Sonatus Innovation & Technology Culture

What types of products or services does your engineering team build? What problem are you solving for customers?

I work on our AI Technician product, which is software designed to help service technicians quickly diagnose and resolve vehicle issues. For example, a technician can ask the AI how to troubleshoot an error reported by a vehicle sensor and the AI will analyze the problem and recommend actionable steps to fix it. Our goal is to make vehicle diagnostics faster, more accurate and less reliant on individual experience.

Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?

We use AI as a coding assistant on most of our projects. It’s not always about adopting AI for a specific task; often, it’s about leveraging LLM-based tools to help write software more efficiently. In one recent example, I needed to convert a binary file into a human-readable table. Reading binary data manually is time-consuming, but using Gemini, I was able to generate a Python script that converted it into a CSV in seconds.

What would that project have looked like if you didn't have AI as a tool to use? 

Without AI, that task would have taken much longer and I would have had to manually figure out how to parse and process the binary data. While AI speeds up tasks, it isn’t perfect. LLMs can overcomplicate simple problems or generate buggy code that tries to patch symptoms rather than fixing the root cause. Used correctly, AI dramatically improves productivity, but it’s important to remain critical and not become overly dependent on it.

What is the unique story that you feel your company has with AI? 

Automotive AI is actually the culmination of software-defined vehicles. Sonatus’s mission since its founding has been to accelerate the adoption of software-defined vehicles in the auto industry, enabling vehicles to be flexible, updatable, and dynamic. With AI, it now allows us to add intelligence to that list and enable compelling new capabilities that were not possible before.

What was a monumental moment for your team when it comes to your work with AI?

For some context, one of our products, Collector AI, helps OEMs collect vehicle data that enables specific inquiries and evolves them over time through event-driven collection policies. Vehicle engineers can easily create policies through a graphical user interface or, if they want, by directly editing JavaScript Object Notation code. But these approaches require detailed knowledge of the vehicle by an expert engineer.

One monumental moment was when we were also developing an AI enhancement to make it easier for more users inside the OEM, not just technical experts, to use the product. This enhancement enabled them to describe in natural language what they wanted to collect based on specific trigger conditions. While experimenting, we discovered that the tool could intelligently identify useful, relevant information that exceeded our original expectations when we wrote our queries. The AI was able to really understand the intent of the query, and we realized that AI could serve as a thought partner to our users, not only helping them to be more efficient but also helping them to do their work better. We are now rolling out this capability as a fundamental new feature of our product. 

AI is a constantly evolving field. Very few people coming into these roles have years of experience to pull from. Explain what continuous learning looks like on your team. How do you learn from one another and collaborate?

We collectively read a lot. Everything from academic papers to Medium articles and blog posts to market and industry reports. We have weekly technology team sessions where team members “show and tell” on a rotating cadence over cutting-edge topics, both AI and non-AI. Team members are encouraged to attend conferences and symposia and the company supports it. The only condition is to provide a trip report presentation to share your learnings with others!

How does innovation show up in your company culture?

At Sonatus, innovation is a core company principle, driving our daily operations, decision-making and collaboration to quickly deliver customer value. We focus on solving high-impact, real-world problems for original equipment manufacturers, working within constraints like safety, scalability and legacy systems, and innovating within those realities. This mindset leads to breakthroughs like AI-powered tools that analyze vehicle data to automatically detect failures and find root causes, dramatically reducing testing time and improving scalability.

Our culture emphasizes speed and ownership, where small, cross-functional teams are empowered to experiment, prototype, and iterate rapidly. Cross-functional teams work closely from day one, reducing handoffs and accelerating learning. Our AI initiatives started with small teams and are now integrated into our core platform.

Design innovation means thoughtful simplification: making our highly complex and technical products intuitive, usable and scalable. Leadership supports this through constructive debate and psychological safety. In short, innovation at Sonatus is defined by focus, collaboration and impact — not just what we ship, but how we build.

What’s one recent innovation that improved user or employee experience?

Our recent innovation at Sonatus is a conversational AI agent that revolutionizes troubleshooting for OEM testing engineers. By applying AI directly to vehicle data analysis, we’ve cut issue resolution time from roughly 15 days to as little as two days.

This is a breakthrough in user experience. Instead of digging through data tables, dashboards or documentation, engineers can ask natural-language questions such as “Show me all the diagnostic trouble codes” or “What is the root cause of this sensor issue?” or even “Show me how to fix it step by step.” 

AI’s true power lies in its interpretation of real-time and recorded signals alongside an integrated knowledge base — specs, manuals and diagnostic databases — to deliver comprehensive, actionable insights, significantly reducing diagnostic time and improving fast experimentations. 

The innovation’s impact is defined by its seamless integration into existing OEM workflows, dramatically reducing cognitive load and enabling continuous improvement during testing and even long after vehicles are deployed.

How do you balance experimentation with stability?

At Sonatus, balancing experimentation with stability is foundational to how we build products for both safety-critical standard operating procedure and pre-SOP vehicles. We do this by clearly separating where we explore new ideas from where we guarantee production reliability.

Experimentation starts early in controlled environments such as prototypes, simulations and internal tools, often in close collaboration with OEM customers. Small teams are empowered to apply emerging technologies like AI and iterate quickly without compromising vehicle safety or customer trust. Ideas are reviewed by technical/executive leaders, allowing us to move fast while staying grounded.

Once an idea proves valuable, it moves through rigorous quality gates, validation and cross-functional reviews before reaching production. In the automotive industry, stability is non-negotiable. Our software-defined platform supports this balance by enabling new capabilities, such as analytics, optimization or AI-initiatives, to be introduced without disrupting core systems. 

Culturally, teams experiment responsibly. In practice, this balance allows us to innovate fast where it’s safe, while delivering the reliability our customers and drivers depend on.