Enterprise AI has an awkward middle. Large corporations hire consultants and build teams. Everyone else either overpays for advice or buys a tool nobody has time to implement.
RapidCanvas is aiming straight at that gap. The Austin-based company said Friday it closed a $29M Series B led by Vertex Ventures Southeast Asia and India, with Hitachi Ventures joining and Accel, Peak XV Partners, Valley Capital Partners and Titanium Ventures returning. Total funding now sits at $52.5M.
Software wrapped around field engineers
The sales pitch bundles software with people. Customers get the company’s AI platform plus field engineers who build, deploy and maintain applications with them, paying through subscriptions rather than a large upfront consulting bill.
That platform rests on three pieces: a context engine that captures how a business actually works, a canvas of reusable components, and a harness that watches deployed applications. Chief among the claims is an eightfold rise in annual recurring revenue over six quarters.
Co-founders Rahul Pangam and Uttam Phalnikar target companies between $100M and $10B in revenue, a band with AI budgets but thin engineering benches. More than 40% of customers now run several AI applications in production.
The risk is the model itself. Pairing human engineers with subscriptions is expensive to scale, and it looks a lot like consulting with a software wrapper. RapidCanvas insists the reuse library gives projects a head start, which is what would make the economics work at volume.
For now, investors are funding a simple thesis: the next wave of enterprise AI buyers will not be the Fortune 100.
