Generic AI gives generic answers. We build RAG systems that pull from your docs, your data, your products—so your AI sounds like an expert on YOU, not Wikipedia.
ChatGPT is smart, but it doesn't know YOUR business.
Generic AI has no idea about your products, policies, or internal processes.
AI makes up answers when it doesn't have real data to work with.
RAG grounds AI in YOUR documents, ensuring accurate, relevant responses.
From customer support to internal knowledge—AI that speaks your language.
AI that searches your internal docs, wikis, and manuals. Employees get instant answers without digging through SharePoint.
Answer questions using your actual inventory and specs. "Do you have this in blue?" gets a real answer, not a guess.
Chatbots that pull from your help docs and ticket history. Resolve issues faster with context-aware responses.
Upload PDFs, contracts, or reports and ask questions. Legal review, due diligence, research—all faster.
Combine databases, APIs, and documents into one AI interface. The single source of truth your team needs.
Vector + keyword search for best accuracy. When semantic search isn't enough, we add traditional search power.
We don't just plug in an API—we build systems that actually work.
We analyze your existing documents, databases, and knowledge sources. What do you have? Where does it live? How current is it?
We design the optimal retrieval strategy—chunking, embedding models, vector databases, and search algorithms tailored to your data.
We process your documents, build the vector index, and create the retrieval pipeline. Includes testing for accuracy and edge cases.
We connect RAG to your existing systems—Slack, Teams, your website, CRM, helpdesk. Wherever your users are.
We track what questions get asked, what answers work, and continuously improve accuracy. RAG gets smarter over time.
RAG (Retrieval Augmented Generation) connects AI to YOUR data. Instead of relying only on what ChatGPT learned during training, RAG retrieves relevant information from your documents and uses it to generate accurate, up-to-date answers. Think of it as giving ChatGPT a brain full of your company's knowledge.
Yes. We can deploy RAG using local models (not in the cloud) or with SOC2/GDPR-compliant cloud providers like Azure OpenAI. Your data is never used for model training. We also implement access controls so only authorized users see sensitive information.
A basic POC with a single data source takes 2-4 weeks. A full production system with multiple integrations, access controls, and monitoring takes 6-12 weeks depending on complexity.
Almost anything: PDFs, Word docs, web pages, Notion, Confluence, SharePoint, Google Drive, databases, APIs, and more. If it contains text, we can index it.
Much more accurate for your specific use case. Generic AI hallucinates about 30-40% of the time when asked about specific company information. Well-implemented RAG reduces this to under 5% while citing sources.
Yes. Modern embedding models work across languages. Your Hebrew documents can answer English questions and vice versa. We've built RAG systems that work seamlessly in Hebrew, English, Arabic, and more.
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