01
Governance
Teams adopt tools faster than leadership can set policies.
ITECS defines approved use cases, data rules, human review paths, and operating ownership before AI spreads.
AI Knowledge Base
Internal AI Knowledge Bases & SOP Automation
ITECS builds private AI knowledge bases for Dallas businesses with 50–500 employees. We connect SharePoint, Google Drive, Notion, and Confluence into one RAG-powered search engine. Employees ask questions in plain English and get cited answers in 5 seconds. Average result: 50% faster onboarding, 70% fewer repeated questions, full setup in 4–6 weeks.
Your company knowledge is trapped in SharePoint folders, Google Drives, Notion pages, and people's heads. New hires take months to get up to speed. Employees ask the same questions over and over. ITECS builds private, RAG-powered AI knowledge bases that connect all your documentation into a single natural-language search interface — like having a secure AI assistant that only knows your company's SOPs, policies, and institutional knowledge, and cites the source document for every answer.
The Stakes
AI adoption fails without governance, security, and operations.
Most organizations do not need another disconnected AI experiment. They need a managed operating model that tells people what is approved, where data can go, which workflows deserve investment, and who owns reliability after launch.
ITECS Position
Managed Intelligence applies ITECS's 24-year managed IT and cybersecurity operating model to AI systems, prompts, agents, connectors, and employee adoption.
02
Security
Sensitive data moves into public prompts, unmanaged plugins, and disconnected workspaces.
ITECS brings managed-IT discipline to access, identity, data handling, and vendor selection.
03
ROI
AI experiments consume subscriptions and meetings without a measurable operating case.
ITECS starts with workflows, cost of delay, and measurable outcomes before recommending build work.
04
Integration
Useful pilots stall when they have to connect with Microsoft 365, CRM, service, or finance systems.
ITECS designs automation around the systems, permissions, approvals, and support model already in place.
19.8%of the average work week spent searching for internal information
Your Company Knowledge Is Trapped in a Thousand Different Places
Your team's institutional knowledge lives in SharePoint folders nobody can navigate, Google Drives with 6 levels of nesting, Notion pages that went stale 8 months ago, and the heads of 3 people who have been here since 2015. New hires spend their first month interrupting everyone with questions that are documented somewhere — if only they could find it.
Every unanswered question costs time twice: once for the employee searching, once for the colleague who stops real work to answer. When those senior employees leave, the knowledge walks out the door. The longer you wait, the wider the gap between what your company knows and what your team can access.
Real-World Example
A 120-person professional services firm in Dallas: spent an average of 45 minutes per new hire per day during their first month helping them locate SOPs, client procedures, and internal policies across SharePoint, Google Drive, and a legacy wiki. Senior staff fielded 40+ knowledge questions per day — most of which were already documented but buried 4 folders deep. The managing partner estimated 6 hours per week of billable time lost to internal information retrieval.
Result: ITECS built a private AI knowledge base connecting their SharePoint, Google Drive, and Confluence. New hires reached full productivity in 1 week instead of 4. The system handles 600+ employee queries per week with cited answers. The firm recovered 25+ hours of billable time per week across the team.
Capabilities
AI Knowledge Base Capabilities
Natural-language search across all company documents, SOPs, and wikis
Connects to SharePoint, Google Drive, Notion, Confluence, and file servers via API
Cited answers — every response links to the source document and paragraph
Confidence scoring rejects low-certainty answers instead of hallucinating
Role-based access control so departments only see authorized knowledge
Auto-sync indexes new and updated documents without manual re-ingestion
How to build an AI knowledge base for your company
- 1
Audit your documentation landscape and identify knowledge gaps
We map where your company knowledge lives — SharePoint, Google Drive, Notion, Confluence, wikis, file servers, and undocumented tribal knowledge. We interview department leads to identify the 20 most frequently asked questions and the biggest onboarding bottlenecks.
- 2
Ingest, chunk, and embed your documents into a private vector database
We connect to your data sources via read-only API, split documents into semantic chunks, and generate vector embeddings stored in a private database on your infrastructure. No data leaves your environment. Role-based permissions mirror your existing access controls.
- 3
Build the RAG pipeline with confidence scoring and citation logic
We configure the retrieval-augmented generation pipeline — query parsing, semantic search, re-ranking, and answer synthesis via OpenAI API or Azure OpenAI. Every answer includes source citations. Confidence scoring rejects uncertain responses instead of hallucinating.
- 4
Deploy to Slack, Teams, or intranet and train your team
We launch the AI knowledge base where your team already works — Slack, Microsoft Teams, or a branded intranet portal. We run hands-on training sessions and configure auto-sync so new documents are indexed within minutes of being saved.
