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Turn PDFs, contracts, manuals, and websites into a searchable, cited Q&A interface.
Features
5
Tech
14
Steps
5
Document AI & RAG Knowledge Base
Capabilities
Every capability is shipped end-to-end — not a feature flag. You get a working slice on day one and we expand from there.
Feature 01
PDFs, DOCX, PPTX, websites, audio transcripts, images.
Feature 02
Every reply links to the exact source paragraph.
Feature 03
Per-document permissions, audit log of every query.
Feature 04
Re-ingests on change, knows which version is current.
Feature 05
Pulls fields from invoices, contracts, forms into JSON.
Stack
Production-tested tools chosen for reliability, observability, and developer velocity. Every piece is swappable.
System at a glance
A simplified view of what comes in, what the agent does with it, and what it produces. Each arrow is observable end-to-end.
Inputs
Agent
Document AI & RAG Knowledge Base
Plan → tool-call → reflect, with approval gates.
Tools the agent calls
Outputs
Engagement
A 5-step process from kickoff to handover. Every step has a deliverable you can sign off on.
Audit which docs to index and who can see them.
Parse → chunk → embed → store, with versioning.
Web app or Slack bot with citation rendering.
SSO, per-doc ACLs, full query log.
Webhook-driven re-indexing as content changes.
Outcomes
Real numbers we see when Document AI & RAG Knowledge Base ships on top of an actual workflow. Specifics vary with starting baseline, data quality, and scope — but these are the ranges.
Outcome 01
−85%
Lookup time
From minutes searching to seconds answering with citation.
Outcome 02
92-97%
Answer accuracy
Against ground-truth Q&A set, tuned over 6-8 weeks.
Outcome 03
10K+ docs
Source coverage
Per workspace, with permissioning and version awareness.
Sample use cases
Three concrete scenarios where teams deploy Document AI & RAG Knowledge Base today. Your engagement starts with one of these (or your own variant) and expands from there.
Engineers ask the bot anything about the codebase, runbooks, or product — answers cite the exact doc + line. Ramp time drops from 3 weeks to under 1.
A counsel team uploads 200+ contracts. The agent surfaces non-standard clauses, missing indemnities, expiry windows — saves 60+ hours per quarter.
HR + Finance answer 'can I do X?' questions from the workforce automatically, with permission-aware retrieval — sensitive policies stay private.
Typical engagement
Most Document AI & RAG Knowledge Base engagements follow this shape. We give you a firm quote after a 30-minute scoping call, and the price is fixed up-front so you can budget.
2-3 weeks
2-4 weeks
Ongoing
Indicative range
$2,000 — $5,500
Full project, scoped + fixed up-front. Includes pilot, production, and 30 days of post-launch support.
Or hire us by the week
from $750/wk
Embedded retainer — best for evolving scopes.
Also in Knowledge & Research
Often deployed alongside — or instead of — Document AI & RAG Knowledge Base.
Slack/Teams bot that answers staff questions from Notion, Confluence, Drive, and SharePoint.
View detailsRuns structured interviews or synthesises transcripts into themes, quotes, and product opportunities.
View detailsCase law search, contract summarisation, clause-by-clause risk flagging for law firms and counsel.
View detailsReads incoming RFPs, drafts answers from your past wins and knowledge base, scores risk per question.
View detailsTell us about your data, your tools, and what success looks like. We come back within one business day with a clear plan, price, and timeline.