LLM Cost Watchdogv1.0.0

A customer support platform uses multiple LLM providers to handle queries. Cost Watchdog tracks spend live, detects runaway loops where an agent repeatedly calls the API, and enforces budget ceilings to prevent unexpected overages.

A marketing agency runs batch content generation using LLMs. Cost Watchdog audits code for unbounded loops and enforces daily budgets, ensuring that batch jobs don't exceed allocated spend and alerting when budgets are near limits.

A DevOps team uses LLMs for automated incident response and code generation. Cost Watchdog provides live cost per call, identifies the cheapest model alternatives, and prevents cost spikes from recursive workflows.

A data science team validates LLM token counts for training data pipelines. Cost Watchdog compares heuristic token counts with provider authoritative counts using the validate-tokens command, ensuring accurate billing and data quality.

A fintech company integrates LLMs for transaction analysis. Cost Watchdog performs AST-based code audits to identify missing cost controls, such as unbounded loops or missing max_tokens, ensuring compliance with internal financial policies.

Offer Cost Watchdog as an add-on to existing LLM-based SaaS platforms. It provides real-time cost tracking and budget enforcement, reducing customer churn due to unexpected bills.

Provide a consulting service that sets up Cost Watchdog for enterprise clients, including custom budget thresholds, alerts, and periodic reports. This helps enterprises control AI spend without internal expertise.

Release Cost Watchdog as open source to build community adoption, then offer premium support, custom integrations, and advanced reporting for enterprises.