Overview
- Prevent budget overruns with per-user, per-team, and per-agent spend caps enforced in under 10ms for every AI request
- Real-time enforcement checks each limit, entitlement, and credit expenditure before a token exceeds its budget
- Ship new AI models, tiers, or features without code changes by keeping entitlement logic outside your codebase
- Capture every transaction with high-throughput real-time metering for granular AI usage tracking and aggregation
- Maintain full ownership of subscription and usage data independent of your billing vendor for data privacy and security
- Augment existing billing systems instantly—no migration needed—while adding financial-grade credit infrastructure
- Eliminate fraudulent AI usage through stringent real-time tracking that accounts for every request and transaction
- Automate spend decisions by treating each AI call as a budget check, ensuring profitable growth without slowing functionality
Pros & Cons
Pros
- Real-time enforcement
- Financial-grade credit infrastructure
- Rapid deployment model
- High event-per-second metering rate
- Per user spend controls
- Billing system integration
- Ownership of subscription data
- Prevents token budget overrun
- Priority consumption feature
- Establishes expiry rules
- User-Codebase Independence
- Prevents potential fraud
- Entitlements for quick feature shipping
- Seamless integration with existing systems
- Consolidates pricing and packaging
- Centralized entitlements and provisioning
- Built-in usage metering
- Robust Subscription Management
- Versioning, Lineage and Migrations support
- Embeddable UI widgets
- Prevents vendor lock
- Bi-directional sync feature
- Low latency entitlement checks
- Real-time caching
- Supports offline operations
- Delivered over Edge Network
- Capable of processing high-volume events
- Fault tolerant
- Extensible
- Automated failover
- Asynchronous data replication
- Built-in idempotency
- Auditing and logging
Cons
- Complex integration
- Requires real-time decision capability
- Expenditure closely monitored
- Budget cap limitations
- Rapid deployment may confuse
- High event-per-second rate demanding
- Requires existing billing systems
- Subscription and usage data management
- Ledgers and wallets need management
- Dependency on Stigg's financial infrastructure
Reviews
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❓ Frequently Asked Questions
Stigg is a runtime tool specifically formulated for AI products that allows for the effective management and monetization of AI features in real-time.
Stigg serves the purpose of treating every AI request as a spend decision. It controls what a given customer, user, or agent is allowed to do, permitting real-time control over every AI credit, limit, and dollar spent. Its aim is to ensure growth remains profitable without compromising functionality or speed.
Stigg processes every AI request as a spend decision, providing control over what every customer, agent, or user is allowed to do. For effective management, each limit, entitlement, and credit expenditure is verified before a token surpasses its allocated budget.
Stigg's real-time enforcement feature ensures that millions of AI requests are decided in less than 10ms. It checks every limit, entitlement, and credit expenditure in real-time before a token exceeds its budget, ensuring immediate and accurate spending decisions.
Stigg leverages a financial-grade credit infrastructure, equipped with features such as wallets, ledgers, and credit expenditure. These allow for advanced financial management of AI services, incorporating regulation of burn-downs, priority consumption, and implementing expiry rules.
Key features of Stigg include real-time control over AI credits, limits, and dollars; transaction metering; spend decision making; a robust AI credit system and financial infrastructure; rapid deployment of AI models; real-time enforcement; a comprehensive governance system; integration with existing billing systems; ownership of subscription and usage data; independent user-codebase, and provisions for fraud prevention and efficiency.
Stigg's entitlement feature allows AI features to be shipped swiftly. The entitlement logic resides outside of the user's codebase, enabling rapid deployment of a new model, tier, or feature without having to extensively modify the existing system.
Stigg performs real-time metering at a remarkably high event-per-second rate. This feature ensures that every transaction is captured and accounted for in real-time, providing an accurate and granular view of AI usage.
Stigg is equipped with governance features that provide self-serve spend controls, ensuring a per user, per team, and per agent budget cap. These governance controls allow organizations to regulate spending easily and prevent overspending on AI resources.
Stigg integrates with existing billing systems seamlessly, working alongside them without necessitating migration. This allows organizations to enhance their AI management and monetization capabilities without overhauling their existing platforms.
With Stigg, organizations maintain full ownership of their subscription and usage data, independent of the billing vendor. This feature gives organizations ultimate control and ensures data privacy and security.
Stigg's user-codebase independence means that the entitlement logic lies outside of the user's codebase. This allows for the rapid deployment of a new model, tier, or feature, and ensures that AI feature upgrades or adjustments do not necessitate radical changes to existing codebases.
While Stigg doesn't directly engage in fraud prevention, its stringent real-time tracking and enforcement policies aid in eliminating fraudulent activities by ensuring that every transaction and AI request is accounted for. It also promotes efficiency by automating many aspects of AI feature management and monetization.
Stigg provides a budget cap per user, per team, and per agent, allowing for control over the spending on AI features. This ensures that usage does not surpass allocated budgets, helping to manage costs effectively.
In the context of Stigg, spend decision making refers to the system's process of treating every AI request as a spending decision. It controls what each customer, user, or agent can do, ensuring immediate decisions regarding the allocation and use of resources.
As a runtime tool for AI products, Stigg seamlessly manages and monetizes all AI features in real-time. By treating every AI request as a spending decision and providing comprehensive real-time enforcement, Stigg effectively governs all aspects of AI usage, including credits, spending limits, and dollar valuation.
Benefits of using Stigg include: real-time control over AI functions, streamlined operations by treating each AI request as a spend decision, easy integration with existing systems, user-codebase independence, and precise real-time enforcement. It also ensures complete ownership of subscription and usage data, protecting the privacy and integrity of data.
Stigg ensures that all transactions are captured and aggregated by offering real-time metering at an extremely high event-per-second rate. It accurately records every transaction, allowing organizations to meticulously track AI feature use and associated expenditures.
Stigg's rapid AI deployment feature is facilitated by the fact that its entitlement logic resides outside of the user's codebase. This means that new models, features, or tiers can be implemented rapidly without having to make major changes to the basic framework of the user's system.
Stigg provides real-time control over every credit, limit, and dollar associated with AI usage. From entitlements to spending caps, every aspect of AI management and financial control is made immediate and accurate, facilitating improved efficiency and reduced wastage of resources.
Pricing
Pricing model
Freemium
Paid options from
$331/month
Billing frequency
Monthly
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