Rag Development
Your Knowledge. Instant Access.
What We Do
Your organization already has the answers. They are buried in SharePoint folders, Confluence pages, Google Drive documents, Slack archives, recorded meetings, and email threads. Your team spends hours every week searching for information that already exists somewhere in your systems. Retrieval-Augmented Generation changes that. A RAG system ingests your documents, indexes them semantically, and gives your team a single interface to ask questions in plain language.
The answer comes back in seconds with citations pointing to the exact source document. Not a list of search results. Not a hallucinated response. A grounded answer from your own knowledge base. We build RAG systems that connect to your existing document infrastructure, handle permissions and access control, and improve continuously as your knowledge base grows.
How We Work
We start by auditing your knowledge base: where documents live, how they are organized, how frequently they change, and what questions your team needs answered most often. That audit shapes the ingestion pipeline. We connect to your document sources, process content into optimally sized chunks, generate embeddings, and store them in a vector database. The retrieval pipeline is tuned for your specific domain vocabulary and question patterns.
The generation layer synthesizes answers grounded strictly in retrieved content with source citations on every response. We configure guardrails that decline to answer when confidence is low rather than generating plausible but incorrect responses. Deployment options include web interface, Slack bot, Teams integration, API endpoint, or embedded widget in your existing applications. We monitor retrieval accuracy, track which questions go unanswered, and continuously improve the system as your knowledge base evolves.
Why Running Start Digital
Pricing
From $10,000
Typical turnaround: 6-16 weeks
Includes
Frequently Asked Questions
RAG stands for Retrieval-Augmented Generation. Unlike ChatGPT which answers from its training data, a RAG system retrieves information from your specific documents before generating a response. The answer is grounded in your content, not general internet knowledge.
PDFs, Word documents, web pages, Confluence pages, Notion pages, Google Docs, Slack messages, emails, CSV files, and structured databases. If it contains text or data, we can index and search it.
We implement permission-aware retrieval that respects your existing access controls. Users only get answers from documents they are authorized to see. This integrates with Active Directory, SSO providers, and application-level permissions.
The system reports low confidence and declines to answer rather than guessing. It can suggest related documents that might help or escalate the question to a human subject matter expert.
A single knowledge base with standard document types takes 4 to 8 weeks. Enterprise deployments with multiple sources, permission integration, and custom interfaces take 10 to 16 weeks.
Automated ingestion pipelines monitor your document sources for changes and re-index updated content. New documents are indexed within hours of publication. Deleted documents are removed from the index automatically.
Ready to get started?
Start with a $5,000 deposit. Balance due on delivery.