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.
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.
