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Answers grounded in your own documents

Gezora builds retrieval systems that ground AI answers in your own documents and data, so a response cites a real source in your business instead of guessing from general training.

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Inside a retrieval system

  • Document ingestion
  • Access control sync
  • Passage splitting
  • Format coverage
  • Semantic search
  • Keyword search

What a retrieval system includes

  • Document ingestion and indexing
  • Hybrid retrieval tuned to you
  • Citations and permission control
  • Evaluation and scheduled refresh

Why the answers hold up

  • Answers you can check

    Every response points to the source passage it came from, so your team can verify it.

  • Permissions still apply

    Retrieval applies the permissions already on your documents, so people only see what they can access.

  • Your content, not guesses

    Responses come from your contracts, policies, and product documentation rather than general training data.

  • Content that stays current

    The index refreshes on a schedule, so answers follow your content as it changes.

Inside a retrieval system

  • Document ingestion
  • Access control sync
  • Passage splitting
  • Format coverage
  • Semantic search
  • Keyword search
  • Hybrid retrieval
  • Relevance tuning
  • Answer evaluation
  • Source citations
  • Permission aware retrieval
  • Index refresh

What a retrieval system includes

Each build is shaped around where your documents already live and what your people keep asking. These are the pieces that make up the work.

  • Document ingestion and indexing

    We connect the systems that already hold your documents and bring the content in as it is. It is split so each retrieved passage still carries its meaning, then indexed across the formats you actually store, including PDFs, spreadsheets, and internal pages.

  • Hybrid retrieval tuned to you

    Keyword and semantic retrieval run together, so an exact term and a loosely worded question both find the right passage. Retrieval is then tuned against the questions your people really ask, not a generic benchmark.

  • Citations and permission control

    Each response carries a citation back to the passage it came from, so a reader can open the source and check it. Retrieval also applies the permissions already set on those documents, so nobody sees a passage they should not.

  • Evaluation and scheduled refresh

    Answers are evaluated against the questions that matter to you rather than assumed to be good, so gaps surface before your people run into them. The index refreshes on a schedule, so answers follow your current content and not a snapshot taken at launch.

How the system gets built

The work starts with your documents and the questions people keep asking, and ends with a system your team can check for itself.

  1. 01

    Step 1, Scoping

    We map where your documents live and what your people keep asking before anything is built.

  2. 02

    Step 2, Ingestion

    Content is pulled from the systems that hold it, split into passages, and indexed across your formats.

  3. 03

    Step 3, Retrieval tuning

    Hybrid retrieval is tuned against your real questions until the right passage comes back consistently.

  4. 04

    Step 4, Evaluation

    Answers are scored against an agreed set of questions, and citations are checked against the source.

  5. 05

    Step 5, Launch and refresh

    The system goes live with permissions enforced and the index set to refresh on a schedule.

Where the answer already exists

The pattern is always the same: the answer already exists in a document, and finding it takes longer than acting on it.

  • Support teams working from a policy library

    Today an agent reads across policy pages and product notes to confirm a single answer, and different agents land on different wording for the same question. Retrieval returns the passage the answer came from, so the agent checks a source instead of hunting for it.

  • Legal and contract teams fielding the same questions

    Today questions about terms and obligations keep coming back to the few people who know where each agreement sits. Retrieval answers from those contracts and cites the passage, so a reader can open the source and confirm it without joining that queue.

  • Companies with documents spread across systems

    Today the content sits across shared drives, internal pages, and file formats nobody wants to search, and it is hard to tell which copy is current. Ingestion brings those sources into one index that refreshes on a schedule, so an answer follows the document as it changes.

  • Teams where document access differs by role

    Today a shared assistant is a risk, because not everyone should see every contract or policy it could reach. Retrieval applies the permissions already set on your documents, so a person only gets passages they were already allowed to open.

What ships with the system

An engagement ends with a working system and the material your team needs to run it and extend it.

  • A running retrieval system with source citations
  • Connectors to each source agreed in scoping
  • The agreed evaluation question set and its scores
  • A permission map for every connected source
  • A documented index refresh schedule
  • A runbook for adding a new source

The index sits in your environment, and support continues as your content and your questions change.

FAQ about RAG Systems

Straight answers on scope, timelines, and what running RAG Systems asks of your team.

Other work that pairs with this

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Stop paying people to do what an agent can

Tell us what you want to automate. We will map the workflow, deploy the right agents, and train your team to run them.

  • Every agent is trained on your own workflows, never a generic template
  • Most deployments are live within two to four weeks
  • SOC 2 compliant, with a complete audit trail on every deployment
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