Kultivait.ai speaks the same API language your tools already use — OpenAI-compatible and Anthropic-compatible endpoints, both streaming. Swap the endpoint, keep your workflow, and let the router do the economics.
Point any OpenAI- or Anthropic-compatible tool at http://localhost:4114 with model: auto. No retraining, no workflow changes — it speaks the language your tools already use.
A local embedding model (nomic-embed-text, 274 MB) classifies each prompt in milliseconds against four roles — simple, reasoning, docs, architect. Routine work runs on your own hardware; hard problems go to a cloud tier.
Every decision is recorded to a local savings ledger with costs computed against frontier-model baseline pricing. kultivait harvest shows what was routed where and what you saved.
The router's job is simple to state: never spend a premium token on work a free model does well. Here's how a typical workload splits.
You stay in control: routing lives in a plain TOML config (~/.kultivait/config.toml) you can edit freely, and kultivait route "your prompt" dry-runs any classification so you can see exactly what the router would do — and why — before it does it. Every decision lands in the ledger with its classification margin, so you can audit the router's judgment after the fact.
Some prompts deserve a frontier model. When one arrives and no cloud tier is available — or your agent's tool loop keeps the work local — Kultivait.ai serves it with your best local model and archives the full conversation as an escalation.
kultivait escalations --brief then distills it into a paste-ready TASK / CONTEXT / PROGRESS / NEEDED brief using a local model, and names where to take it. Escalating costs one paste instead of re-explaining the whole session — and the distillation itself costs zero cloud tokens.
Would-be escalations are never silently swallowed: each one is flagged in the ledger and surfaced by kultivait harvest.
kultivait prune distills long transcripts at phase boundaries — findings, decisions, constraints, open questions — so the next phase starts light.
Distillation is lossy, so every full transcript is composted to disk first. The compost pile is the escape hatch.
Anything that talks to an OpenAI- or Anthropic-style API today can talk to Kultivait.ai instead. One endpoint change.
An 8–14B model runs comfortably on a modern dev machine. kultivait init surveys what you have: your smallest capable model becomes the simple tier, your largest the reasoning tier.
If claude or gemini CLIs are on your PATH, they become cloud tiers. None installed? Local-only mode is first-class — cloud-worthy prompts are still recognized and packaged as escalation briefs.
Kultivait.ai is free during early access. If you run local models with ollama, you're two minutes from routing.
curl -fsSL https://kultivait.ai/install.sh | sh
Full quickstart, command reference, and agent integration on the developers page.