RAG Pipeline
From Scattered Documents to Cited Answers in 5 Seconds
Ingest Sources
SharePoint, Drive, Notion, Confluence
Chunk & Embed
Semantic splitting, vector embeddings
Vector Store
Private Pinecone or pgvector DB
Employee Query
Plain-English question via Slack or Teams
Retrieve & Rank
Semantic search, re-ranking, filtering
Cited Answer
AI response with source links
Ingest Sources
SharePoint, Drive, Notion, Confluence
Chunk & Embed
Semantic splitting, vector embeddings
Vector Store
Private Pinecone or pgvector DB
Employee Query
Plain-English question via Slack or Teams
Retrieve & Rank
Semantic search, re-ranking, filtering
Cited Answer
AI response with source links
Platforms We Connect to Your Knowledge Base
- Microsoft SharePoint
- Google Drive
- Notion
- Confluence
- Slack
- Microsoft Teams
- OpenAI API
- Azure OpenAI
- Pinecone
- Microsoft 365
Security
Enterprise-Grade Security for Business Data
Your knowledge base contains SOPs, client data, HR policies, and proprietary processes. ITECS AI is backed by ITECS — a Dallas cybersecurity MSP since 2002. Document repositories sit alongside the productivity stack our Microsoft 365 specialists already secure for Dallas businesses every day.
Private deployment — your knowledge base runs on your infrastructure or private cloud, never on public servers. Your data never trains third-party models.
Role-based access control mirrors your existing permissions. Employees only see knowledge their department and clearance level authorizes.
AES-256 encryption at rest and in transit. All queries and answers logged for compliance audits with configurable retention policies.
Compliance-ready for HIPAA, SOC 2, FINRA, and CMMC. We build deployment architectures that satisfy your regulatory requirements from day one.
Pricing
How Much Does an Internal AI Knowledge Base Cost?
Most businesses either build internally and spend 4–6 months, or buy a SaaS tool that can't connect all their sources. Here is how ITECS compares for a 50–500 person company.
DIY / Internal Build
ITECS Managed Knowledge Base
Time to production
4–6 months
4–6 weeks
Connected data sources
1–2 platforms
SharePoint, Drive, Notion, Confluence, file servers
Hallucination control
None — answers anything
Confidence scoring + data boundaries
Access control
Manual per-user setup
SSO + role-based auto-provisioning
Document updates
Manual re-indexing
Auto-sync within minutes
Setup cost
$15,000–$50,000+
$8,000–$20,000 flat fee
Average client ROI: 50% faster onboarding, 70% fewer repeated questions, 25+ hours recovered per week. Most businesses recoup the full setup cost within 3 months.
- Setup: $8,000–$20,000 depending on data sources, document volume, and compliance scope
- Monthly hosting and management from $500/month — includes auto-indexing, performance monitoring, and quarterly accuracy reviews
- Multi-source connectivity included — no per-platform fees for SharePoint + Google Drive + Notion + Confluence
- HIPAA/SOC 2/FINRA/CMMC compliance options available — quoted based on your regulatory requirements
50%
Faster Employee Onboarding
70%
Fewer Repeated Questions
5sec
Avg. Answer Time
600+
Queries Handled Weekly
FAQ
Internal AI Knowledge Base FAQ
How much does an internal AI knowledge base cost?
Setup ranges from $8,000–$20,000 depending on the number of data sources, document volume, and compliance requirements. Ongoing hosting and management starts at $500/month including auto-indexing and performance monitoring. Most Dallas businesses with 50+ employees recover the full cost within 3 months through reduced onboarding time and fewer repeated questions.
Is my company data safe in an AI knowledge base?
Yes. We deploy on your infrastructure or a private cloud — your data never touches public AI services or trains third-party models. We implement AES-256 encryption at rest and in transit, role-based access control, and full audit logging. For regulated industries we build HIPAA, SOC 2, FINRA, and CMMC compliant deployments.
What is the difference between an AI knowledge base and SharePoint search?
SharePoint search matches keywords. An AI knowledge base understands meaning. Ask 'What is our PTO policy for first-year employees?' and get the exact answer with a citation — instead of 50 documents that mention 'PTO'. It also searches across all your platforms simultaneously, not just SharePoint.
How does RAG work for internal knowledge bases?
RAG (Retrieval-Augmented Generation) splits your documents into chunks, converts them into vector embeddings, and stores them in a searchable database. When an employee asks a question, the system retrieves the most relevant passages, then uses AI to synthesize a clear answer with citations. It only answers from your data — no hallucinations.
How long does it take to deploy an AI knowledge base?
Most deployments take 4–6 weeks from kickoff to production. Week 1 covers the documentation audit and data source mapping. Weeks 2–4 handle ingestion, pipeline configuration, and accuracy testing. Weeks 5–6 cover deployment, team training, and auto-sync configuration. Companies with clean, centralized documentation can go faster.
Can the AI knowledge base connect to multiple platforms at once?
Yes. A single knowledge base can pull from SharePoint, Google Drive, Notion, Confluence, file servers, and wikis simultaneously. Multi-source connectivity is included at no additional per-platform fee. Employees search one interface and get answers sourced from any connected platform.
What happens when we update or add new documents?
Auto-sync monitors your connected data sources and re-indexes new or updated documents within minutes. No manual re-ingestion required. Deleted documents are automatically removed from search results. We also run quarterly reviews to tune retrieval accuracy as your knowledge base grows.
Final step
Start with an AI Readiness Assessment.
Identify the workflows, risks, data boundaries, and operating model before AI spend turns into another unmanaged tool rollout.
30 minutes | no obligation | DFW-based team | (214) 444-7884