Knowledge That Finds You
Your team has solved this problem before. The fix is documented somewhere — in a wiki page nobody can find, an email thread from 2023, or a Slack message buried in a channel. TechManager AI's knowledge base uses semantic vector search to surface the right answer instantly, even when people don't know the right terms to search for.
Why Traditional Knowledge Bases Fail
You've tried wikis, shared drives, and Confluence. They all have the same problem: people write documentation once and nobody can find it when they need it.
Keyword Search Fails
A nurse types "computer is frozen" into the wiki search bar. She gets zero results because the article is titled "Application Not Responding (ANR) Troubleshooting." Keyword search only works when you already know the terminology — which is exactly when you don't need a knowledge base.
Content Goes Stale
That VPN setup guide was written two years ago for the old system. The passwords in the printer configuration article were changed last month. Without version tracking and review cycles, knowledge bases become a graveyard of outdated procedures that mislead more than they help.
No Quality Control
Anyone can publish anything. An intern writes a troubleshooting guide with the wrong steps. A well-meaning employee copies a procedure from the internet that doesn't match your environment. Without approval workflows, your knowledge base accumulates bad information alongside good.
No Usage Insights
Which articles are actually useful? Which ones are people searching for but not finding? Where are the gaps? Traditional wikis don't tell you. You end up writing articles nobody reads while users search for topics you haven't covered.
Siloed Knowledge
Multi-site organizations end up with a different knowledge base at each location. The Phoenix office solved the printer issue last week, but the Austin office doesn't know about it. Without centralized, searchable knowledge, every office reinvents the wheel.
Semantic Search: Find Answers, Not Keywords
Powered by vector embeddings, not keyword matching. The search understands what you mean, not just what you typed.
How It Works
Every article in your knowledge base is converted into a vector embedding — a mathematical representation of its meaning. When someone searches, their query is also converted to a vector, and the system finds articles with the closest semantic meaning. "My computer is frozen" matches "Application Not Responding" because the AI understands they describe the same problem.
This isn't just fuzzy matching or synonym lookup. The AI understands context, intent, and technical relationships. "Can't connect to the printer" finds articles about network printing, driver issues, and print spooler troubleshooting — even if those exact words never appear in the search query.
- Understands synonyms, abbreviations, and technical terms
- Relevance scoring with confidence percentages
- Sub-second search across thousands of articles
- Results cached with Redis/Valkey for repeat queries
Search: "wifi keeps dropping"
AI maps to: network connectivity, wireless, intermittent
1. Wireless Network Troubleshooting Guide
v4.1 • Updated 3 days ago • 96% relevance • 127 views
2. Office Wi-Fi Access Point Configuration
v2.3 • Updated 1 week ago • 91% relevance • 89 views
3. VPN Connectivity Issues (Remote Workers)
v3.0 • Updated 2 weeks ago • 84% relevance • 203 views
AI also searched: 14 resolved tickets with similar symptoms
Content Management That Keeps Knowledge Fresh
Write it once, keep it current forever. Version control, approval workflows, and usage analytics ensure your knowledge base improves over time.
Version Control
Every edit creates a new version. See what changed, who changed it, and when. Roll back to any previous version with one click. No more wondering which copy is current.
Approval Workflows
New articles and major edits go through review before publishing. Subject matter experts verify accuracy. Approved content gets a trust badge. No more unvetted procedures in your KB.
Collections & Categories
Organize articles into collections (Hardware, Software, Network, Compliance) and categories within each. Users can browse by topic or search across everything.
Bookmarks & Votes
Users bookmark articles they reference frequently. Upvotes surface the most helpful content. Downvotes flag articles that need updating. Community curation without the overhead.
Bulk Import
Migrating from Confluence, SharePoint, or Google Docs? Bulk import your existing documentation. Articles are automatically embedded for semantic search on import.
File Attachments
Attach screenshots, PDFs, configuration files, and videos to articles. Everything is stored securely in Google Cloud Storage and accessible through the article.
Know What Your Team Needs
Usage analytics show you what's working, what's missing, and where to focus your documentation efforts.
Article Performance
See which articles are viewed most, which have the highest helpfulness ratings, and which are linked to the most ticket resolutions. Identify your best content and replicate its structure. Spot articles with high traffic but low ratings — they probably need updating. Track trends over time to see if your documentation quality is improving.
- View counts, helpfulness ratings, and ticket resolution links
- Stale content detection — articles not updated in 90+ days
- Trending topics and seasonal patterns
Gap Analysis
The most valuable feature: see what people are searching for but not finding. When someone searches "VPN setup for Mac" and gets zero results, that's a gap. When tickets pile up for a topic with no KB article, that's a gap. The analytics dashboard surfaces these gaps so you can prioritize what to write next based on actual user demand, not guesswork.
- Zero-result searches ranked by frequency
- Ticket topics without corresponding KB articles
- Suggested article topics based on search patterns
Enterprise Knowledge Sharing
Multi-site organizations need knowledge that flows across locations. Enterprise plans include global KB sharing.
Share articles across all sites in your organization. Phoenix solves it, Austin benefits.
Global procedures with site-specific variations. Each location keeps its unique quirks documented.
Control who can read, write, approve, and publish. Sensitive procedures restricted to authorized staff.
Full API access for custom integrations. Pull KB data into your tools or push external docs in.
The AI Feedback Loop
The knowledge base doesn't just serve information — it learns from every interaction and improves automatically.
Ticket Resolution
AI resolves a ticket using a KB article. The article's effectiveness score increases. Resolution steps are logged.
Knowledge Capture
When AI escalates and a human solves it, the resolution is captured as a new KB article draft. Knowledge grows from every interaction.
Continuous Improvement
Search patterns identify gaps. Usage analytics prioritize updates. The knowledge base gets smarter and more complete over time — automatically.
Turn Your Team's Knowledge Into a Competitive Advantage
Book a demo and see how semantic search, version control, and usage analytics transform your IT documentation.