RapidCanvas raises $29M Series B to bring Fortune 100-grade AI to every enterprise

Enterprise AI startup RapidCanvas has raised $29 million in Series B funding to help businesses deploy custom AI applications without spending millions on consulting firms or hiring large in-house engineering teams. The funding comes as companies face growing pressure to move beyond AI experiments and show measurable returns on their investments.

The round was led by Vertex Ventures Southeast Asia & India, with participation from Hitachi Ventures. Existing backers Accel, Peak XV Partners, Valley Capital Partners, and Titanium Ventures joined the financing, bringing RapidCanvas’ total funding to $52.5 million.

The Austin, Texas-based company announced the funding on Friday, reporting an eightfold increase in annual recurring revenue (ARR) over the past six quarters. RapidCanvas said more than 40% of its customers now operate multiple AI applications in production, suggesting that demand is shifting from experimental projects to everyday business operations.

The funding comes at a time when enterprise AI adoption faces a familiar obstacle: companies want the benefits of AI but often lack the technical resources to put it to work.

Large corporations can afford dedicated AI teams and expensive consulting engagements. Smaller enterprises face a tougher choice: pay millions for outside expertise or buy software their employees may struggle to implement.

RapidCanvas is betting that combining software with hands-on engineering support can close that gap.

Bringing enterprise AI beyond the Fortune 100

Founded by Rahul Pangam and Uttam Phalnikar, RapidCanvas targets businesses generating between $100 million and $10 billion in annual revenue. These companies often have AI budgets but lack a clear path from initial testing to applications that deliver business results.

Instead of selling customers another platform to figure out on their own, RapidCanvas pairs its AI software with field engineers who work directly with businesses to build, deploy, and maintain custom applications.

The company calls this its Hybrid Approach. Customers pay through subscriptions rather than committing to large, upfront consulting projects.

The service runs on an AI platform built around three components. Its Enterprise Context Engine captures business processes and institutional knowledge. The Visual Development Canvas helps engineers build applications using reusable software components, and the Operational Harness manages deployed applications and their governance.

The company claims its reusable code library gives new projects a 60% head start, though that figure comes from RapidCanvas, not independent testing.

So far in 2026, RapidCanvas says more than 75 enterprises across manufacturing, financial services, retail, business services, and infrastructure have used its applications to make 1.4 million AI-assisted decisions.

“AI can be the great equalizer, but so far its biggest wins have gone to the Fortune 100. We want to give every enterprise the same opportunity,” said Rahul Pangam, co-founder and CEO of RapidCanvas. “Vibe coding has made it easy to start building with AI. Getting AI into production reliably and safely still remains the biggest gap. Our growth over the past six quarters is evidence that AI in enterprises is moving beyond pilots into production and real operations.”

The challenge is getting AI into production without introducing reliability, security, or operational problems. RapidCanvas says conversations with more than 400 business leaders revealed that most executives expect returns on AI investments within six to 12 months, yet relatively few companies have progressed beyond pilots.

That disconnect is central to the company’s pitch. Businesses increasingly want AI systems that can handle actual work, rather than demonstrations that never become part of daily operations.

Investors see an opportunity in that shift.

“Enterprise AI will ultimately be measured by the economics of delivering outcomes at scale,” said Radhika Ananth, Head of India and Investment Director at Hitachi Ventures.

RapidCanvas plans to use the new funding to hire more field AI engineers across the United States, Brazil, and India. It will invest in its software platform, strengthen application governance, and grow its sales operations and partner network.

For RapidCanvas, the bigger test is whether its combination of engineers and reusable software can deliver custom AI applications at a cost that makes sense for businesses outside the Fortune 100.

Its reported ARR growth suggests customers are responding. The next challenge is proving that the model can scale without losing the hands-on support that makes it attractive in the first place.

RapidCanvas AI