As artificial intelligence transforms the software industry, companies are facing new business challenges. Every prompt, generated image, automated workflow, and AI agent action has a cost.
Unlike traditional Software-as-a-Service products, where revenue is highly dependent on the number of users or subscription plans, AI-powered products incur compute costs each time a customer uses them. This is forcing software companies to rethink how they manage access, usage, and pricing in real time.
stig team
(Photo: Stig)
The problem has become so serious that some of the world’s largest AI development companies, including OpenAI, have begun building their own internal infrastructure to determine whether a user has the credit, permissions, and budget to complete an AI request before processing it.
Israeli startup Stigg says it was founded to address that problem.
Founded in Tel Aviv in 2021 by former New Relic colleagues Dor Sasson and Anton Zagrebelny, the company develops software that allows vendors to control in real-time what customers, teams, and AI agents are allowed to use and how much of their services.
The founders say the idea grew out of Sasson’s experience leading AI product development at New Relic. A customer adopted an AI-powered log analysis tool, but the company struggled to determine who had access to the feature and how to manage pricing and usage.
“The answers came back to us as a spreadsheet,” Sasson said of the company’s existing qualification system.
The experience highlighted what the founders saw as widespread weaknesses in the software industry as a whole. Although companies have become highly efficient in product development, systems for managing pricing, feature access, and customer entitlements often remain fragmented across billing platforms, application code, and manual processes.
The rapid adoption of AI is exacerbating these challenges.
Traditional SaaS companies typically charge customers based on subscription tiers or number of users. In contrast, AI products often need to monitor multiple variables simultaneously, such as prompts, image generation, automated workflows, AI agent actions, credits, and spending limits.
This complexity has led enterprise customers to seek greater control over their AI spending. Increasingly, companies want to allocate AI budgets by department, limiting the amount that individual employees or AI agents can consume and preventing unexpected computing costs, Stig said.
The company says it has seen cases in which one heavy user depleted an organization’s AI budget in a single day before administrators realized what had happened.
OpenAI released details of its internal infrastructure earlier this year, describing a system that checks user restrictions, credits, and entitlements before processing requests, and offering a glimpse of how leading AI developers are tackling this challenge. Stigg’s founders say this architecture is similar to the approach they took when designing their own platform.
This week at the AI World’s Fair conference, Stig announced what the company calls its “usage runtime” platform, designed to manage the entire process from measuring AI usage to billing customers. The company says the system includes real-time usage tracking, spend management, high-volume metering capabilities, and the ability for enterprise customers to deploy the platform within their own cloud environments.
Stig said collaboration software company Miro implemented an AI credit model within six weeks using its platform. The company estimated that the project would require approximately 5,000 engineering hours if developed in-house.
The startup also introduced a free version aimed at early-stage companies, while continuing to target large enterprise customers whose AI infrastructure requirements become more complex as they grow.
Industry analysts increasingly believe that usage management will become the core infrastructure of AI businesses, rather than just being part of billing systems. As AI services continue to expand, companies are looking for ways to avoid unpredictable operational costs due to increased customer demand.
For startups like Stig, this shift means an opportunity to offer technology that many companies might find too costly or complex to build themselves.
