Your Knowledge,
Answerable.
We build retrieval-augmented generation systems that turn your documents, tickets, and wikis into an assistant that answers from your truth, with citations, not guesses.
A Model That Guesses Is A Liability.
A general model has never read your policies, your tickets, or last week's decision. Ask it anyway and it will answer confidently, and sometimes wrongly. RAG fixes that by retrieving the truth before it speaks.
Refunds are typically processed within 30 days, though it can vary by retailer.
Your refund window is 5 business days from delivery [1], with a 14-day window for enterprise accounts [2].
Two Lanes, One Vector Store.
RAG has an offline side that prepares your knowledge and an online side that answers in real time. Both meet at the vector store.
Ingest
Connect and load your sources
Chunk
Split into meaningful passages
Embed
Encode chunks as vectors
Retrieve
Find the closest passages
Rerank
Order by true relevance
Generate
Answer, grounded and cited
Search By Meaning, Not Keywords.
We turn every passage into a vector, a point in a space where similar ideas sit close together. A question becomes a point too, and retrieval is simply finding its nearest neighbors. Done well, it is the difference between a useful answer and a wrong one.
Semantic, Not Literal
Retrieval matches meaning, so a question phrased nothing like the source still finds it.
Hybrid Search
We blend vector similarity with keyword and metadata filters for precision and recall.
Reranking
A second pass reorders candidates so the best passages, not just the closest, reach the model.
Assistants That Know Your Stuff.
Internal Knowledge Assistant
One place to ask anything your company already knows, answered with sources.
Customer Support Copilot
Draft accurate, cited replies from your support knowledge in seconds.
Document Q&A
Ask questions across long, dense documents and get answers with page references.
Research & Analyst Copilot
Synthesize across many sources with traceable evidence for every claim.
Policy & Compliance Assistant
Answer policy questions exactly as written, with the clause it came from.
Product & Sales Enablement
Put your latest positioning and answers at every rep's fingertips.
Every Source, One Index.
Your knowledge is scattered across a dozen tools. We connect them, keep them in sync, and unify them into a single searchable index, with permissions respected.
NotionSlackGoogle DriveConfluenceSalesforceDropboxGitHubJiraZendeskSharePointWebsitesPDFs & docsAnatomy Of A Trusted Answer.
A good RAG answer is more than text. We measure and engineer the signals that make it trustworthy, then test them continuously against your real questions.
Enterprise accounts have a 14-day refund window from delivery [1], extended from the standard 5 days [2].
Grounded Span
Every sentence traces to retrieved text, so nothing is invented.
Inline Citations
Sources are linked at the claim level, not just listed at the end.
Confidence & Abstention
Low-evidence questions get a careful answer or an honest I do not know.
Freshness
Re-indexing keeps answers current as your sources change.
Frequently Asked Questions.
No. Retrieval reads your data at query time to ground an answer. It is not used to train the underlying model, and you control where it lives.
Make Your Knowledge Ask-Anything Ready.
Point us at your documents and the questions your teams keep asking. We'll build a grounded, cited RAG assistant on your knowledge, and prove it on your real queries.