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Custom LLM Integration

Your Private Intelligence Layer

Solution Infrastructure

We specialize in moving companies beyond basic ChatGPT wrappers. We build proprietary RAG (Retrieval-Augmented Generation) systems that allow your LLM to securely access your internal documentation, wikis, and databases without leaking data to public models. Our custom models are trained on your proprietary data, ensuring complete privacy and context-aware responses that generic AI cannot provide.

Core Capabilities

  • Proprietary RAG Pipeline setup with enterprise data connectors
  • Model fine-tuning (Llama 3, Mistral, GPT-4o, Claude, Gemini)
  • Context-aware AI Agents for internal workflows
  • Enterprise-grade data encryption & on-premise deployment options
  • Real-time document indexing and retrieval
  • Custom API endpoints for seamless integration

Tech Stack

LangChainPineconePyTorchOpenAI APIWeaviatevLLM

Implementation Process

1

Discovery & Data Audit (Week 1)

2

Model Selection & Fine-tuning Prep (Week 2)

3

RAG Pipeline Architecture Design (Week 3)

4

Development & Integration (Weeks 4-5)

5

Testing, Security Audit & Deployment (Week 6)

Real-World Use Cases

Internal knowledge base chatbot for employees

AI customer support agent trained on product docs

Legal document analysis and contract review

Medical literature summarization for healthcare

Frequently Asked Questions

Is my data used to train public models?

No. We deploy private models that never share your data with third parties.

Can I run this on my own servers?

Yes, we support on-premise, VPC, and hybrid cloud deployments.

Impact Metric

Reduces internal support tickets by 65% through automated knowledge retrieval.

Request Demo

Delivery Time

4-6 weeks

Pricing

Custom

Best For

SaaSHealthcareFinanceLegalE-commerce
View Case Study