Solution Package

AI Knowledge Management

Turn scattered databases, emails, and PDFs into a single intelligent search portal.

The Business Challenge

Break down data silos. NANO4C's AI Knowledge Management solution indexes scattered files from SharePoint, local servers, and databases—creating a unified search interface that understands meaning, not just keywords.

Solution Architecture Showcase

How our AI Knowledge Management integrates into your environment.

Multi-Source Data Ingestion

Automated connectors ingest data from email servers, local file shares, SharePoint, and databases.

Semantic Embedding Engine

Converts text blocks into mathematical vectors that represent the core meaning of the words.

Unified AI Search Interface

A simple search portal that answers questions directly, citing the source documents used.

Central Hub

Business Value Delivered

Unified Enterprise Knowledge

Access all company files and historical data from a single search bar.

Semantic Search Intelligence

Query using natural sentences (e.g. 'How did we solve the server lag in 2024?') to get exact results.

Preserved Operational History

Store and query years of project notes and decisions, ensuring expert knowledge is never lost.

Frequently Asked Questions

How does semantic search differ from keyword search? +

Keyword search looks for exact matches, while semantic search understands context and meaning to find relevant files.

Can the system index scanned paper documents? +

Yes, we use advanced OCR (Optical Character Recognition) to extract and index text from scanned PDFs and images.

Is the search index updated in real-time? +

Yes, we configure background processes to scan and index new or modified files automatically.

Can we host this system on-premise? +

Yes, we can deploy the entire search and database system on your local hardware for complete data control.

Does the system cite its sources? +

Yes, every answer shows clickable links to the exact files and pages used, enabling quick validation.

How do you handle duplicate documents? +

The ingestion pipeline uses deduplication logic to index only the latest version of files.

What vector databases do you use? +

We build on enterprise-grade engines like Milvus, Qdrant, or PGVector depending on your infrastructure.

Can the search run inside Microsoft Teams? +

Yes, we build custom tabs and bots to enable search directly within Teams channels.

Is my data shared with external vendors? +

No, the system is fully self-contained inside your network; no data is sent to external sites.

What is the cost model for this solution? +

We charge a one-time implementation fee followed by a predictable monthly support retainer.

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