AI-Powered Enterprise Search: Find Anything Across Company Knowledge
Your people waste hours every week hunting files across drives, email, and wikis. Semantic search surfaces the answer in seconds, with citations, so knowledge workers stop rediscovering what the company already knows.
We build the company-wide AI search layer that cuts rediscovery cost.
Sound Familiar?
These are the exact issues our clients faced before enterprise search:
- Staff hunt the same policy, proposal, or spreadsheet across SharePoint, Drive, email, and wikis every week
- Keyword search fails when people ask in plain language instead of exact file names
- Answers live in Outlook threads and database reports that never appear in the document library
- New joiners ping colleagues for weeks because tribal knowledge is not searchable
- Teams recreate documents that already exist somewhere, then argue which version is current
McKinsey estimates better internal search and knowledge sharing can cut search time by as much as 35%. Every month you wait is another month of paid hours spent hunting files that already exist.
What Semantic Enterprise Search Actually Does
Ask in plain language → AI searches every connected source → cited answer in seconds. No hunting through folders.
Employee Asks a Question
Someone asks in Slack, Teams, or the search portal in everyday language
AI Searches Company Knowledge
Semantic search queries documents, SharePoint, Drive, wikis, email, and selected databases
Cited Answer Surfaces
Top matches return with snippets and links to the original source
Work Continues
Minutes of hunting become seconds of document discovery, every day
Everything You Need for Reliable Knowledge Management Search
Company-Wide Source Index
We connect SharePoint, Google Drive, Confluence, Notion, Outlook and Gmail mailboxes, file shares, and selected databases into one semantic enterprise search layer.
Semantic Query Understanding
AI search matches meaning, not just keywords. Vague questions like "last board pack on Capex" still surface the right document.
Answers With Source Citations
Every result links back to the original file, wiki page, email, or record so knowledge workers can verify and open the source in one click.
Permissions-Aware Retrieval
Results respect existing access controls. HR packs, finance folders, and restricted mailboxes stay invisible to people who should not see them.
Desktop, Slack & Teams Access
Deliver enterprise search in a portal, Slack, or Microsoft Teams so employees ask where they already work, without hopping between five apps.
Freshness & Coverage Signals
Failed queries and stale hits show knowledge leads which topics need better documents, cutting rediscovery cost over time.
Sources We've Connected for Document Discovery
From Hours of Hunting to Seconds With Citations
How a 95-person Johannesburg professional services firm cut rediscovery time by roughly 35% and recovered 5,800+ staff hours in year one.
The Manual Hunt
- Forty knowledge workers jumped between SharePoint, Google Drive, Outlook, and Confluence for every brief
- Average search and gathering time sat near McKinsey's 1.8 hours per person per day
- Keyword search needed exact titles; vague questions returned noise or nothing
- Teams often needed up to eight searches to land on the right document
- Managers recreated proposals and packs because nobody could prove the latest version existed
The Semantic Search Layer
- One AI enterprise search box across documents, Drive, SharePoint, wiki, and mail
- Plain-language questions return ranked answers with source citations
- Permissions preserved: finance and HR packs stay invisible to the wrong roles
- Search time fell by about 35%, in line with McKinsey's upper estimate for better internal search
- New joiners stop pinging seniors for files that already live in the company knowledge base
Before vs After AI Enterprise Search
How It Works
From first conversation to live enterprise search in 4–8 weeks.
Tell Us Your Setup
Which drives, wikis, mailboxes, and databases hold the knowledge people cannot find, and which roles waste the most time hunting.
Free Scoping Call
30-minute call with your COO, Head of Knowledge, or Internal Ops lead to map sources, permissions, and success metrics.
Build & Test
We index approved sources, tune ranking on real failed searches, enforce permissions, and run a parallel week against keyword search.
Go Live & Monitor
Roll out semantic AI search company-wide. We monitor citation quality, time-to-answer, and hours recovered.
Frequently Asked Questions
How is enterprise search different from helpdesk knowledge base search?
Helpdesk KB search helps support agents find approved articles. AI-powered enterprise search indexes the whole company knowledge graph: documents, SharePoint and Drive libraries, wikis, email, and selected databases, so every knowledge worker finds answers, not only the support desk.
Which sources can you include in semantic enterprise search?
We commonly index SharePoint, Google Drive, OneDrive, Confluence, Notion, Outlook and Gmail, network file shares, and selected SQL or reporting databases. If a source is reachable with proper authentication, we can include it in document discovery.
Will this replace SharePoint or Drive search?
No. Built-in keyword search stays useful when someone knows the exact title. Semantic enterprise search sits alongside it for the vague, cross-system questions that waste hours. Most organisations keep both and default to AI search for day-to-day hunting.
How do you handle permissions and confidential content?
Retrieval respects source permissions. Users only see documents, emails, and records they are already allowed to open. Private HR, legal, and finance material stays out of open results.
How long does an AI enterprise search project take?
Most builds take 4–8 weeks from scoping to go-live: source access, indexing, ranking on real queries, permission checks, and a parallel test week. Narrow pilots over Drive and SharePoint alone can be live in about three to four weeks.
How much does AI-powered enterprise search cost?
Pilots start from around R45,000. Production semantic search across documents, mail, wikis, and selected databases typically ranges from R70,000 to R140,000. Teams of 40+ knowledge workers usually recover the project cost within 2–3 months from rediscovery time alone.
Stop Paying Staff to Hunt for Files
If your people still spend a fifth of the week searching for company knowledge, you are funding a problem semantic enterprise search already solves.
Tell us which drives, wikis, mailboxes, and databases hold the answers, and which roles burn the most time hunting. We will show you how AI-powered enterprise search would work for your organisation.