Today we’re excited to share that we’ve raised $25 million from a group of world-class investors, founders, and CTOs to help engineering teams reach their potential in an era defined by AI transformation.

Why we started Span

Span began with a simple but familiar frustration: as companies grow, they slow. Not because people lack the skill or the will, but because context gets buried. What used to be clear around a small table now lives in ten tools and a dozen meetings. The effort required just to stay aligned becomes its own kind of work.

We’d both felt this pain firsthand. In our previous roles running large engineering organizations, we had dashboards, reports, and rituals meant to keep everyone in sync. Yet we still found ourselves chasing the same questions: 

Where is our time actually going? Are we investing in the right things? How much of our effort is spent keeping the lights on instead of pushing the product forward?

Over time, we realized the problem wasn’t a lack of data — it was that the data lacked context. The more tools we added, the more fragmented the picture became. We started Span to rebuild that missing layer of understanding. And to give teams back the time they spend maintaining it.

That problem of buried context has only grown sharper with the rise of AI. 

The shift in software development

AI has rewritten how software gets built. Inside the IDE, code comes together at remarkable speed. But in the outer loop — planning, collaboration, and reporting — the old bottlenecks remain. Leaders still spend enormous energy trying to understand what’s happening, what’s slowing teams down, and what’s truly changing with AI.

That’s the new challenge in engineering: navigating AI transformation with clarity and evidence.

Span gives teams that clarity. By unifying signals across code, tickets, incidents, and tools, it reveals where time really goes, and how AI is reshaping the development lifecycle. Beyond visibility, Span creates leverage: automating the manual work of writing updates, attributing R&D for tax credits, and searching for answers.

The result is an organization that understands itself better, moves with less friction, and gets more time back for the work that matters.

Span unifies data across code, tickets, and tools to provide a complete picture of engineering impact and automate busywork.

What makes Span different

Works without perfect hygiene

We designed Span for the world as it really is: messy, fast-moving, and rarely perfectly documented. Our AI reasons over imperfect data and fills in gaps, giving you a clear picture of where time is really going.

Holistic context, not just numbers

Productivity can’t be captured by a single metric, and sentiment alone isn't enough either. We combine metrics, surveys, and behavioral context to reflect the full story of productivity and team health.

Traceable to the code level

Every insight in Span is verifiable back to the code and work artifacts themselves. When it comes to measuring AI, we’re the only platform that detects AI-generated code at the chunk level, rather than relying on inconsistent vendor data or surveys.

Flexible to deploy your way

We built Span with granular permissions and controls from the start, so you can shape visibility and reporting in a way that fits your team’s values and operating philosophy.

Built alongside world-class practitioners

For the past two years, we’ve built Span side-by-side with forward-thinking engineering leaders at companies like Ramp, Vanta, Carvana, Intercom, Braze, Writer, URBN, and ClassPass.

These organizations are leading AI transformation with hard evidence, not hype. They’re running leaner, automating busywork, and preserving the agility and focus of a small team, even as they scale.

What's next

This funding allows us to go deeper on what we’ve started. We’re building toward a future where the hardest questions about your team and codebase can be answered in seconds, not days.

Because Span already connects directly to your repos, tools, and work patterns, it can surface real answers without the endless back-and-forth. That means fewer coordination loops, fewer manual reports, and more space for the work that really matters.

The future of software organizations will look different. They’ll be flatter in structure but larger in impact. They’ll rely less on ceremony and more on continuous, always-on context that keeps everyone aligned.

We’re incredibly grateful to our team, our early customers, and our investors for believing in this vision.

Thank you for being part of this journey. We’re just getting started.