After-sales · Variant management · Product configuration · Custom software
First understand. Then prove. Then we build your software.
Custom enterprise software that moves your business forward – we prove on your real data that it works before you invest. No surprises: you decide again after every phase.
Proven in the variant-exact repair scope: the right spare part, the right operations — in milliseconds.
Our approach
Four phases to a production system.
IT projects rarely fail because of the technology. They fail because of the approach. Each of our four phases eliminates one risk before it costs money: results instead of promises.
Understand
Which process is worth casting into software?
Lean analysis with your subject-matter experts: first we examine which steps can be dropped — then which can be solved algorithmically. We don't cast waste into software. Typically 1–2 weeks.
Result: target process + automation leversProve
Does it really work — with your data?
A feasibility sprint on your real data, at real volumes — proving the critical assumption before serious budget is committed.
Result: a solid proof of feasibilityDeliver
How does the solution reach production reliably?
Agile implementation, steered with our published Six-Practice method on our own platform: your management knows where the project stands at all times — no whitewashed traffic lights.
Result: a production system without surprisesOperate
How does it stay stable and economical?
Operated by the team that built it: proactive monitoring, growing AI automation, falling operating costs.
Result: predictable operating costsShow the detail on all four phases
1 · Understand
Your processes have long been digital. They just run in Excel. We capture them in workshops at the place where the value is created; for the steps that remain, we determine the volume baseline for automation. Where more depth pays off — in branched or multi-site processes, for example — we extend the analysis with classic lean methods such as value stream mapping and plan more time together. Lean is not a brochure word here: Complevo's lean competence comes from our own subsidiary Makeo, which runs lean consulting as a business in its own right.
The same methodology we use to streamline production processes protects your software project from bad investments. You also receive the cut of the success-critical work packages — the blueprint for the feasibility sprint.
2 · Prove
The core question is this: can the decisive task be solved algorithmically at all? We test the success-critical work packages from phase 1 — at your volumes, because with thousands or millions of possible variants a test on toy data proves nothing. We work in short iteration cycles with your subject-matter contact: your feedback goes straight into the next round. A no is a result too: you have avoided an expensive wrong decision, at the price of one sprint.
3 · Deliver
We deliver continuously, feature by feature: what is finished goes live instead of waiting for the end of a planning cycle. Review, testing and responsibility for the result stay with the team. Planning is rolling — only what is next for execution becomes binding in detail. Eliminating waste applies to our project management, too. The platform is called Makeo: a regular communication cadence keeps every level — from the team to the steering committee — on the same page, while status reporting and problem solving stay deliberately separate. Deviations are control signals: visible while you can still steer, decided where the authority sits. And if your goals change, we realign the project — the method is built for moving targets, developed in one of the largest infrastructure projects in the world.
4 · Operate
No break in knowledge at handover: we detect anomalies before they turn into incidents. And operation by us is an option, not a condition — you can move to in-house operation at any time, with a documented handover.
Process first, automation second.
Complevo combines lean process analysis with AI-assisted software development. The order is the point: first it is settled which process remains at all — then we apply AI, in the specification, in the rule set, in test automation and in operations. Lean and AI are not competing approaches; they are a sequence.
The problem — and the solution
Every machine is one of a kind.
One call, everything in it: spare parts, operations, labour times — variant-exact, in milliseconds.
The type plate does not lead you to the configuration actually built. The variant-exact repair scope resolves a serial number or VIN against the as-built state — automatically, completely, via API into your systems. For planned maintenance just as much as for the unplanned repair.
Identifying parts is manual work
What really fits is worked out through portals, callbacks and experience — or through the second order.
Instructions only roughly apply
Modular guides apply “except with equipment X” — what applies to this product remains a matter of interpretation.
The repair does not end with the last bolt
Software versions, coding and mandatory calibrations are scattered across tester, guide and catalogue.
Resolved for every product variant ever built — for fleets in the field across decades.
And how does that work with our data? Show the four steps
- Conversion: we convert your historically grown bills of material into a rule-based super BOM — a structure that maps every variant ever built in a single model.
- Migration: every product variant built — per serial number or VIN — is resolved as a product configuration against that structure.
- Calculation: from this the variant-exact repair scopes are derived: spare parts, operations and labour times per exact variant.
- Delivery: retrieved through a high-performance API, straight into your systems — the same interface also serves access obligations, in so far as they apply to your product group.
Industries
One logic, three fields of application.
Insurers
The target scope as an independent reference calculation in technical claims — verifiable position by position.
Automotive
After-sales for manufacturers and importers: variant-exact parts, operations and service information — since 2011.
Long-life products in the field
Construction machinery, agricultural machinery, lifts, wind power, rail, heating and air conditioning: variant-rich products with decades of service life and recurring maintenance cycles.
Discuss your route there →The independent target calculation in technical claims.
