What Is On-Premise Document AI?

AI Document Processing Operated Fully Within a Private Network

On-premise Document AI refers to an AI-powered system for processing documents that runs entirely within an enterprise's private infrastructure — without any cloud connectivity. This isolated setup (e.g., VPNs or air-gapped networks) ensures documents are handled securely without exposing them to external networks. It's particularly beneficial for organizations subject to strict regulations or those dealing with sensitive information.

Designed for Security-First Organizations

Industries such as finance, pharmaceuticals, and government agencies often cannot allow internal documents to be uploaded to external AI servers. With on-premise Document AI, all data is processed and stored locally. Search logs and usage records are kept within the system, helping businesses meet internal security policies, audit requirements, and legal compliance.

Integrated with OCR, NLP, RAG, and Audit Trails

Document AI does more than just search — it structures, understands, and responds to content using advanced AI. On-premise Document AI includes:

• OCR (Optical Character Recognition) to extract text from scanned files

• NLP (Natural Language Processing) to interpret information

• RAG (Retrieval-Augmented Generation) to answer questions using context It also supports audit logs, access control, and usage tracking — enhancing information security.

Architecture of On-Premise Deployment

Deployment Environments: On-Premise, VPC, and Air-Gapped

• On-Premise: Installed directly on local company servers. All computing and data storage occur internally.

• VPC (Virtual Private Cloud): A segregated environment built within a cloud provider’s infrastructure.

• Air-Gapped: A fully isolated network with no internet connection. Common in defense and intelligence sectors.

Each environment requires different configurations for deployment, communication protocols, and security policies — making infrastructure customization essential.

Document Processing Workflow

1. OCR: Converts scanned or digital documents into text

2. Key-Value Extraction: Identifies data pairs (e.g., “Contract Date: 2023.12.01”)

3. Structuring: Stores extracted data in a database

4. Query & Response: Uses LLM or rule-based engines to answer natural language queries based on stored data

Infrastructure Requirements: Containers, GPUs, and More

Typically deployed using containerized solutions like Kubernetes or Docker, on-premise Document AI systems often require GPU support. Especially for RAG-based models, which demand significant memory and compute power during document embedding and LLM operations — infrastructure planning is crucial.

Core Features and Tech Stack

Structured Document Recognition and Table Analysis

Beyond simple text extraction, Document AI must understand and analyze tabular data — identifying relationships between cells. This is crucial for processing clinical trial tables in pharma reports or cost tables in financial documents.

Support for Custom LLMs and RAG Systems

Organizations can implement open-source LLMs (e.g., LLaMA, Mistral) or develop internal document embedding systems to build RAG-powered responses. This enables natural language queries, summaries, and key sentence highlights — all without relying on external APIs.

Built-In Security and Compliance Features

Essential features include:

• Audit logs: Track who searched what and when

• Access control: Restrict document access by user role

• Version control: Track changes and restore past versions of documents

Use Cases by Industry

Financial Institutions: Contract Review and Recordkeeping

Automate analysis of repetitive and complex documents such as loan contracts and product terms. Extract key clauses and maintain change logs and Q&A histories for audit readiness.

Public Sector: Sensitive Information Search with Audit Trail

Governments and municipalities often handle sensitive personal and administrative data. On-premise Document AI allows secure, traceable search without exposing documents externally.

Pharma & Manufacturing: Regulatory Document Analysis

Industries regulated by GMP or FDA can use Document AI to scan large volumes of documentation, detect compliance violations, and prepare response files efficiently.

Checklist for PoC Implementation

Performance Metrics to Evaluate

• Response accuracy: Use Top-k metrics based on document type

• Response time: Average time to return results

• Automation rate: F1 score-based measurement of how much manual work is reduced

Tailor test datasets to reflect industry-specific document types for accurate evaluation.

Cost Considerations

Deployment costs depend on:

• GPU specs

• Number of concurrent users

• Document volume

• Maintenance model

Some vendors offer CPU-only versions, but these have limited performance. Licensing can be based on user count, document volume, or concurrent access.

Vendor Selection Criteria

Evaluate:

• Experience with on-premise deployments

• Compatibility with open-source tech ecosystems

• Flexibility to update LLMs or integrate with internal systems

Practical Benefits of Solutions Like Wissly

Truly Local RAG Search Without Uploads

Wissly is an on-premise AI document search platform that operates fully within your organization. It doesn’t connect to external servers, making it ideal for cloud-restricted environments.

Multi-Format Support: PDF, Word, HWP, and More

Handles diverse document types — including scanned images, Hangul (HWP), Word, and PDF files — with OCR and NLP. Recognizes complex structures for accurate indexing and search.

Traceable, Highlighted Answers for Compliance

Wissly provides answers with highlighted sentences and original source references — a big plus for legal and audit teams preparing documentation.

Conclusion: Secure Document Utilization at Scale

On-premise Document AI is more than just a document storage system. It empowers enterprises to explore and leverage their vast repositories securely — without compromising on compliance. As your document volume grows, don’t let information become buried. Let AI uncover and activate its value.

With solutions like Wissly, it's time to redesign your document strategy — securely and intelligently.