Less context, same Claude Code

Your agent re-sends the whole conversation to the model on every turn, so by mid-session you are paying again and again for text the model has already seen. On our own traffic 67.7% of the bill is re-reading old conversation, and only 0.2% is new text you just typed. condense shortens that history on its way to the model. Helene 1 handles the newest turn, dropping the parts that are not pulling their weight and passing the rest through word for word, fast enough that you will not notice it. Adeline 1 goes back over older work that is already finished and rewrites it to about a tenth of its length. What always survives: your instructions, what you asked for, and the answers you got back. Code, patches and error messages are never touched.

No. condense is built around the cache rather than in spite of it. We split each request into three parts. The oldest part is shortened once, then locked and never touched again, so the provider keeps serving it from cache cheaply for the rest of your session. The middle is the part still settling, which is due to be rewritten anyway. The newest part is this turn's text, which Helene trims before it is ever cached at all. Because the locked part only ever grows at the end, shortening what comes after it cannot spoil what is already cached. Our measured cache hit rate is 98.6%, and the published benchmark prices every run from real provider bills, so a broken cache would show up as a bigger bill rather than hide.

It scales with how long your sessions get, because the saving comes from the history an agent re-sends every turn. Our published live run removed 37.3% of the bill on chains averaging ~179k tokens; sessions peaking past 800k save 66–72%. Dollar-weighted across all our own spend it comes to 66%. Chains under roughly 4k are too short to be worth compressing. The benchmark is public, so you can run it on your own sessions before you pay us anything.

We published a head-to-head against headroom: minmax-bench replays the same real session through both, reads back the real provider bill, and prices both the same way. condense removed 37.3% of the bill against headroom's best mode at 13.8%, close to three times as much. Compared only over the shorter sessions headroom managed, condense is at 28.0%, still about twice their best. The difference is built in: headroom's default setting keeps its cache clean but never touches the piled-up history that is most of the bill, while its more aggressive mode spoils the cache and ends at 1.8%. RTK, caveman and ponytail are not really competitors. They go after the model's replies and tool output, which is a different part of the bill, and they work alongside condense rather than replacing it.

Only the context we remove. If condense strips 4,000 tokens from a request before it leaves for Anthropic or OpenAI, that is 4,000 tokens saved: tokens the provider never saw and never billed you for. Whatever passes through untouched costs you nothing here.

Yes. condense sits in front of your provider and uses your own API key, so the provider still bills you directly, just for far fewer tokens. That is where the saving lands. What you pay us is a flat tier for doing the compacting, never a percentage of your provider bill.

Every tier is a weekly pool of tokens saved. Free gives you 25M a week. Starter is $5/month for 500M, Pro is $20/month for 2.5B, Max is $50/month for 10B. The pool refills every week, and when it is empty your requests keep flowing to your provider uncompressed until it refills. You lose the savings, not the service, and nothing extra is charged. See the full pricing page for team plans and how to size a tier.

Your upstream provider key is never stored. Only a sha256 fingerprint reaches the usage ledger, enough to attribute requests without holding the secret. We never train on your data. Content is deleted on a 7-day window, all storage and processing stays in the EU, and zero data retention is available on request. Read the security page for the full posture.