RAG Development
Retrieval-Augmented Generation (RAG) is an AI architecture that first retrieves the most relevant document passages, then asks the AI model to answer from those passages. As a result, the chatbot answers from your company documents rather than general knowledge, and every answer can be traced to its source.
Enterprise Knowledge Chatbot, Internal AI Chatbot
Business problems
HR, IT and operations answer the same procedure questions every day.
Key provisions are buried in policies, regulations or manuals hundreds of pages long.
AI answers without references are hard to verify and may be fabricated.
What we build
Collect documents from multiple sources, clean them and split them into searchable chunks.
Semantic search to find the document sections most relevant to the question.
Users only get answers from documents they are allowed to access.
Test question sets to measure accuracy and prevent fabricated answers.
Chat on the web, in internal applications or in channels your team already uses.
Example applications
Answer operating procedure questions for new employees and branch teams.
Find provisions across long regulatory and policy documents.
Service teams find answers in product manuals and past case handling.
Architecture & approach
Every answer goes through a document retrieval step before the AI model composes it.
Documents are collected, cleaned, chunked and indexed with their access-right metadata.
The question is matched with the most relevant passages the user is allowed to access.
The AI model composes the answer only from those passages, with references.
Test question sets run regularly to keep accuracy as documents grow.
Technology & integration
Deployment
RAG can be built privately so documents never leave company infrastructure.
| Option | Description | Best for |
|---|---|---|
| Cloud with data control | The document index stays on your servers; only relevant passages are sent to the model via API. |
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| Private / on-premise | Index and model run on internal servers. |
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Specializations
AI copilots, summarization and document Q&A that work with company data and systems.
Explore Generative AIOCR, document classification and data extraction from invoices, purchase orders and import documents, validated before entering systems.
Explore Document AITranscribe voice recordings and meetings into text that can be searched, summarized and passed to work systems.
Explore Speech-to-TextClassification, recommendations and AI steps embedded in workflows you already run.
Explore AI AutomationAI agents that run multi-step work with restricted tools, clear logs and human approval.
Explore AI Agent & Agentic WorkflowGenerative AI, RAG and document AI integrated into enterprise workflows with clear data controls.
Explore AI Development & IntegrationFAQ
Tell us about your context and goals. We will help map the solution, priorities and an initial estimate.
