Avoid vendor lock-in: run AI assistant tooling on any LLM model

Avoid vendor lock-in: run AI assistant tooling on any LLM model targets a $32.0B = 25M professional developers x $1,280 avg annual spend on AI dev tooling/infra total addressable market with medium saturation and a year-over-year growth rate of 35-45% (LLM infra, model ops, and AI dev tooling growth).

Key trends driving demand: Open models proliferating -- Llama/Mistral/GRO/others reduce dependence on one API and enable on‑prem deployments.; Composable AI stacks -- developers expect pick‑and‑mix model, embedding, and vector store components.; Cost sensitivity -- token and inference costs drive teams to multi‑provider routing and local inference.; Enterprise privacy & data sovereignty -- pushes on‑prem or private cloud execution and auditability.; Tooling standardization -- demand for unified observability, prompt/agent templates and deployment patterns..