Applying AI in automotive engineeringwhere it delivers measurable value. We bring AI into automotive engineeringwhere it delivers measurable value.
System complexity keeps growing while development cycles keep shrinking. Four patterns stall programs again and again:
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Engineering toolchains have turned into a patchwork of isolated platforms. Requirements engineering, test orchestration, and CI/CD pipelines hang together on manual handoffs and homegrown workarounds. When AI finally arrives, it usually lands beside them as one more parallel platform. Engineers have to leave their workflow to use it, instead of getting the intelligence where their ASPICE-compliant processes already run.
Modern SDV architectures produce terabytes of CAN, Ethernet, and trace data every day. Rule-based scripts fire false positives or miss the subtle cross-domain anomalies entirely. Experienced engineers then spend weeks digging through log files for the cause of a single intermittent bug, instead of building features.
Engineering teams need modern AI tooling to move faster. Strict IT policies, IP protection, and TISAX rules effectively shut out cloud AI. By the time a secure internal environment has been negotiated, procured, and approved through every gate, the critical project phase is over. The momentum is gone.
Data scientists without a vehicle background see only numbers in the data. They do not know the vehicle architecture, they have no feel for bus latencies, and they cannot spot a failing sensor in a trace log. Automotive engineers, for their part, rarely have time to learn modern AI architectures. Initiatives stall in between, proof-of-concepts pile up, and the models never reach series production.
AI and ML roles are now the hardest positions to fill worldwide (ManpowerGroup, 2026 Talent Shortage Survey). Germany has one of the tightest talent markets of any major economy on top of that. Engineers fluent in both AI and automotive are rarer still.
AI consulting built specifically for automotive engineering: for OEMs, Tier-1 suppliers, and their engineering-service providers. We work on the bottlenecks that generic approaches cannot reach.
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We embed AI workflows into the tools your teams already use. No parallel platforms.
Your toolchain is fragmented enough already. So we build modular AI solutions that plug straight into your existing ASPICE-compliant processes. From automating requirements engineering to test orchestration inside your CI/CD pipelines, the AI works as an extension of the workflow your team already runs. Every solution is handed over with structured documentation and clear ownership boundaries. Your engineers can maintain and extend it themselves, with no standing dependency on us.
Structured rollout with clear milestones and a documented handover.
AI-driven analysis pipelines on your systems. They separate real anomalies from log noise.
Automotive validation teams are buried in terabytes of log data. We put log analytics and anomaly detection directly on your systems to separate real physical behavior from data noise. Rule-based validation combined with targeted ML analytics automates root-cause analysis, including for faults that span several domains. Interactive dashboards then let your engineers narrow in on the specific ECU or bus fault.
Root-cause analysis your validation team runs themselves, on your own log data.
On-premise, cloud, or hybrid: we build AI solutions for the deployment model that fits your reality.
Generic cloud AI often fails at the first IT compliance check. We build AI architectures around your data sovereignty requirements from the start. Whether that means an isolated on-premise setup, a hybrid architecture, or a TISAX- and GDPR-compliant private cloud, security is part of the design from day one. You get modern AI governance and flexible deployment without risking your IP or waiting quarters for IT approvals. And because a model is only useful once it knows your data, we ground it with secure retrieval running entirely on your infrastructure. Your requirements, specifications, and trace archives never leave your perimeter, and access stays governed.
Runs on your hardware. No data leaves your network.
AI agents that execute your engineering workflows end-to-end and cut manual coordination at every step.
Modern automotive development is built on interdependent tasks scattered across tools and teams: requirements reviews, specification cross-checks, test-case generation, pipeline triggers, and error management. We design task-specific AI agents that run those chains end-to-end, without a human in the loop at every step. They detect, classify, and file defects on their own. Built on open agent frameworks and wired into your existing toolchain, they get through overnight what used to cost days of back-and-forth.
The agents run the chain overnight. Your engineers review the result.
Built by engineers who shipped software-defined vehicles end-to-end at BMW and VW Group. Deployed entirely on your infrastructure.
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From ECU prototype to series production: we shipped SDV systems end-to-end for BMW and VW Group.
More than 15 years of Connected Car engineering across the BMW Group and the VW Group. From ECU prototype into series production, we owned Software Defined Vehicle systems end-to-end. We know where AI actually moves the needle in your development process — and where it does not.
Founder-led and hands-on. You work directly with the engineers who shipped these systems.
K1Logic was founded in Munich in 2026, after 15 years inside BMW and VW Group. The same bottlenecks kept stalling programs, and fixing them takes people who know both the vehicle and the AI. That depth means nothing gets lost between your engineering problem and the technical solution. We understand the hardware that generates your data: how signals originate in ECUs and bus systems, and how the vehicle actually behaves on the road. We combine that systems view with modern AI architectures so the solutions hold up in production.
Everything runs on your infrastructure. No data leaves, no lock-in. Full ownership from the start.
Strict IT policies, TISAX requirements, and GDPR turn cloud-first AI into a compliance question. We have worked inside exactly those constraints for over a decade, on BMW and VW Group infrastructure, with their security protocols and approval processes. Everything runs on your systems. No data leaves, no lock-in. Full ownership from the start.
We clarify where AI can create measurable value in your development process, in a way that is technically sound and feasible with reasonable effort.