Real-time enforcement
Make real-time allow/deny decisions for customer, user, or agent actions before a request consumes tokens or exceeds budget. The home page states these enforcement checks run locally with p99 under 10 ms.
Stigg
Stigg is a usage runtime for AI products that helps teams meter usage, manage entitlements, and enforce credits and spend controls in real time. It is designed to work with existing billing systems and deployment models, including hosted cloud, BYOC, and BYODB.
Overview
Stigg is a usage runtime for AI products that decides, in real time, what a customer, user, or agent is allowed to do. It combines entitlement checks, metering, credits, and governance in one enforcement layer so teams can meter usage and control access without building the billing infrastructure themselves.
The product is positioned for teams that need to monetize AI features, usage-based pricing, and spend controls at scale. The site emphasizes local enforcement, high event throughput, deployment options that include cloud, BYOC, and BYODB, and compatibility with existing billing systems rather than a full rip-and-replace migration.
Core capabilities
Credits engine
Track credits with wallets, ledgers, burn-downs, expiry rules, and priority consumption. The site also describes double-entry integrity, immutable ledgers, and balances that update in under 10 ms.
Entitlements management
Define and enforce entitlement logic outside the application codebase, so model changes, pricing tiers, and feature access can be updated without redeploying product code.
High-throughput metering
Capture and aggregate usage events in real time, including token, inference-call, and agent-action activity. The pricing page shows metering throughput tiers up to 1M+ events per second on BYOC.
Governance and spend controls
Apply spend controls for users, teams, and agents at call time. The site frames governance as self-serve caps configured by customers rather than support teams.
Billing system integration
Layer onto an existing billing stack with bi-directional sync. The home page and pricing page mention Stripe, HubSpot, Zuora, Chargebee, Salesforce, NetSuite, and direct invoice support through Stigg or external billing tools.
Common use cases
AI monetization
Launch AI feature pricing with usage-based limits, credits, and automatic resets. Miro’s story shows this pattern for AI tokens, seat-based allocation, and enforcement across the stack.
Feature gating and plan control
Enforce entitlements for feature access or plan tiers without hardcoding pricing rules into the application. The home page says entitlement logic lives outside the codebase, which helps teams change tiers or add-ons without redeploying.
Usage metering and reporting
Meter token, inference, and agent activity in real time so product and finance teams can track consumption accurately. The site describes aggregated usage data, BI-ready reporting, and sync into warehouses such as Snowflake in the Miro story.
Spend control for customers
Set per-user, per-team, or per-agent spend caps that are enforced when a request is made. Stigg positions governance as self-serve controls that customers can configure themselves.
Monetization infrastructure migration
Move off homegrown monetization tooling or migrate large subscription bases without rewriting the product. The Miro case study highlights a migration of tens of millions of subscriptions with no custom scripts and no disruption.
Pros and Cons
Pros
- Combines metering, entitlements, credits, and governance in a single runtime.
- Supports existing billing stacks instead of requiring a wholesale migration.
- Offers deployment choices from hosted cloud to BYOC and BYODB.
- Backed by concrete performance and throughput claims on the public site, including p99 under 10 ms and high event rates.
Cons
- The public pages do not provide detailed implementation steps or documentation coverage for every capability in the extracted source.
- Some integrations and enterprise options appear to vary by plan, so readers may need to confirm fit and pricing for their specific stack.
FAQ
What does Stigg do?
Stigg is a usage runtime for AI products. It handles real-time enforcement, metering, entitlements, credits, and governance so teams can control what customers, users, and agents are allowed to do before requests run.
Does Stigg replace an existing billing system?
Stigg is described as working with existing billing stacks and layering on top of providers such as Stripe or Zuora with bi-directional sync. The pricing page also lists support for billing integrations including Stripe, HubSpot, Zuora, Chargebee, Salesforce, and NetSuite, depending on plan.
How can Stigg be deployed?
The site says Stigg can be deployed as a cloud API, in your own VPC as BYOC, or as BYODB with your own database and event queue. The pricing page also mentions an air-gapped option on the BYOC/enterprise tier.
How fast is Stigg?
The home page says entitlement checks and runtime enforcement are executed locally, with p99 under 10 ms, and the pricing comparison shows throughput tiers ranging from 1,000 events/sec on Build to 1,000,000+ events/sec on BYOC.
Who is Stigg for?
The site highlights engineering teams operating at scale and complexity, and customer stories show usage for AI pricing, plan and add-on management, feature gating, metering, and subscription migration. That suggests it is aimed at product and engineering teams monetizing AI features or usage-based products.
Quick Facts
- Category
- Usage runtime for AI products
- Primary users
- Engineering, product, and monetization teams
- Deployment options
- Cloud API, BYOC, BYODB, air-gapped on enterprise tier
- Billing approach
- Layers on top of existing billing systems with bi-directional sync
- Source domain
- stigg.io
- Customer evidence
- Miro customer story highlights AI pricing, credits, and usage enforcement
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