Following industries and services news from the Dominican Republic
Provided by AGPSAN FRANCISCO, May 12, 2026 (GLOBE NEWSWIRE) -- Roadrunner, the AI-native revenue infrastructure company, today announced $27M in funding — a Seed led by Mamoon Hamid at Kleiner Perkins, and a Series A led by Trae Stephens at Founders Fund — alongside the general availability of its platform. Roadrunner is rebuilding quote-to-cash from the ground up, starting with CPQ.
Quote-to-cash touches every dollar of revenue a company generates. It is also the most broken workflow in the enterprise. Pricing models have exploded in complexity, hundreds of SKUs, consumption-based contracts, AI-based outcomes, while the underlying software has barely changed. The result is painfully familiar to anyone who has worked in enterprise sales: reps spend hours manually assembling quotes, approvals spiral through Slack threads and email chains, and deals still get structured wrong. CIOs consistently rank CPQ among their top operational pain points. Sales teams hate it.
Roadrunner was co-founded in 2025 by Joubin Mirzadegan, Ajay Natarajan, and Eugene Shao to uniquely solve this problem.
Roadrunner is replacing CPQ with a new category: PQA: Prompt, Quote, Approve. It’s an agentic stack rebuilt from scratch on a data model designed for how enterprise deals actually get done today. Roadrunner intelligently recommends deal configurations, enforces pricing policies, and automates approval routing, giving every rep the ability to structure any deal instantly, as if they were the best rep in the company.
"This problem haunted me throughout my entire sales career," said Joubin Mirzadegan, CEO and Co-Founder of Roadrunner. "When I was an AE, the underlying software systems would not permit me to get deals done. We built custom Frankenstein things on top of Salesforce CPQ and other solutions that just don't work. The data models do not work. When I got to Kleiner Perkins, I sat down with enterprise CIOs and CROs and asked them what was most broken. Uniformly, all of them said the same thing: sales is being let down by the software they depend on to close deals. We didn't set out to improve CPQ. We set out to replace it."
Founders Fund led the Series A, with Trae Stephens joining the board.
"Sales still runs on surprisingly manual and fragmented systems,” said Trae Stephens, Partner at Founders Fund. “Roadrunner is using AI to streamline the complex CPQ process, improving efficiency and accelerating revenue growth as companies scale. Joubin has assembled a world-class team to fix this critical but historically overlooked part of the sales process."
Roadrunner was incubated at Kleiner Perkins - the firm's first incubation since Glean - with Mamoon Hamid leading the Seed.
“Quote-to-cash touches every dollar of revenue a company generates, yet the systems behind it were built for a different era. Joubin understood this better than anyone because he lived the pain in sales, then heard it repeatedly from CIOs and CROs at Kleiner Perkins. His insight was clear: CPQ is not a configuration problem, it is an architecture problem. You cannot fix a broken data model by patching it,” said Mamoon Hamid, Partner at Kleiner Perkins. “Roadrunner is rebuilding the revenue infrastructure layer from the ground up, starting with CPQ, and we’re proud to have incubated the company and led the seed.”
The funding will be used to scale Roadrunner's team, deepen enterprise customer partnerships, and accelerate the build toward a full quote-to-cash platform spanning pricing, quoting, approvals, billing, and beyond.
About Roadrunner
Roadrunner is the AI-native revenue infrastructure company rebuilding quote-to-cash from the ground up. Its PQA platform — Prompt, Quote, Approve — replaces legacy CPQ with an agentic stack designed for how enterprise deals actually get done. Roadrunner was incubated at Kleiner Perkins and is backed by Founders Fund. For more information, visit roadrunner.ai.
Press Contact: press@roadrunner.ai
Legal Disclaimer:
EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.