Stigg 2.0

The usage runtime for AI products

Software EngineeringDeveloper ToolsArtificial Intelligence

▲ 126 votes28 commentsLaunched Jul 1, 2026

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Stigg is the usage runtime for AI products: the real-time enforcement and governance layer between your app and your billing stack. It decides what every customer, user, team, and agent can do, the moment they try. Millisecond credit checks, zero overdraft, enterprise governance, and modular BYOC. Metering, credits, entitlements, and governance in one runtime. Enforce in the request path instead of reconciling on the invoice. Free forever for AI startups.

AI Analysis

📝 Summary

Stigg 2.0 is the usage runtime for AI products, acting as a real-time enforcement and governance layer between apps and billing systems. Core features include millisecond credit checks, zero overdraft protection, enterprise governance, metering, credits, entitlements, and modular BYOC support. It enforces policies directly in the request path instead of post-invoice reconciliation. It solves pain points like unpredictable AI usage costs, lack of real-time control over users/agents, and complex governance. USP is unified real-time decisioning for usage-based AI products, free forever for AI startups, enabling safe scaling without billing surprises.

📈 Market Timing

With explosive AI growth in 2025-2026, usage-based pricing (tokens, agents) dominates, creating strong demand for real-time governance to control costs and prevent overruns. Real-time tech is mature, user needs for AI tooling are surging, and economic focus on efficiency supports developer tools. Excellent Timing.

✅ Feasibility

Technical difficulty is medium-high for low-latency enforcement and integrations, but the product demonstrates it's achievable. Dev/ops costs are standard for SaaS with usage processing; low supply chain risk, moderate compliance (privacy/GDPR) for enterprises. Strong scalability in cloud. High overall, due to modular design and proven AI market fit.

🎯 Target Market

Main segments: AI/ML engineers, startup founders, product teams at tech companies building usage-based AI apps/agents. Industries: AI, developer tools, SaaS. Geographic: primarily US, Europe tech hubs. TAM for AI billing/governance software ~$2B+, SAM ~$500M, SOM ~$100M. Pain points: cost overruns, entitlement complexity. High willingness to pay to mitigate financial risks.

⚔️ Competition

Medium. Direct competitors: 1. Orb (orb.com), 2. Metronome (metronome.com), 3. Lago (getlago.com), 4. Amberflo (amberflo.io), 5. Stripe Billing (stripe.com). Advantages: AI-specific agent governance, true real-time request-path enforcement with zero overdraft, free for AI startups, BYOC modularity. Disadvantages: narrower AI focus vs. general billing platforms; potentially fewer integrations than incumbents like Stripe.

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