Identify runaway LLM costs and prevent low-quality AI outputs

Identify runaway LLM costs and prevent low-quality AI outputs targets a $6.0B = 4,000,000 potential businesses running LLM features × $1,500 ACV total addressable market with medium saturation and a year-over-year growth rate of 40% YoY (LLM/AI infra and API spend growth estimated by industry analysts and cloud providers, 2023-2025).

Key trends driving demand: LLM adoption by product teams — more apps are embedding generation which converts provider fees from experimental to recurring operational spend, creating demand for cost tooling.; Provider proliferation and pricing divergence — multiple model providers and pricing options make cross-provider cost/quality tradeoffs complex and valuable to optimize.; Rise of ML observability — teams expect tracing, evaluation, and drift detection similar to model ops for supervised models, enabling prompt/output diffing and regression alerts.; Automation-first operations — teams prefer automated remediation (policy enforcement, model switch) to manual investigation to reduce toil and save money..