Your own private AI — trained on your knowledge, on your infrastructure.
We deploy a private Retrieval-Augmented Generation (RAG) system on your own secure VPS. Your team (and your AI agents) get instant, cited answers from your internal documentation — and your data never leaves your server.
How it works
Three steps from your scattered internal knowledge to a private AI that answers instantly and cites its sources.
Connect and index your knowledge
We connect to your internal docs, wikis, policies, CRM records, email archives, and databases, then ingest everything into a private vector knowledge base hosted on your own infrastructure. Your data never leaves your environment during this process.
Deploy on your secure infrastructure
We deploy the full RAG stack on your own VPS or private server. For maximum data security we offer fully self-hosted AI models (LLaMA, Qwen) — meaning zero queries or documents ever reach an external AI provider's servers.
Ask in natural language, get cited answers
Your staff and AI agents query the system in plain English and receive accurate, source-grounded answers 24/7. Every response cites the specific document it came from — no hallucinations, no guesswork.
What you gain
Real capabilities and representative results from private RAG deployments.
Support-desk cost reduction
In a representative medical support-desk deployment, a private RAG system answering patient queries from 10,000+ pages of internal documentation reduced support costs by roughly 40% — queries resolved instantly without staff involvement.
Representative result from IG Digital Lab deploymentAnswers from 10,000+ page knowledge bases
Staff no longer hunt through SharePoint, email threads, and PDF archives. The RAG system retrieves the right passage from across your entire document corpus and answers in seconds — with a citation to verify.
Consistent across all RAG implementationsExternal data exposure
With self-hosted models, not a single word of your documents or queries leaves your infrastructure. Suitable for privileged legal data, medical records, and compliance-sensitive business information with the right server configuration.
Architecture constraint, not a marketing claimAI agents grounded in approved knowledge
When your AI automation agents need to answer questions or make decisions, RAG constrains them to your approved knowledge base — eliminating the hallucination problem and keeping every output audit-ready.
Core architectural benefit of RAGOnboarding and support acceleration
New hires and support staff get instant, accurate answers to procedural and policy questions without waiting for a senior colleague. Corporate knowledge becomes democratically accessible, not locked in individual heads.
Reported by clients across service industriesSearch across CRM, email, docs, and databases
One natural-language query searches across all your connected systems simultaneously — CRM notes, email archives, internal wikis, policy documents, and databases — surfacing insights that were previously invisible.
Cross-system retrieval capabilityWho benefits most
Any organization where accuracy, privacy, and deep internal knowledge matter.
Healthcare & Clinics
Instantly answer patient and staff queries from clinical protocols, intake procedures, and policy documents — with zero data leaving your infrastructure. ~40% support cost reduction demonstrated.
Legal Firms
Privileged client data stays on your servers. Staff search case law, precedents, and internal memos in natural language — fast, accurate, and confidential.
Documentation-Heavy Companies
Enterprises sitting on years of internal docs, SOPs, and wikis that nobody can find. RAG turns that buried knowledge into an always-available expert assistant.
Compliance-Sensitive Businesses
Finance, insurance, and regulated industries where data residency and auditability are non-negotiable. RAG on your infrastructure means full control and a clear data lineage.
Support Teams
Agents get instant, accurate answers from your product docs and knowledge base — no more "let me check and get back to you." Resolution times drop, customer satisfaction rises.
Any Knowledge-Intensive Business
If your team spends hours searching for internal information, the ROI on a private RAG system is immediate. Book an audit and we'll map your knowledge sources and estimate payback.
Scoped to your knowledge base
Every RAG deployment is sized to your infrastructure, data sources, and team needs.
Every engagement starts with a free AI audit — we map your knowledge sources, scope the build, and give you a fixed quote.
Frequently asked questions
Common questions about private RAG systems and what deployment looks like.
What is RAG and why does it matter?
RAG stands for Retrieval-Augmented Generation. Instead of relying on a general-purpose AI that makes things up, RAG grounds every answer in your actual documents — it retrieves the relevant passages first, then generates a response with citations. That means accurate, verifiable answers instead of hallucinations.
Does my data go to OpenAI or Google?
No. The system is deployed on your own infrastructure — your VPS or private server. We also offer fully self-hosted AI models (LLaMA, Qwen) so that zero data ever leaves your environment. Not a single document or query touches an external AI provider's servers.
How is this different from ChatGPT or other general AI tools?
General AI tools like ChatGPT answer from their training data — which doesn't include your internal knowledge and is prone to hallucination. A private RAG system is constrained strictly to your approved knowledge base: it can only answer from your documents, always cites its source, runs on your infrastructure, and never shares your data with third parties.
What data sources can it connect to?
We can index internal documents and PDFs, wikis and knowledge bases (Notion, Confluence, SharePoint), CRM records, email archives, databases, and any other structured or unstructured data source your team uses. Everything is ingested into a private vector knowledge base on your infrastructure.
Is it secure and compliant enough for sensitive data?
Yes — because it runs entirely on infrastructure you control, not on shared cloud AI services. The strict RAG architecture limits responses to your approved content only. With the right server configuration it is suitable for privileged legal data, medical records, and other compliance-sensitive information. We scope security requirements during the audit.
Your knowledge base deserves a smarter interface.
Book a 30-minute AI audit. We'll map your data sources and show you what a private RAG system could do for your team.
No commitment. No sales pitch. Just the plan.