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SolutionPlus
Automotive AI
Automotive AI
Duration: Ongoing
Dedicated teams

Building two automotive platforms in parallel

One accountable delivery lead set the delivery direction while senior engineers across our offices built both platforms in parallel. Traceability and validation were part of the release work.

Platforms built
2 in parallel
Delivery friction
Zero
Compliance
ISO 26262 + SOTIF
Automotive AI - product preview
Programs
Two product lines in parallel (SGAF + NavDB)
Operating model
Embedded team with shared milestones and one technical lead across streams
Standards in scope
ISO 26262, ISO 21448 (SOTIF), UL 4600-aligned workflows
Risk posture
Evidence-first: traceability, validation hooks, and performance budgets baked in

Overview

Automotive AI GmbH, based in Germany, delivers automotive intelligence and simulation solutions in a regulated, performance-critical environment. Their work supports safety-sensitive systems where traceability, validation, and technical reliability are non-negotiable.

The challenge

AAI needed to build two independent products from scratch simultaneously, both reaching production-ready MVP stage on strict timelines. Each platform had to integrate with existing workflows, handle complex automotive data structures, and scale without architectural rework — all without creating coordination overhead between the two streams. They needed a delivery partner who could take ownership and operate with minimal handholding.

Our role

SolutionPlus joined as an embedded engineering partner, taking ownership of technical discovery, architecture design, estimation, and delivery planning across both products. Work was organized around clear milestones and predictable iteration cycles, with continuous alignment to AAI's internal teams. The standard was straightforward: build systems that hold up under regulatory and operational pressure, not just at launch.

What we built

Product 1: Safety Guidance and Analytics Framework (SGAF)

A structured platform for managing and validating safety cases across the lifecycle of complex automotive systems, including autonomous vehicle environments.

  • Traceability between safety claims, regulatory origins, and mitigations

  • Continuous monitoring of Safety Performance Indicators

  • Automated detection of missing evidence and incomplete arguments

  • Safety assertion decomposition across vehicle phases and lifecycle stages

  • Compliance alignment with ISO 26262, ISO 21448 (SOTIF), and UL 4600

Product 2: NavDB — Navigation Database Management System

A dedicated platform engineered for large-scale geospatial data management in automotive simulation and validation environments.

  • Optimized ingestion and processing pipelines for high-volume mapping datasets

  • High-performance spatial query handling

  • Secure access controls aligned with automotive compliance requirements

  • Scalable architecture designed for long-term dataset growth without performance degradation

What changed for the teams

Parallel delivery only works when architecture, compliance context, and communication stay in sync. These outcomes reflect that operating model—not heroics.

Platforms delivered
2 production-ready systems, built in parallel
Delivery friction between streams
None
Architecture approach
Designed for extension, not replacement
Team continuity
Consistent technical lead across both products
Ongoing collaboration
Active, grounded in technical transparency

Two roadmaps, one technical spine

Shared patterns for data ingestion, access control, and validation kept NavDB and SGAF from drifting into incompatible designs.

Reviewable safety artifacts

SGAF emphasized traceability and gap detection early, so reviews focused on evidence—not surprise rework.

Geo data without gridlock

NavDB pipelines were built for growth: heavy datasets, predictable queries, and operational guardrails from the first releases.

Why it worked

Domain familiarity shaped the decisions that mattered most. We invested time in understanding automotive safety logic, simulation tooling, and regulatory context before designing anything.

  • Domain immersion

    We invested time in understanding automotive workflows, constraints, and data realities before writing a single line of code.

  • Structure meets engineering depth

    Berlin-connected delivery discipline paired with experienced engineering teams ensured clarity without compromising technical quality.

  • Transparent execution

    Clear milestones, visible progress, and no surprises. AAI always knew where things stood.

  • Embedded teams

    AAI worked with engineers who felt like an internal extension, without long-term hiring risk or lock-in.

SolutionPlus delivered an automotive simulation platform with advanced mapping and visualization. Their attention to detail and ability to handle complex data sets made them the right partner for an industry as demanding as ours.

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Automotive AI GmbH

Automotive AI

Automotive AI

See it live

Visit the website and product we helped build — still running in production today.

Get in touch

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