Everyday bakes your documents into a compact cartridge inside an open LLM. Grounded answers from your own data — at a fraction of RAG's cost, flat as your corpus grows.
Runs in your cloud. Your data never trains a shared model.
Cost per question
See the math →Connects to the sources you already use
Incremental sync keeps your corpus fresh as documents change.
One-time training, then a flat per-query price ~16× below RAG. Break-even in days.
Answers come from your documents, with sources — matching RAG's grounding head-to-head.
Large corpora shard into many cartridges; we retrieve the right few per query.
How it works
SharePoint, Confluence, Drive, S3, or upload.
Distil your docs into cartridges, once.
Semantic search picks the right cartridges.
The open model answers, grounded and cheap.
We'll run a demo on your own corpus and show you the numbers.
No spam. We'll reach out to schedule.
