Jirka BachelFounder & CEO

I have been in engineering for nearly twenty years, often working as an engineering manager or CTO. No matter how hard we worked, the business side always felt engineering was too slow. In late 2024, when AI coding tools became popular, we wanted to understand the developer story behind each commit. We spent months researching, posted on LinkedIn about opening the black box of IT, and immediately received interest from unicorns and Fortune 500 companies.

We validated the concept through that single LinkedIn post. The overwhelming response from engineering leaders and executives proved that visibility into software development was a massive, industry-wide pain point. Because of this high demand, we were able to raise our seed round very quickly and begin building the performance layer for modern engineering.

Our number one feature is helping companies prove the return on investment on their AI coding spend. For instance, executives have complained that they burned through their yearly AI budgets in a few months without seeing any concrete product improvements. Navigara solves this by establishing a clear link between AI expenditures and actual developer output.

Many companies pay premium rates to outstaffing vendors in South America, Europe, or India. Navigara allows clients to analyze the actual performance and output of these external engineers. By measuring their productivity against clear benchmarks, companies can identify inefficiencies and lower their vendor invoices.

Late-stage venture capitalists and private equity firms use our platform to perform tech due diligence before investing. We allow them to benchmark the engineering team of a target company not just against general industry standards, but also against the most successful portfolio companies in their fund to ensure their engineering is truly exceptional.

CEOs often travel and worry that engineering is moving too slowly. With Navigara, a CEO can check the dashboard on a weekend and immediately see what the team built, how they performed against industry standards, and if they are outperforming top AI coding teams. This transparent data builds immense trust between executive leaders.

We needed a standardized unit to measure software development, so we invented Engineering Throughput Value, or ETV. We published a white paper benchmarking the open-source engineering performance of tech giants like Google, Microsoft, Meta, and OpenAI. ETV allows us to measure engineering throughput at a massive scale of thousands of developers.

Many companies brag about how high their AI bills are to show they are transforming. But measuring a successful AI transition by your billing statements is like measuring personal success by a credit card bill. It is an expensive thing to brag about, but it is not how you run a productive, profitable business.

When companies face rising costs without visibility, their default response to manage budgets is to fire developers. Navigara helps engineering teams prove that their work directly delivers on the roadmap, increases revenue, or saves money. This data-driven proof allows developers to justify their roles and keep their jobs.

We primarily serve companies with fifty or more engineers, which is when middle management is introduced and executives begin losing visibility into daily work. For smaller companies, the outreach usually comes directly from the CEO who wants an unbiased view to ensure their team is adopting AI fast enough to beat the competition.

While CTOs are often too busy to engage initially, we found our primary champions are AI transformation managers. Navigara gives these managers the exact data they need to prove to the board that their AI initiatives are working. It also helps CTOs enter board meetings with reports showcasing exceptional performance.

The value is generated almost instantly. We connect to Git repositories, ticket systems like Jira, and AI spend tools. Because these systems have extensive histories, we can analyze the data immediately. Customers can compare their current performance to a year ago, before they adopted AI coding tools.

The biggest concern is how developers will react to being monitored, as no one likes to feel measured. We explain that focusing on individual metrics is counterproductive. Instead, we encourage leaders to focus on team-level performance, which represents the collective success of all members and aligns everyone's goals.

In Moneyball, a small baseball team achieved record wins by analyzing player statistics differently than the rest of the league. We do the same for software development. While the league focused on traditional metrics, the movie showed that getting on base was what won games. For us, delivering the product roadmap is what drives revenue.

Before AI, the CTO was strictly a management role. Today, the technology landscape is changing so fast that hands-on experience is critical. CTOs need to personally test AI tools to understand their team's potential. Without hands-on experience, it is impossible to manage developer performance effectively in the AI era.

Engineering departments are often run on vibes, with leaders telling the board that their teams are the best in the world. When Navigara provides objective benchmarks showing their average performance is actually standard, some CTOs get defensive because it contradicts what they reported to management.

We want to act as an AI consultant that never sleeps. We are introducing a structured framework and guide that provides engineering teams with rules and checks to pass. This roadmap helps teams transition from traditional workflows to highly productive, AI-native engineering systems.