Most of your AI token spend is repetition.

Every long-running session with Claude Code or Copilot re-sends its accumulated history with each turn. Every fresh session pays again to rebuild understanding the last one already had — the architecture, the constraints, the decisions and their reasons. You're not billed for new thinking. You're billed for saying the same things to the same model, over and over.

Context stuffing is the expensive answer

The industry's default fix is a bigger context window: stuff more history in, pay for more tokens, and accept degraded attention as the window fills. It treats memory as a transcript to replay. Transcripts grow without limit; your bill grows with them — and everything still dies at session end.

Constructed recall is the cheap one

Juvina takes the other road. A local memory engine encodes what matters as it happens — decisions, reasoning, project history — into a database on your machine. When a session needs the past, it asks a question and gets back a compact constructed answer: a few hundred to ~a thousand tokens, however long the history behind it is. The recall cost stays flat while the transcript it replaces keeps growing. That gap is your saving, and it widens every week you use it.

Measure your own bill first — free, ten seconds

Don't take our word for how much repetition costs you. If you use Claude Code, run this in any terminal:

npx github:1picassoai/juvina-token-bill

It reads only your own local logs, makes no network calls, and opens a report card showing what share of your usage was re-sent history — and what that would cost at API rates. Free, open source, method printed on the card.

See the number, don't take the claim

The live demo prints a token receipt under every answer — what the constructed recall actually cost versus re-sending the history it stands in for. The extension shows the same running meter on your own projects. Measure it on your bill, not our word.

And it stays inside your walls

The engine, the database, and your memories are stored entirely on your machine; model calls go to your own endpoint on your own key. Point it at your company's Azure tenant and nothing crosses your own walls. No hosted service, no telemetry to us, nothing to trust but your own disk.