Token prices are visible; total cost of ownership is not. Most LLM spend in India sits in discovery, integrations, evaluation, hosting choices, and the people who keep the system current.
Scope the workflow first. A single high-value process with clear KPIs costs less to prove than a vague “chat with all our data” mandate that expands every month.
Budget for eval harnesses, monitoring, and prompt or index updates. Without them, drift quietly erodes quality and forces expensive fire drills.
Compare India residency options and private deployments against public APIs on risk and run cost — not only on latency benchmarks.
Digicane prices engagements around build, integrate, and run so finance and IT see a full TCO picture before they commit.
Ask vendors for a 12-month run forecast: model usage, vector store, observability, and support hours. That forecast is the real buying artifact.