Your documents answered.Precise responses.Sources always cited.

RAGAI plugs AI into your documents, PDFs, wikis and knowledge bases. Ask in natural language, get precise answers with cited sources.

answer accuracy
95%
response time
<2s
pages indexed
1000+
sources cited
100%

Orders of magnitude the installation aims for; they are measured on your premises during the audit, on your volumes.

RAGAI, Offer illustration
RAGAI. AI agent for document Q&A with RAG
01What the agent does

Fully automated, nothing to manage.

01

Multi-format ingestion

PDF, Word, Markdown, Notion, Confluence, Google Drive, RAGAI indexes every format of your documents automatically.

02

Semantic search

Beyond keywords, the AI understands the meaning of your question and finds the most relevant passages in your corpus.

03

Auto citations

Every answer cites its sources: document, page, paragraph. Zero hallucination, full traceability.

02How it works

Live in days, not months.

  1. 01

    Upload your documents

    Drag and drop your PDFs, connect Google Drive or Notion. RAGAI indexes and vectorizes your corpus in minutes.

  2. 02

    Ask your questions

    Intuitive chat UI. Questions in French or English. The agent scans your entire base and synthesizes the relevant answers.

  3. 03

    Answers with sources

    Every answer comes with source excerpts. Your teams save hours of document hunting every week.

03Under the hood

The pipeline behind this offer.

Sovereign RAGOpen-source, self-hosted, cited answers, 6 stages
Sources
NotionSharePointDrivePDF
Vision-langage OCR
OCR ingestion
Vision-langageOllamaDécoupage
Chunk + embed
Embeddings
EmbeddingsOllama
Hybrid search
Hybrid retrieval
Vector
pgvectorPostgreSQL
Keyword
Postgres FTSBM25
Knowledge graph
Apache AGE
RRF fusion
Fusion + Reranking
RRFReranker
Grounding
Grounded generation
LLM localCitations
04Tools we operate

We plug the agent into the tools you already use.

  • Pinecone
  • OpenAI
  • Anthropic
  • Notion
  • Groq

Nothing to learn: we configure and operate these connections for you.

Why now

The answer already exists. Nobody knows where to find it.

What it costs you today

2:08 PM, Tuesday. A five-year customer calls about a clause in their master contract. The consultant in charge opens Confluence, SharePoint, Notion, the shared drive. She types the query, skims three 80-page reports, opens four PDFs, ends up Slack-ing the colleague who drafted the contract two years ago, who is on leave. She promises a callback by end of day. 11 PM, she's re-reading the same documents at home. The customer already called the competitor. The answer was in the 2023 report, page 47, paragraph 3. Nobody ever found it again.

The facts

The McKinsey Global Institute has documented that knowledge workers spend an average of 1.8 hours per day searching for information in internal documents, 9.3 hours per week, more than a quarter of a work week. IDC estimates that poor document management costs 21.3% of total productivity for a 1,000-person company. And the enterprise RAG market, valued at $1.2B in 2024 by Forrester, will double in 18 months.

Why us

Wikolabs installs AI systems built on open-source models, on your premises, paid once. No black box: your data, your prompts and your history stay in your infrastructure. We quote at a fixed price or on time and materials, never per ticket or per token, and we say before you sign what works and what does not yet.

What we put in place

Concretely: connect Drive, Notion, Confluence or drop your PDFs, RAGAI vectorizes your corpus in minutes, and your teams ask their questions in natural language via chat. Every answer lands in under 2 seconds with a precise citation, document, page, paragraph. 95% accuracy, 0 hallucination thanks to strict RAG, full traceability for your compliance needs. Your consultants reclaim 9 hours per week and stop re-writing what already exists.

Your knowledge base, finally searchable

20-minute demo. First documents indexed in 1 hour. Teams self-serving from day one.