IntelliDocs AI
Your documents. Your AI. Your infrastructure. Zero compromise.
Enterprise Document Intelligence Without Compromise
Organizations today sit on vast repositories of institutional knowledge trapped inside documents — contracts, technical specifications, policies, reports, and regulatory filings. When employees need answers, they spend hours searching through folders, skimming PDFs, and piecing together information from multiple sources. Generic AI chatbots offer fast answers but hallucinate confidently, referencing information that doesn't exist in your documents or mixing in irrelevant training data.
IntelliDocs AI solves this with Retrieval-Augmented Generation (RAG) — a fundamentally different approach to enterprise AI. Instead of generating answers from pre-trained knowledge, IntelliDocs AI first performs semantic vector search across your uploaded documents using PostgreSQL pgvector with HNSW indexing, retrieves the most relevant passages with similarity scores, and only then generates a precise answer grounded exclusively in your verified content. Every response includes source attribution: document name, page number, and relevance score — so users can verify answers against the original source in seconds.
Built on Clean Architecture principles with .NET 8, React, PostgreSQL, and Ollama, IntelliDocs AI follows a per-client deployment model where each organization runs a completely isolated instance — your own application server, your own database, your own AI engine. No data co-mingling, no multi-tenant risks, no vendor lock-in. Deploy on Azure, AWS, GCP, on-premise bare metal, or air-gapped environments. The entire stack is open-source and portable: PostgreSQL replaces Pinecone, Ollama replaces proprietary AI APIs, and your data never leaves your infrastructure.
With sub-25ms semantic search across millions of document chunks, real-time SSE streaming responses, four intelligent chunking strategies, and security aligned with ISO 27001, OWASP API Security Top 10, and GDPR — IntelliDocs AI delivers enterprise-grade document intelligence that IT teams trust and end users love.
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Document Intelligence, Reimagined
Six core capabilities that transform how your organization interacts with its knowledge base.
AI-Powered Knowledge Assistant
Real-time conversational AI grounded in your organization's documents using Retrieval-Augmented Generation (RAG). Every answer includes source attribution with document name, page number, and similarity score — eliminating hallucinations and ensuring verifiable, trustworthy responses. Unlike generic chatbots, IntelliDocs AI retrieves verified content from your uploaded documents before generating answers.
Intelligent Document Processing
Upload PDF, DOCX, CSV, and TXT files for automatic text extraction, semantic chunking, 768-dimensional vector embedding, and indexed storage. Four intelligent chunking strategies — Semantic, Fixed, Hybrid, and Paragraph — are optimized for different document types including legal contracts, technical specifications, structured reports, and narrative content.
Real-Time Streaming Responses
Server-Sent Events (SSE) streaming delivers AI responses token-by-token in real time — users see answers forming instantly without waiting for full generation. Combined with pgvector HNSW indexing, semantic search across millions of document chunks completes in under 25 milliseconds, delivering a fluid, responsive experience.
Enterprise-Grade Security
Defense-in-depth security aligned with ISO 27001, OWASP API Security Top 10, and SOC 2 Type II requirements. JWT Bearer authentication with RS256 signing, BCrypt password hashing (work factor 12), refresh token rotation with revocation chains, rate limiting (100 req/min general, 10 req/min auth), and comprehensive audit logging on every request.
Per-Client Deployment Model
Each client runs a dedicated instance with their own application server, PostgreSQL database, and AI engine — complete data isolation with zero risk of cross-tenant data leakage. Independent scaling, custom AI models per instance, and regulatory compliance guaranteed per jurisdiction. Updates and patches are applied independently without affecting other clients.
Cloud-Agnostic Portability
Built entirely on open-source technologies with zero vendor lock-in. Deploy via Docker Compose, Kubernetes with Helm, bare metal VMs, or any managed cloud. No dependency on Azure Cognitive Search, AWS Kendra, Pinecone, or Weaviate — PostgreSQL + pgvector provides battle-tested, self-hosted vector search. Runs on Azure, AWS, GCP, or on-premise infrastructure.
