Span, an engineering intelligence platform built to bring clarity to software teams in the AI era, announced the closing of a $25 million funding round from leading investors, founders, and CTOs. The new capital supports platform expansion aimed at improving visibility, alignment, and operational efficiency for modern engineering organizations.
Span originated from a widely shared challenge inside growing companies: buried context slowing execution. As teams scaled and workflows spread across tools and meetings, alignment work began consuming significant time. Earlier leadership roles inside large engineering organizations highlighted recurring gaps in understanding where effort went, how resources were allocated, and how much work fueled product innovation versus maintenance.
These issues intensified with the rise of AI. While AI accelerated coding inside IDEs, planning, collaboration, and reporting retained longstanding bottlenecks across the outer loop of development. Engineering leaders continued seeking evidence-based clarity on team activity, friction points, and emerging shifts driven by AI adoption.
Span addresses this challenge by unifying signals across code, tickets, incidents, and tools to expose where time flows and how AI reshapes development workflows. The platform automates routine updates, R&D attribution, and information retrieval, reducing organizational friction and restoring focus to impactful work.
Span delivers differentiated value through context-rich insights, resilience to imperfect data, traceability back to code-level artifacts, and flexible deployment controls. Development has taken place in collaboration with engineering leaders at Ramp, Vanta, Carvana, Intercom, Braze, Writer, URBN, and ClassPass, enabling real-world validation across AI-forward teams.
This new funding accelerates work toward a future where critical questions about engineering activity, codebases, and team performance can be answered instantly. With direct integration into repositories, tools, and work patterns, Span aims to reduce coordination loops, eliminate manual reporting, and provide always-on context for fast-moving software organizations.