Product memo
AI product teams and developers use Stigg for real-time usage metering and enforcement. It handles credit infrastructure and entitlements, allowing teams to price AI features without building custom billing logic. The platform integrates with existing billing stacks, removing a common friction point for AI companies scaling their offerings.
For who
AI product teams and developers
Solves what
Real-time usage metering, enforcement, and governance for AI products.
- Usage runtime for AI
- Real-time credit and entitlement management
- Deployable in VPC
In their own words
Every AI request is a spend decision. Make it in milliseconds.
The usage runtime that decides what every customer, user, and agent is allowed to do. Credits, entitlements, metering, and governance in a single enforcement layer.
Meter usage, manage entitlements, and monetize AI features in real time, without building the billing infrastructure yourself.
Commercial cues
Model
subscription
Free tier
Yes
Trial
Available
Pricing Strategy
- • A free tier removes friction for early-stage AI product adoption.
- • Higher-volume plans offer predictable pricing for scaling AI products.
Operator context
Operating setup
Team
VC / larger team
LLM classification
Founded
Jul 2026
HQ
United States
Platform
API
Audience
Developers
Social footprint
Tech stack
Market demand
Stigg keyword demand
4 keywords
Market demand is Starter-tier market intelligence.
Derived from this product’s latest SimilarWeb keyword mix — directional demand, not proof.
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Complex Stack
About Stigg Expand
Stigg offers a specialized usage runtime for AI product teams and developers, addressing the complex challenge of metering and enforcing AI feature usage. It provides the infrastructure for real-time credit management, entitlements, and governance, allowing companies to price their AI offerings without developing custom billing systems.
The platform integrates with existing billing stacks, serving as a critical layer for AI companies that need to scale rapidly and reliably. This focus on a specific, technical problem within the AI ecosystem helps teams manage usage and pricing effectively.