From Document Upload to AI-Powered Answers
IntelliDocs AI transforms your documents into a searchable, conversational knowledge base in five automated steps.
Upload Documents
Upload PDF, DOCX, CSV, or TXT files through the web interface or REST API. Documents are queued for asynchronous processing via BackgroundService + Channel<T> producer-consumer pattern.
AI Processing & Chunking
Documents are automatically parsed, text is extracted, and content is split into optimized chunks using one of four strategies: Semantic, Fixed, Hybrid, or Paragraph — selected based on document type.
Vector Embedding
768-dimensional embeddings are generated using nomic-embed-text via Ollama, capturing deep semantic meaning beyond keywords. Embeddings are stored in PostgreSQL with pgvector and indexed using HNSW for sub-second search.
Semantic Search
When you ask a question, it is embedded and matched against your document chunks using cosine similarity computed natively in PostgreSQL. HNSW indexing delivers results in ~15ms across 1M+ chunks.
AI-Generated Answer
Retrieved context is fed to the LLM (llama3.2, mistral, qwen, or deepseek) which generates a precise, source-attributed answer streamed token-by-token via SSE to the user interface.
See IntelliDocs AI in Action
From conversational document search to real-time health monitoring, explore the interfaces that power enterprise document intelligence.
Knowledge Assistant
Conversational AI interface grounded in your document repository. Ask questions in natural language and receive precise, source-attributed answers streamed in real time. Every response links back to the original document and page.
Document Library
Upload and manage your organization's knowledge base. Track processing status, view chunk statistics, and monitor embedding quality for each document. Supports PDF, DOCX, CSV, and TXT with automatic format detection.
Health Monitoring Dashboard
Real-time component health monitoring for Database, AI Engine, and Memory. REST /health endpoint ready for Prometheus/Grafana integration. Instant visibility into system status and performance metrics.
Enterprise-Ready by Design
Clean Architecture, defense-in-depth security, and compliance readiness built into every layer.
Clean Architecture (Onion)
Four-layer separation of concerns: Domain (pure C#, zero dependencies), Application (use cases, DTOs, validation), Infrastructure (EF Core, PostgreSQL, Ollama), and API (ASP.NET Core 8 endpoints). All layers depend inward on Domain abstractions.
Zero Data Leakage
Per-client deployment ensures data never co-mingles between organizations. AI models run locally via Ollama — no data sent to external AI APIs. Cosine similarity search computed natively in PostgreSQL — data never leaves the database for search operations.
HNSW Vector Indexing
Hierarchical Navigable Small World indexing via pgvector delivers O(log n) search complexity — 15ms on 1M chunks versus 12 seconds for naive approaches. The same algorithm family used by Spotify, Meta, and Pinecone, running on open-source PostgreSQL.
OWASP API Security
Mitigations implemented for OWASP API Security Top 10 (2023): Broken Authentication (API2), Unrestricted Resource Consumption (API4), SSRF prevention. FluentValidation on all API inputs, DOMPurify on frontend, parameterized queries via EF Core.
GDPR by Design
Data sovereignty through per-client deployment. User data deletion via API endpoints. Data residency guaranteed per jurisdiction. No data processed by third-party cloud AI services. Full audit logging of all data access and modifications.
Open-Source Stack
Zero proprietary dependencies. PostgreSQL + pgvector replaces Pinecone/Weaviate. Ollama replaces Azure OpenAI/AWS Bedrock. .NET 8 LTS, React 19, EF Core 8 — all open-source, all portable, all self-hosted. No vendor lock-in at any layer.
Contact Us for a Personalized Demo
IntelliDocs AI is deployed per-client with custom configuration. Schedule a demo to see the platform with your own documents and receive a tailored deployment proposal.
45 minutes
Live Demo
Cloud or On-Premise
Deployment Options
Your documents
Proof of Concept
Frequently Asked Questions
Common questions about IntelliDocs AI, RAG architecture, and enterprise document intelligence.
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Real Answers From Your Real Documents. Zero Hallucinations.
Join organizations that trust IntelliDocs AI to transform their document repositories into intelligent, searchable knowledge bases — with complete data sovereignty.