Dor Sasson

Dor Sasson co-founded Stigg, a platform for controlling software access, measuring consumption, and enforcing commercial rules. His work connects pricing strategy to the software needed to enforce it while a product runs, increasingly addressing the spending controls AI products need when each request can create a new cost.

From product work to monetization infrastructure

Before Stigg, Sasson worked at SignifAI and New Relic on AI operations products, shipping anomaly detection, forecasting, and root-cause analysis. That experience building predictive systems later informed his skepticism about using historical consumption to predict how customers will respond to new prices. His early work on Enlightenment Park addressed a different part of the problem: exposing feature usage and consumption at the account level. Connecting that visibility to rules governing what customers could access helped lead him to found Stigg with Anton Zagrebelny in 2021.

Sasson’s experience with New Relic’s pricing overhaul helped shape Stigg’s initial problem: changing a business model could require extensive changes to the application that enforced it. In his account of pricing and packaging, conversations with engineering, product, growth, and pricing teams helped develop Stigg’s direction. The aim was to make commercial changes possible without repeatedly rebuilding the product around them.

That experience also informed his view of pricing as a continuing process. Research, implementation, rollout, and customer feedback form a loop; infrastructure needs to make the next iteration practical. A price or package is only useful if the product can grant the promised access, measure consumption, and respond when a customer reaches a limit.

Stigg developed into a modular monetization platform covering entitlements—the features and quantities a customer may use—alongside metering and subscription capabilities. Its December 2024 funding announcement described a $17.5 million Series A and customers including Miro, Webflow, and PagerDuty. Miro’s AI workspace illustrated a concrete need: administrators wanted visibility into their organization’s AI-credit consumption. Metering made that consumption legible to the people responsible for managing it.

Commercial flexibility and control over spending

Sasson’s arguments address three related problems:

• Modular monetization: Catalogs, entitlements, metering, and commercial workflows have different responsibilities. In his argument for unbundling monetization infrastructure, separating those components lets teams change how they sell and govern a product without allowing a billing vendor’s architecture to dictate the business model.

• Control before consumption: Autonomous workflows can spend continuously, so a monthly invoice arrives too late to prevent overspending. Sasson advocates checking permissions and available funds before inference, then settling the cost asynchronously. Concurrency makes the distinction consequential: several agents can each see the same remaining balance and collectively spend more than it contains. Atomic reservations account for funds already committed to work in progress; settlement reconciles those reservations with actual consumption. Different credit pools need explicit rules about which balance is spent first, and organization, team, user, and agent budgets need connected enforcement.

• Pricing requires customer judgment: Drawing on his background in AI operations, Sasson challenges promises that historical usage can predict the right future price. Buyers renegotiate, users change behavior, and competitors respond. Recalculating last year’s consumption at a new rate cannot establish how customers would behave under that rate. He favors infrastructure that supports experimentation while leaving strategic judgment with people.

The June 2026 launch of Stigg 2.0, announced by Sasson and Anton Zagrebelny, extended this agenda into AI usage governance: credit wallets, reserve-and-settle operations, usage metering, and enforceable budgets across customers and agents. It brought the commercial rules governing a product into the execution of requests that create costs.