Applying AI in automotive engineeringwhere it delivers measurable value. We bring AI into automotive engineeringwhere it delivers measurable value.
As system complexity explodes and development cycles shrink, four failure patterns keep stalling programs across the industry:
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Engineering toolchains have become a fragmented patchwork of isolated platforms. Requirements engineering, test orchestration, and CI/CD pipelines are held together by manual handoffs and custom workarounds. When AI is finally introduced, it's usually bolted on as yet another parallel platform — forcing engineers to break their workflow instead of embedding intelligence directly into their existing ASPICE-compliant processes.
Modern SDV architectures generate terabytes of CAN, Ethernet, and trace data daily. Rule-based scripts trigger false positives or miss subtle, cross-domain anomalies entirely. Instead of building new features, skilled engineers spend weeks hunting through endless log files for the root cause of a single intermittent bug.
Engineering teams need advanced AI tools to accelerate development, but strict IT policies, IP protection, and TISAX constraints rule out modern cloud-based AI. By the time a secure, compliant internal environment is negotiated, procured, and approved across stakeholders, the critical project phase is already over and the momentum is gone.
Generic data scientists treat data as abstract numbers — they don't know vehicle architecture, bus latencies, or how a physical sensor glitch shows up in a trace log. Automotive engineers, in turn, rarely have time to master modern AI architectures. The result: stalled initiatives, endless proof-of-concepts, and models that never reach series production.
AI and ML have become the hardest roles to fill worldwide (ManpowerGroup, 2026 Talent Shortage Survey) — and in Germany, with some of the highest talent shortages of any major economy, 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. Focused on the bottlenecks that generic approaches can't reach.
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We embed AI workflows into the tools your teams already use. No parallel platforms.
We don't add yet another isolated platform to an already fragmented toolchain. Instead, we build modular AI solutions that plug directly into your existing ASPICE-compliant processes. From automating requirements engineering to test orchestration within your CI/CD pipelines, the AI acts as an integrated extension of your team's current workflow. Every solution is handed over with structured documentation and clear ownership boundaries — so your engineers can maintain and extend it independently, with no recurring dependency on us.
Predictable timelines. Structured rollout with clear milestones.
AI-driven analysis pipelines on your systems to cut through log noise and isolate true anomalies.
Automotive validation teams are buried in terabytes of log data. We deploy log analytics and anomaly detection directly on your systems to separate real physical behavior from data noise. By combining rule-based validation with targeted ML analytics, we automate root-cause analysis for complex, system-spanning errors — with interactive dashboards built to help your engineers locate the exact ECU or bus fault in hours rather than weeks.
Designed to cut validation effort and surface issues in hours, not weeks.
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 built in by design — so 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 when it knows your data, we ground it with secure retrieval that runs entirely on your infrastructure — your requirements, specifications, and trace archives stay inside your perimeter, with governed access.
Built to deploy in weeks, not quarters — without IT delays or compliance risk.
AI agents that execute your engineering workflows end-to-end — reducing manual coordination at every step.
Modern automotive development runs on interdependent tasks scattered across tools and teams — requirements reviews, specification cross-checks, test-case generation, pipeline triggers, and error management: detecting, classifying, and filing defects without manual intervention. We design and deploy task-specific AI agents that execute these chains end-to-end, without a human in the loop at every step. Built on open agent frameworks and wired into your existing toolchain, they can run overnight what used to take days of back-and-forth — removing the handoff latency that compounds across a development cycle.
Engineering cycles that run unattended. Coordination overhead cut at the source.
Built by engineers who shipped software-defined vehicles end-to-end at BMW and VW Group — and deployed entirely on your infrastructure.
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From ECU prototype to production — we've shipped SDV systems end-to-end for VW and BMW Group.
Built on over 15 years of Connected Car engineering across the VW Group and BMW Group. From ECU prototype to production — we've shipped Software Defined Vehicle systems end-to-end. We know where AI creates leverage in your development process — and where it doesn't.
Founder-led and hands-on — you work directly with the engineer who shipped these systems, fluent in both AI and automotive.
After 15 years inside BMW and VW Group, we founded K1Logic in Munich in 2026 — because we kept seeing the same bottlenecks stall programs and knew what it would take to fix them. That depth means zero translation loss between your engineering bottlenecks and the technical solution. We don't just treat data as abstract numbers in a cloud dashboard; we understand the hardware that generates it. From how signals originate in ECUs and bus systems to the physical behavior of the vehicle on the road, we combine this systems view with modern AI architectures to build solutions that hold up in production.
Everything runs on your infrastructure — no data leaves, no lock-in. Full ownership from day one.
Strict IT policies, TISAX requirements, and GDPR make cloud-first AI a compliance challenge. We've worked inside these constraints for over a decade — on BMW and VW Group infrastructure, with their security protocols and compliance frameworks. Everything runs on your systems. No data leaves, no lock-in. Full ownership from day one.
We clarify where AI can create measurable value in your development process — in a way that is technically sound, measurable, and feasible with reasonable implementation effort.