less poo. better search.

We build custom search and RAG systems for teams whose corpus is worth searching well. Internal docs, codebases, support archives, niche public domains. The result is search that returns what you wanted, not what was loud, with a curated source list, an evaluation harness your team will actually keep using, and ranking you can debug when it's wrong.

grep "the question your team keeps asking"
off-the-shelf  : 18 results, 14 are AI-generated rephrases of each other
us             : 3 results, all from the docs that actually answer it
explain why result #1 ranked first
off-the-shelf  : "the model decided"
us             : signal/feature/source on every chunk; reproducible; fixable
add a new corpus on monday
off-the-shelf  : re-train, re-tune, hope
us             : index, audit, ship; same eval harness keeps you honest

$ talk to us

curate. we read the corpus before we index it. wrong, stale, AI-slop sources come out. provenance stays in. the top result is from a source you'd cite.
evaluate. a question/answer harness your team actually runs — not a one-time benchmark that goes stale by month two. regressions surface on the way in, not after a customer notices.
explain. when a result is wrong, we can tell you why and fix it. signal/feature/source on every chunk. no black box, no “the model decided.”
own it. the index, the eval, the ranking, the runbooks all land in your repo. nothing for us to revoke when the engagement ends.