Connect enterprise knowledge
Turn information scattered across documents, spreadsheets, and systems into a knowledge layer AI can retrieve, understand, and cite.
PDF+Sheets+Wiki
Enterprise AI that actually works
A free 30-day path from RAG to Agentic Workflow — enterprise AI that reliably gets work done.
30days, full path
6maturity stages
3+enterprise data sources
PRODUCT THINKINGEnterprise AI's value isn't
Enterprise AI's value isn't
just the model itself
An AI product that actually ships needs to handle knowledge, computation, tools, decisions, and control together. Data Machi puts these capabilities on one system map.
Separate out the decision logic
Let code own computation and rules, let the model own understanding intent and language — cutting down hallucination and bad calls.
Intent→Rule→Verify
Push real work forward
Move from finding information to calling tools, updating tasks, and completing workflows — making AI a real collaborator.
Read Decide Act
MATURITY MODELFrom a chat interface
From a chat interface
to an enterprise-grade AI product
Every capability upgrade means the system needs a different data architecture, tool permissions, decision control, and reliability design.
Read the full framework01
ChatUnderstand the question
L102
RAGFind the knowledge
L203
Tool UseFetch live data
L304
AgentJudge autonomously
L405
WorkflowControl the process
L506
ProductDeliver reliably
L6REAL WORKFLOWS
Designed from real work problems, not model choice
Instead of starting with "which model should we use," we start by breaking down the work, the data sources, the decision steps, and the acceptable risk.
CROSS-SOURCE QUERY
One question, three systems checked at once
Pull exact numbers from a spreadsheet, definitions from a knowledge base, and the latest status from a task board.
MEETING WORKFLOW
From meeting content to action items
Turn a recording, a summary, an owner, and a deadline into a trackable task — not just meeting notes that sit unread.
RELIABLE RAG
Every answer traces back to a source
Keep the retrieval results, data timestamps, and citation locations, so an answer can be verified instead of just trusted.
30-DAY SERIES
View all articles30 days to a complete enterprise AI knowledge map
DAY 01–0501
FOUNDATION
AI and Work
First clarify that what enterprises actually need isn't a chatbot — it's a system that can complete knowledge work.
Read this article →DAY 06–1002
KNOWLEDGE
Enterprise Knowledge Retrieval
From document parsing and RAG to hybrid search — build a traceable enterprise knowledge layer.
Read this article →DAY 11–1503
TOOLS
Tool Integration
Connect Google Sheets, Confluence, Trello, and everyday enterprise systems.
Read this article →DAY 16–2004
AGENT
Agent Decision-Making
Understand how ReAct, coordinators, memory, clarification, and verification work together.
Read this article →DAY 21–2505
WORKFLOW
Controllable Workflows
Use LangGraph, state, and human review to turn black-box decisions into a transparent process.
Read this article →DAY 26–3006
PRODUCT
Enterprise-Grade Product
Fill in the last mile: reliability, Agent UX, security, testing, and deployment.
Read this article →FROM THE BLOG
Industry Notes & Field Notes
How we see the enterprise AI market, platform choices, and the pitfalls we've actually run into — written up on the blog.
Tacit Knowledge Is Your Next Moat: What AI Agents Need You to Keep Isn't Data, It's Judgment
When data is abundant and models are commoditized, real competitive advantage is shifting to the judgment your best people can't put into words. Drawing on new Berkeley research, this piece explains why writing knowledge down isn't the same as making it AI-readable — and why that gap is exactly what RAG-to-Agentic-Workflow is built to close.
Read this article →FAQ
Frequently Asked Questions
If this doesn't answer your question, feel free to email us directly.
Data Machi is a free enterprise AI learning resource built around a 30-day series — from RAG, Tool Use, and Agent to Agentic Workflow, systematically breaking down how to design and reason about enterprise AI. We're not a product or development platform right now.
Yes — it's currently completely free and openly readable, no account or payment required. We haven't launched any paid plan yet.
Those platforms solve "how do you build and run an Agent." Data Machi is trying to fill in the step before that — helping you build the judgment for "why do Agents fail, and which decisions should an AI actually make." Whichever platform you end up using, that judgment still applies.
The 30-day series covers everything from concepts to implementation. Each day explains "why" before getting to "how." An engineering background makes the implementation details easier to follow, but it isn't required.
Feel free to reach out at [email protected] — questions, suggestions, or collaboration ideas are all welcome.
START BUILDINGStart from day one,
Start ReadingStart from day one,
and build enterprise AI
that actually gets work done
30 days, from RAG all the way to Agentic Workflow and productization.