$ emgram — kb-preparation-for-ai
Your AI automation is only as reliable as your knowledge base.
Most teams fix the agent. Nobody fixes the content.
Emgram is the resource hub for teams preparing their KB for AI agents and RAG pipelines. Tutorials, tools, playbooks, and case studies — all in one place.
📄 140+ tutorials
🛠 12 playbooks
👥 2,400+ teams
71%
of enterprises use AI regularly
"Only 17% see real ROI. The gap is what the model retrieves."
"Only 17% see real ROI. The gap is what the model retrieves."
95%
of AI initiatives deliver zero measurable ROI
"Not a model problem. A content problem."
"Not a model problem. A content problem."
1.8hrs
wasted daily per employee searching for information
"RAG finds it faster. That's not the same as finding the right thing."
"RAG finds it faster. That's not the same as finding the right thing."
34/100
average KB readiness score
"Based on 2,400+ Emgram KB scans. Most teams don't know where they stand."
"Based on 2,400+ Emgram KB scans. Most teams don't know where they stand."
// what you'll find here
Everything you need to prepare your KB for AI
Tutorials
Step-by-step written guides from RAG basics to metadata tagging and chunking strategy.
Free Tools
KB health scanner, metadata template generator, chunking calculator, article readiness checker.
Playbooks
Domain-specific preparation guides for HR, IT, Support, Legal, and Sales knowledge bases.
Case Studies
Before-and-after examples from teams that fixed their KB and made AI automation actually work.
Video Walkthroughs
Screen recordings walking through the full KB preparation process step by step.
Community
Post your KB health score, ask questions, get feedback from peers doing the same work.
// start here
Three tutorials that change how you think about KB and AI
What is RAG and why your KB is the most important part
RAG Basics
· 8 min read
The 6 metadata fields every KB article needs before you connect AI
Metadata
· 12 min read
Smart chunking: why 512 tokens is the sweet spot (and when it isn't)
Chunking
· 10 min read
// the difference it makes
This is what the AI sees. One of these costs you everything.
kb/hr-policies/parental-leave.md
-11,0 +0,0
1
- title: FAQ_v3_FINAL_USE_THIS (2)
2
- owner: [none]
3
- last_updated: 2022-03-14
4
- tags: [none]
5
6
- See above for details. Note: this may be outdated,
7
- check with HR or someone who knows. The policy was
8
- changed at some point last year we think. There are
9
- also some exceptions but they are complicated.
✗ Retrieved by AI — answered confidently — wrong
kb/hr-policies/parental-leave.md
-0,0 +11,0
1
+ title: US Parental Leave Policy — 2026
2
+ owner: sarah.chen@company.com
3
+ effective_date: 2026-01-01
4
+ domain: hr | region: us | type: policy
5
+ review_due: 2026-12-01 | status: active
6
7
+ Eligible employees may take up to 16 weeks of paid
8
+ parental leave within 12 months of a qualifying
9
+ birth, adoption, or foster placement event.
✓ Retrieved by AI — cited correctly — answer trusted
// free tool
Find out where your KB stands in 60 seconds
- ✓Article ownership coverage
- ✓Metadata completeness
- ✓Content freshness
- ✓Title descriptiveness
- ✓Duplicate and gap detection
- ✓Chunk size suitability
Free forever
No login required
Confluence
Notion
SharePoint
// from the community
From teams that fixed the foundation first
MR
Marcus R., Head of IT · logistics-company · 800 employees
"Two ServiceNow pilots failed. 70% of our KB had no owner and hadn't been touched in years. Found Emgram, spent 8 weeks on the foundation, third pilot worked. Should have started here."
commented 3 months ago
JT
Jamie T., Knowledge Manager · saas-startup · 250 employees
"Everyone kept blaming the model. Emgram's chunking tutorial made me realise we were feeding 8,000-word documents into a system designed for 500-token chunks. One afternoon to fix. Changed everything."
commented 2 months ago
PK
Priya K., Director of Operations · healthcare-network · 1,200 employees
"The metadata playbook alone saved six months of trial and error. Our Confluence space needed to be structured differently for AI retrieval than for human browsing. It does. Very much does."
commented 1 month ago