Analyze. Build. Operate. How we de-risk every engagement.
Industrial AI projects typically fail due to poor problem selection, unready data, complex integration, or lack of maintenance. Our lifecycle prevents these by prioritizing decisions before commitments, evidence before development, and operations before handoff.
The three phases at a glance
Every Cadran engagement follows the same structured path — even when the phases are adapted to the client’s starting point. Here’s what each phase delivers and the deliverables that come with it.
Analyze
Purpose
Understand the problem. Validate the solution. Generate evidence before investment.
What you bring in
A challenge, an opportunity, or a question. No certainty required — just the willingness to investigate honestly.
What you walk out with
A defined problem, a quantified opportunity, a validated approach, and a clear go / no-go decision with the numbers to back it.
Build
Purpose
Build the system. Integrate it with your environment. Deploy it to production.
What you bring in
An approved scope from Analyze — or a clear specification if you’re ready to skip directly to Build.
What you walk out with
Production-grade software, deployed and in active use. Documented, tested, and integrated with your operations.
Operate
Purpose
Keep the system performing. Improve it continuously. Adapt it as conditions change.
What you bring in
A deployed system — ours or one we’ve inherited — that needs to remain reliable, performant, and evolving.
What you walk out with
Ongoing operational excellence under SLA. Performance trending up over time. Compounding business value.
Analyze
The first phase
Most engagements start here — because the riskiest decision in any industrial AI project is the one made before the work begins. Analyze de-risks that decision by generating evidence about the problem, the data, the technical feasibility, and the business case.
What you can engage us for in Analyze
A structured assessment of a specific challenge or opportunity in your operation. Our consultants map your current state, document the data and systems landscape, identify high-impact opportunities, and quantify the business case for each. You walk out with a prioritized roadmap, ROI estimates, and a clear go / no-go recommendation. If you proceed to Build, 50% of the Discovery fee is credited toward engagements over €150k. You take no risk to find out what’s possible.
A working prototype that validates a specific AI capability against your data, your infrastructure, and your operational constraints. Not a demo — a real system that processes real data and produces measurable results. You walk out with technical validation, performance benchmarks, integration findings, and the evidence to decide whether to scale to production.
A dedicated assessment of your data readiness for AI. We audit data quality, completeness, accessibility, and governance — then identify gaps and recommend the engineering work required to close them. Critical for clients who know they want AI but aren’t sure whether their data can support it.
Build
The middle phase
This is where Engineering, AI Agents, Integration, Automation, and Innovation — our five Solution Areas — become real systems running in production. Build is the largest phase of most engagements, and the one where Cadran’s embedded team model differentiates us most clearly.
How Build engagements work:
Discovery assessment
Cadran engineers work as an extension of your team — participating in sprint planning, code reviews, and product decisions. Not a vendor delivering a spec. A partner co-developing a system.
Sprint-based delivery
Production code shipped every sprint. Working software demonstrated to your stakeholders continuously. No multi-month black box where you wait for a release and hope it works.
Production-grade quality
Automated testing pipelines. End-to-end tests with Playwright. Nightly regression runs. Code reviewed by senior engineers before merge. The systems we build are built to survive a Friday night on the production floor.
Cloud-native by default
Modern architecture (microservices, containers, infrastructure as code). Battle-tested through 3+ years of HOMAG production workloads on Azure. EU-sovereign deployment options where data residency matters.
Documented for handover
Every system we build comes with architecture documentation, operational runbooks, and the knowledge transfer required for your team to maintain it — whether that’s us, your internal engineers, or both
What we build
Engineering
Custom software, cloud-native platforms, manufacturing operations management, IoT data pipelines, and machine integration layers.
AI Agents
Production-grade AI: optimization models, predictive systems, copilots embedded in operator workflows, computer vision for quality, and agentic AI for autonomous decision support.
Integration
ERP, MES, SCADA, CMMS, and machine integration. OPC-UA, MQTT, Modbus. Connecting the systems that need to talk to each other but don’t.
Automation
Workflow automation, intelligent document processing, RPA, industrial process automation, and AI-driven business process redesign.
Innovation
R&D pilots, applied research, technology validation in operational contexts, and early-stage work that may not have existed as a category before this engagement.
Operate
The phase most consultancies skip
Go-live is not goodbye. Systems that aren’t maintained decay faster than the hardware they run on. AI models drift. Integrations break when upstream systems update. New edge cases appear in production that nobody anticipated during Build. The Operate phase exists because the value of a deployed system depends on what happens after it ships.
What Operate covers
Because we’re incentivized to. Our Operate engagements are recurring, which means our economic interest aligns with your continued success. When your system delivers more value year over year, our business does better. When it doesn’t, we have a problem to solve — and we solve it.
Managed operations
Performance monitoring, incident response, bug resolution, infrastructure management, and security maintenance. SLAs define response times, uptime commitments, and escalation paths appropriate for the criticality of the system. The bar is the same one HOMAG’s customers expect when their machines start on Monday morning.
Continuous improvement
Reviews that identify new optimization opportunities, refresh AI models, expand automation portfolios, and adapt the system to changing business conditions. Most Cadran clients automate 2–3 new processes per quarter once they’re in Operate — because each round of automation reveals the next round worth doing.
Performance monitoring
Dashboards that show how the system is performing against business outcomes — not just technical metrics. OEE trending. Waste reduction over time. Cycle-time improvements. Whatever the original business case promised, we monitor whether it’s being delivered — and adjust when it isn’t.
Not every engagement starts at Analyze
The standard path is Analyze → Build → Operate. But not every client starts there, and not every engagement needs all three phases. Here are the patterns we see most often:
Standard engagement
You have a challenge but aren’t certain about the solution, the data readiness, or the ROI. Discovery quantifies the opportunity before commitment.
Direct-to-Build
You’ve already done the analysis (internally or with another partner). The scope is clear and the data is ready. We pick up where you are.
Pure Analyze (R&D)
You want to validate a new technology, evaluate feasibility, or generate evidence for a strategic decision. No commitment to Build at the outset.
Operate handover
You have a system built by another partner (or internally) that needs ongoing maintenance, performance optimization, or continuous improvement. We inherit and improve.
Full lifecycle partnership
Strategic partnerships like HOMAG and WEINMANN. Multiple products developed and operated over years. Continuous Build cycles inside ongoing Operate engagements.
The lifecycle in action
Every case study in our portfolio demonstrates one or more phases of the lifecycle:
Common questions about how we engage
No. If you’ve already done your analysis or you have a clear specification, we can engage directly in Build. Discovery exists for clients who want evidence before commitment — not as a gate every engagement must pass through.
No. If you’ve already done your analysis or you have a clear specification, we can engage directly in Build. Discovery exists for clients who want evidence before commitment — not as a gate every engagement must pass through.
No. If you’ve already done your analysis or you have a clear specification, we can engage directly in Build. Discovery exists for clients who want evidence before commitment — not as a gate every engagement must pass through.
No. If you’ve already done your analysis or you have a clear specification, we can engage directly in Build. Discovery exists for clients who want evidence before commitment — not as a gate every engagement must pass through.
No. If you’ve already done your analysis or you have a clear specification, we can engage directly in Build. Discovery exists for clients who want evidence before commitment — not as a gate every engagement must pass through.
Most engagements start with Discovery. Yours can too.
4 weeks. €15–25k fixed fee. 50% credited toward Build engagements over €150k. A defined problem, a quantified opportunity, and a clear recommendation at the end. No risk to find out what’s possible.