Check every repair invoice submitted against the variant-exact target scope — automatically and independently of the manufacturer. Including the bulk that no review capacity looks at today.
The proof
In use at leading manufacturers since 2011.
Our flagship project: in production worldwide for three years, with millisecond response times.
“Throughout the entire engagement I experienced the work with the Complevo team as highly collaborative, solution-oriented and pragmatic. The approach Complevo established, together with its in-house toolset, contributed substantially to creating transparency about requirements, priorities, releases and implementation progress. Many challenges could only be solved successfully because the teams did not stop at analysis but worked consistently towards workable solutions.”
Two more voices from customer projects
“Where efficiency and results are right, onshore projects can certainly be cost-effective. Our experience in projects with Complevo has shown this.”
“For the development of our intelligent charging infrastructure solution they adapted to our requirements flexibly and with great commitment. The result: a future-proof product — developed in an agile way, delivered reliably.”
The Six-Practice method is scientifically published (IGLC): iglc.net/Papers/Details/2474
Why now
The installed fleet is ageing — after-sales carries the load.
When new sales fluctuate, vehicles and machines stay in service longer. The installed base in the field then decides workshop utilisation and earnings.
Automation only takes effect at scale.
Individual AI projects do not change a cost structure. Noticeable effects appear only once a relevant share of a process runs automatically.
Data access is opening up — we turn that into an advantage.
The Data Act opens up the usage data of connected products. Repair data is not covered — whoever provides it in structured form regardless occupies the channel into the field themselves.
Experience retires — data stays.
The experts who know today which variant needs what will retire over the coming years. In after-sales, the skills shortage means above all one thing: loss of knowledge.
Why this counts right now — the four developments in detail
Ageing installed fleet
Maintenance recurs predictably and repairs come on top: parts identification and service information become more important, not less. That is exactly where the variant-exact repair scope comes in.
Automation at scale
That is precisely what our approach is designed for: phase 1 determines the automation levers along the entire process, phase 2 proves them on your real data. Specification, rule-set implementation and test automation run AI-assisted here: smaller senior teams, shorter cycles, transparent costs.
EU Data Act
The Data Act (Regulation (EU) 2023/2854) governs the data that arises when connected products are used — not bills of material, configuration rules, repair instructions or labour times. The Repair Directive (EU) 2024/1799 likewise covers consumer goods, not agricultural, construction or special-purpose vehicles. Enforceable access pressure today exists mainly sector by sector: in type-approval law for motor vehicles and tractors, and in the right-to-repair legislation of individual US states. The direction is set; the obligation for your product group may not be — so the question is not compliance, but who occupies the data channel into the field.
Loss of knowledge
The variant-exact repair scope codifies that knowledge in rules and data — available to every team, in every system, regardless of who happens to be planning the repair.
Sources for the four figures
Kraftfahrt-Bundesamt (German Federal Motor Transport Authority), vehicle population as at 1 Jan 2026 (average age 10.9 years) · German Economic Institute (IW), “Künstliche Intelligenz als Wettbewerbsfaktor”, 2025 (6 % of companies use AI in several business areas) · Regulation (EU) 2023/2854 (Data Act), Article 3: access “by design” for connected products placed on the market after 12 Sep 2026 — covering usage-generated product data, not bill-of-material and service data · Directive (EU) 2024/1799 (Repair Directive), scope: consumer goods · Federal Statistical Office of Germany, press release of 23 Jun 2026 (13.3 million people in the labour force will reach retirement age within the next 15 years).
Roadmap: the three expansion stages
From the spare part to the completed repair.
What is in production today is the core. Each further stage makes one more step of the repair process variant-exact.
Resolved
Spare parts, operations with labour times and consumables — variant-exact for every product variant ever built.
In productionPlannable
Tools, test equipment and qualifications per operation — scheduling checks up front whether everything fits together.
PlannedExecutable
The variant-filtered instruction: only the steps, torques and safety notes for this exact product.
PlannedCompletable
Target software versions, coding scopes and mandatory calibrations — the digital sign-off is part of the repair scope.
PlannedEvery expansion stage is created with pioneer customers — and, as with everything here: proven in a feasibility sprint first, then built.
Frequently asked
Answered briefly.
What is a variant-exact repair scope?
Which industries is the solution suitable for?
How fast is the calculation?
Our bills of material have grown historically — can we still start?
What does the EU Data Act mean for our after-sales?
How does a project with Complevo work?
Let's get started.
Start small and measure on a real job: we begin with the “Understand” and “Prove” phases — the decision is made on the basis of your numbers, not our slides.
Book a meetingPrefer to write or call? kontakt@complevo.de · +49 30 959 99 75 75
Your contact: Stefan Pillasch, Managing Director — LinkedIn
COMPLEVO GmbH · Franklinstraße 14 · 10587 Berlin · Germany