A private AI that answers from your own documents.
This is part of our custom software service: an assistant that reads your policies, contracts, wikis, CRM notes and PDFs, answers staff questions in plain language, and cites the document it took the answer from. It runs on a server you control, so the files never leave your environment. Engineers call this retrieval-augmented generation, RAG.
How it works
Three steps from scattered internal knowledge to an assistant that answers in seconds and shows its source.
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 whole 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
What a private assistant on your own documents changes for the people who use it every day.
Repeat questions stop reaching people
Most internal questions have already been answered somewhere in a policy, a procedure or an old email thread. When the assistant can find that passage and quote it, the routine half of the queue stops landing on a colleague who has to stop what they were doing.
The usual reason clients ask us for thisAnswers from 10,000+ page knowledge bases
Staff no longer hunt through SharePoint, email threads, and PDF archives. The system retrieves the right passage from across your entire document set and answers in seconds, with a citation to verify.
Consistent across every implementationExternal 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, the retrieval layer constrains them to your approved material, eliminating the hallucination problem and keeping every output audit-ready.
Core architectural benefitOnboarding 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.
Why documentation-heavy teams ask for itSearch 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
Answer patient and staff questions from clinical protocols, intake procedures and policy documents, with nothing leaving your infrastructure. The citation matters here: a front-desk answer can be checked against the source before anyone acts on it.
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
Companies sitting on years of internal docs, SOPs and wikis that nobody can find. The assistant turns that buried material into something a new hire can question directly at 11pm.
Compliance-Sensitive Businesses
Finance, insurance and regulated industries where data residency and auditability are non-negotiable. Running it on infrastructure you own means full control and a clear line from every answer back to its source.
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, this pays for itself quickly. Book an audit and we will map your sources, size the build, and tell you honestly if a simpler tool would do the job. It is often part of a larger custom software project.
Scoped to your documents, not sold by the seat
Most builds land in the connected systems band, $6,000 to $15,000, depending on how many sources there are and how much cleanup the documents need. Larger multi-system projects start at $15,000, and ongoing support runs $300-500/mo (Care) or $750-1,500/mo (Active).
Every engagement starts with a free audit: we map your sources, scope the build, and give you a fixed quote. Local to the region? We also list this under software development in Sacramento.
Frequently asked questions
What people ask before we build a private assistant on their own documents.
Is this the same thing as RAG?
Yes. Engineers call it retrieval-augmented generation, or RAG. Instead of a general-purpose model answering from memory, the system retrieves the relevant passages out of your own files first, then writes the answer and cites the document it came from. Almost nobody searches for the acronym, so we describe it in plain language everywhere else on this page.
Is this a separate service or part of custom software?
It is part of our custom software service. A private assistant on your documents is one of the things we build inside a larger system, alongside internal tools and integrations, and it is usually scoped in the same engagement. It has its own page because people ask for it by name, not because it is sold separately.
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 assistant on your own documents is constrained strictly to your approved material: it can only answer from your files, 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 index 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 retrieval 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.
Put your documents where your team can actually ask them questions.
Book a 30-minute audit. We map your sources, show you what a private assistant on your own files would answer, and tell you what it takes to build.
No commitment. No sales pitch. Just the plan.