Welcome to SeekFiles AI

Most "chat with your files" tools you can try today are doing the same trick: they take a file, throw it at a language model in one big chunk, and let the model figure out the answer. It works for a five-page PDF. It does not work for the messy, real-world stack of contracts, receipts, scanned manuals, and meeting notes that an actual person — or an actual team — accumulates.

We built SeekFiles AI because we wanted something different.

Retrieval first, generation second

The "RAG" in retrieval-augmented generation is doing the heavy lifting. We treat retrieval as a first-class problem:

• Every file is chunked with overlap, not blindly stuffed into a prompt.
• Every chunk is embedded into a vector index and indexed for keyword search. Queries fan out to both, and we fuse the results with reciprocal rank fusion.
• For scanned PDFs and image-only documents, a vision pipeline OCRs and captions each page so they're searchable too.
• An optional cross-encoder reranker can sit on top for production-grade precision.

The model only ever sees the chunks that survived this process — and it's strongly instructed to refuse rather than hallucinate when grounding is weak.

Citations are not optional

If an answer can't be traced back to a specific chunk in your file, it shouldn't be on the screen. Every assistant message carries citation chips that link to the source — file, page, paragraph. You get the answer and the receipt.

Cross-lingual out of the box

Cross-lingual retrieval is a day-one capability. Ask in one language and retrieve from source files written in another. It just works — no extra configuration, no per-language deployments.

Mobile and web

The mobile app (iOS + Android) is built for capture-and-ask: scan a contract, ask a question, get an answer with citations — all without leaving your phone. The web dashboard is for heavy lifting: managing assistants, inspecting usage, sharing public assistants.

What's next

We're planning posts on:

• How hybrid retrieval (vector + BM25) outperforms either alone.
• The economics of credit-based pricing versus seat-based SaaS.
• Building public assistants and embedding them on websites.
• Inside the vision pipeline: from PDF page to searchable text.

In the meantime — the fastest way to know if this fits your workflow is to try it free.