What we’re building

Problem

Enterprises spend 300B-$1 T+ annually on internal software, much of it on custom applications built on top of legacy systems and fragmented platforms.

Enterprises build custom software because off-the-shelf solutions don’t fit the complex and bespoke nature of real work. This spend is accelerating as companies replace legacy tools with ones that natively integrate AI. Leaders want leverage, but engineering expertise is tied up in core products and most available solutions don’t fit their needs.

Current Solutions

Current AI products excel at certain use cases, but don’t fit the majority of enterprise work:

• Vertical AI (e.g., Rillet) → require risky migrations, and can’t adapt to bespoke, cross-system processes
• AI replacements (e.g., Decagon) → automate low-hanging fruit then escalate complex tasks to humans
• AI builders (e.g., N8N) → build point agents and automations, not full applications with tight human / AI collaboration and data understanding for business users.
• Legacy builders (e.g Retool, Superblocks) → built for technical builders vs. business users, full stack building capabilities were made as an afterthought, lack semantic data layer just have integrations.

These categories all add value, but they leave the largest gap: the bespoke, cross-system workflows that define most enterprise operations and demand tight human-AI collaboration.

Our Solution