When Spyri Karasavva was at Stripe, pricing meant long hours building and enforcing guidance for SaaS products. “Pricing was always hard,” she recalled. “Today, with AI-native companies shifting to usage-based, hybrid, and outcome-driven models, and iterating weekly, the complexity has only grown. Yet most sales teams are still stuck in spreadsheets, Slack threads, or bloated CPQs built for a slower era.”
Karasavva founded Dealops in response to that gap, aiming to give go-to-market teams the ability to “ship pricing strategies fast, test them in live deals, and scale what works.” The San Francisco-based startup has now raised $7 million from Pear VC, General Catalyst, and other backers including leaders from OpenAI, Anthropic, Stripe, and Salesforce to advance that mission.
From Static Tools to Real-Time Pricing
Flat-rate and seat-based pricing, long the norm in software sales, is giving way to models that change frequently. In AI and enterprise software, companies like OpenAI and Anthropic are introducing usage-based and hybrid approaches, and adjusting terms in near real time. While product and revenue teams move quickly, quoting processes often lag behind, relying on legacy Configure-Price-Quote (CPQ) systems that expect annual or semiannual price changes.
Dealops replaces those static systems with what it calls a “deal pricing platform,” designed to operate inside the sales cycle. According to the company, the software offers AI-driven pricing recommendations based on deal context, historical data, and usage patterns, along with Slack-native approvals to avoid delays. The platform integrates with Salesforce, Snowflake, and other tools, allowing companies to launch in about a week without external consultants.
Teams like Plaid and Airwallex have adopted the product to scale usage-based pricing, test new models, and give sales representatives real-time guidance. “Dealops gives us structure and visibility, with a feedback loop that allows us to continue to improve on our pricing strategy, so that over time, we’re not just quoting faster, but we’re able to quote smarter,” said Maggie Bouscaren, Head of Pricing at Plaid.
The company reports that customers have seen quoting times improve by a factor of ten, average contract sizes increase by more than 30%, and product attach rates rise by 50%. It says it has already processed more than $1 billion in revenue through its system.
Positioning in a Shifting Market
The pricing software market, which Dealops estimates at $25 billion in potential, includes incumbent CPQ providers as well as newer entrants focused on automation and analytics. While many legacy tools support complex product catalogs and configuration rules, they were built for sales environments where pricing was stable and approvals could take days or weeks.
Karasavva’s pitch is that modern revenue teams need infrastructure that moves as quickly as their product and market changes. “We’re building the pricing system of record for modern sales teams,” she said. “We’re onboarding teams from Series A startups to global public companies, because pricing complexity isn’t a ‘big company problem,’ it’s a modern GTM problem.”
Investors see the timing as favorable. “AI is transforming how value is delivered and it’s exposing how broken pricing systems are,” said Vedant Suri of General Catalyst. Kathleen Estreich, a partner at Pear VC, added, “Spyri and her team lived this problem at Stripe and are solving it with precision and speed.”
With its new funding, Dealops plans to expand its team, build out its product roadmap, and reach more AI and enterprise software companies. The challenge will be scaling in a competitive field while proving that its approach delivers sustained improvements in revenue performance, not just faster deal cycles.
