How much time does your team lose every week searching through scattered documents, outdated spreadsheets, or waiting for a colleague to confirm a policy? How many potential sales or key decisions are delayed because critical information isn't instantly available or is inconsistent?

Challenge

Teams spent valuable time searching for information across documents and tools. Information was often outdated or inconsistent between departments. Generic AI tools produced incomplete or risky answers. The organization missed opportunities to use historical data and patterns. Onboarding was slow due to scattered knowledge. Sales and support faced long response times, repetitive questions, and scalability limitations. Quoting processes were manual, slow, and error-prone.

Solution

BitStone developed a fully custom AI assistant powered by a Retrieval-Augmented Generation (RAG) pipeline. It connects to ERP, CRM, e-commerce systems, product databases, manuals, policies, and internal wikis. All structured and unstructured data is cleaned, tagged, indexed, and transformed into a unified knowledge base. The RAG engine retrieves relevant information and combines it with advanced reasoning to deliver accurate, context-aware answers. The assistant can be accessed via web widget, internal chat, API, CRM plugin, or mobile app. Key benefits include instant conversational retrieval, centralized and verified knowledge, domain-trained security, actionable insights, and 24/7 onboarding and support.

Result

The assistant delivered three core outcomes. Instant Answers: Teams received immediate, conversational access to all business intelligence data, removing search time entirely. Actionable Insights: The AI surfaced trends, patterns, and growth opportunities from historical data. Operational Leverage: The company reduced onboarding time by around 50%, cut quoting time by over 70%, and offloaded 60–80% of repetitive inquiries. