can extend the system to the next facility independently.
OngoingUSE CASES
Designed and deployed a large-scale ML platform for a major oil & gas operator — covering predictive maintenance, anomaly detection, and equipment failure forecasting across production sites. Models were integrated directly into existing SCADA systems and monitored continuously in production.
Built a data-driven pricing engine combining market elasticity models, competitor price signals, and demand forecasting. The system replaced manual pricing committees with a model-backed recommendation layer, reviewed and validated by commercial teams across three markets.
Developed a fleet optimization system combining route planning algorithms, demand prediction, and real-time vehicle telemetry. The solution reduced empty mileage, improved on-time delivery rates, and enabled dynamic dispatching that adapts daily to operational conditions.
CLIENT FEEDBACK
"We had sensors everywhere and no real intelligence on top of them. QuasarZero came in, understood our OT constraints immediately, and delivered a working predictive maintenance model in staging within six weeks. They didn't simplify the problem — they solved it."
"Most AI vendors pitch a platform and leave you to figure out the integration. QuasarZero embedded with our engineering team, worked inside our systems, and built something our operators actually use every day. That's a different kind of engagement."
FREQUENTLY ASKED
SCADA and historians capture data. We build the AI layer on top — the models, pipelines, and decision tools that turn that data into operational actions. Most industrial data teams are strong at maintaining existing infrastructure; we specialize in building what doesn't exist yet, without disrupting what does.
Yes — and this is where most AI vendors struggle. We've worked with OSIsoft PI, SCADA systems, PLCs, and heterogeneous industrial data sources. We don't require a modern data stack to get started. We meet your infrastructure where it is and build from there.
A diagnostic engagement typically runs 2–3 weeks and gives you a clear, ranked roadmap. From there, a focused AI build — one use case, one site — can reach production in 6–12 weeks depending on data readiness. We prioritize quick, measurable wins over multi-year transformation programs.
Platform vendors sell software licenses and expect you to build on top. We deliver working systems — embedded in your environment, built for your constraints, transferred to your team. We're tool-agnostic: if a vendor platform is the right fit, we'll say so and build on it. If it isn't, we build around it.
Yes. Our team operates across Africa, Europe, and North America. We're particularly experienced with the infrastructure and connectivity constraints that come with industrial operations in African markets — and we design AI systems that are robust to those conditions, not just optimized for ideal environments.
START HERE
A 30-minute call is enough to know where the highest-value AI opportunity is in your operations — and whether we're the right team to build it.