Retrieval Augmented Generation (RAG) for LLMs
At LLM.co, we build private RAG pipelines that connect your LLMs to internal documents, wikis, policies, emails, contracts, and databases—ensuring every answer is grounded in your truth, not just the model’s training data.
What is RAG?
Retrieval-Augmented Generation (RAG) combines large language models with real-time information retrieval—so the AI doesn’t guess, it looks things up.
Instead of relying solely on a model’s memory (which can be outdated or incomplete), RAG injects relevant, up-to-date content from your private knowledge base into each response. The result? More accurate, traceable, and business-aligned answers—even in high-stakes, compliance-sensitive environments.
Why LLM.co for RAG
Why you should choose LLM.co for your retrieval augmented generation solutions
Built for Compliance
Built for data-sensitive enterprises: Law firms, finance, healthcare, government
Custom Indexing & Optional Pairing
Custom indexing tuned to your structure and metadata. Optional pairing with agentic AI, chatbots, or internal search.
Modular Deployment
Designed for modular deployment: Integrate RAG into your chatbot, Slack assistant, helpdesk, or search UI.
Smarter AI Starts With Accurate & Trusted Knowledge
RAG is how enterprises move from guessing to knowing—bridging the gap between AI and your private data. With LLM.co, your organization gains the power of retrieval-grounded LLMs that are accurate, auditable, and secure.
Reduce hallucination. Increase trust. Automate with confidence.
Email/Call/Meeting Summarization
LLM.co enables secure, AI-powered summarization and semantic search across emails, calls, and meeting transcripts—delivering actionable insights without exposing sensitive communications to public AI tools. Deployed on-prem or in your VPC, our platform helps teams extract key takeaways, action items, and context across conversations, all with full traceability and compliance.
Security-first AI Agents
LLM.co delivers private, secure AI agents designed to operate entirely within your infrastructure—on-premise or in a VPC—without exposing sensitive data to public APIs. Each agent is domain-tuned, role-restricted, and fully auditable, enabling safe automation of high-trust tasks in finance, healthcare, law, government, and enterprise IT.
Internal Search
LLM.co delivers private, AI-powered internal search across your documents, emails, knowledge bases, and databases—fully deployed on-premise or in your virtual private cloud. With natural language queries, semantic search, and retrieval-augmented answers grounded in your own data, your team can instantly access critical knowledge without compromising security, compliance, or access control.
Multi-document Q&A
LLM.co enables private, AI-powered question answering across thousands of internal documents—delivering grounded, cited responses from your own data sources. Whether you're working with contracts, research, policies, or technical docs, our system gives you accurate, secure answers in seconds, with zero exposure to third-party AI services.
Custom Chatbots
LLM.co enables fully private, domain-specific AI chatbots trained on your internal documents, support data, and brand voice—deployed securely on-premise or in your VPC. Whether for internal teams or customer-facing portals, our chatbots deliver accurate, on-brand responses using retrieval-augmented generation, role-based access, and full control over tone, behavior, and data exposure.
Offline AI Agents
LLM.co’s Offline AI Agents bring the power of secure, domain-tuned language models to fully air-gapped environments—no internet, no cloud, and no data leakage. Designed for defense, healthcare, finance, and other highly regulated sectors, these agents run autonomously on local hardware, enabling intelligent document analysis and task automation entirely within your infrastructure.
Knowledge Base Assistants
LLM.co’s Knowledge Base Assistants turn your internal documentation—wikis, SOPs, PDFs, and more—into secure, AI-powered tools your team can query in real time. Deployed privately and trained on your own data, these assistants provide accurate, contextual answers with full source traceability, helping teams work faster without sacrificing compliance or control.
Contract Review
LLM.co delivers private, AI-powered contract review tools that help legal, procurement, and deal teams analyze, summarize, and compare contracts at scale—entirely within your infrastructure. With clause-level extraction, risk flagging, and retrieval-augmented summaries, our platform accelerates legal workflows without compromising data security, compliance, or precision.
Key RAG Features with LLM.co
Any deployment of retrieval augmented generation (RAG) comes complete with the following critical components
Private & Secure
All ingestion, indexing, and retrieval happens in your VPC or on-prem—no public API calls, no vendor data access.
Model Agnostic Architecture
Works with fine-tuned open-source models (like LLaMA, Mistral, Mixtral) or commercial models in your environment.
Modular Source Chunking
We intelligently segment documents to optimize retrieval relevance and reduce prompt bloat.
Seamless Integration
Connect to SharePoint, Confluence, Notion, Google Drive, file servers, or custom knowledge systems.
Private LLM Blog
Follow our Agentic AI blog for the latest trends in private LLM set-up & governance
FAQs
Frequently asked questions about our RAG services
Traditional LLMs rely solely on their pre-trained knowledge, which can be outdated or incomplete—leading to hallucinations. RAG reduces this risk by retrieving relevant, real-world content (like internal PDFs or wiki pages) and injecting it into the model’s prompt at runtime. This grounds responses in factual, verifiable information from your own knowledge base.
RAG can ingest and index a wide range of documents: PDFs, DOCX, TXT, HTML, slide decks, spreadsheets, emails, support tickets, internal wikis, and more. If it contains text, we can embed it semantically and make it searchable by your LLM—securely and privately.
Yes. LLM.co’s RAG pipelines are deployed inside your virtual private cloud (VPC) or on-prem environment, ensuring that no data leaves your infrastructure. We support full encryption, access control, and audit logging, making the solution safe for healthcare, legal, financial, or government workflows.
You’re not locked in. Our RAG architecture is model-agnostic, meaning it works with both open-source models (like LLaMA, Mistral, or Mixtral) and licensed/commercial models deployed within your environment. We tailor the system to match your performance, privacy, and compliance needs.
Most RAG systems can be implemented in 4 to 8 weeks, depending on the volume and format of data, desired integrations (e.g., SharePoint, Notion, Confluence), and complexity of the use case. Our team handles ingestion, vectorization, search configuration, and LLM integration—all within a private, secure environment.