Cut AI inference costs by orchestrating cheap+accurate models for SaaS

Cut AI inference costs by orchestrating cheap+accurate models for SaaS targets a $6.0B = 200,000 AI-enabled product teams × $30K ACV each (includes SMBs and enterprise subscriptions for developer tooling, monitoring, and managed inference) total addressable market with medium saturation and a year-over-year growth rate of 35% YoY — aligned with broader AI developer tools and inference market growth (industry estimates, 2023-2025 trend).

Key trends driving demand: Open-source models are closing the quality gap with proprietary models — this creates an opportunity to substitute expensive inference with cheaper alternatives while preserving quality.; More vendors and pricing tiers for inference create arbitrage opportunities developers can exploit, making orchestration and routing valuable.; Teams are under pressure to show predictable unit economics as usage scales, increasing demand for tooling that converts model calls into predictable cost profiles.; Shift-left developer adoption of LLMs means decision-makers will buy dev-friendly tooling that reduces time to production and reduces ongoing API bills..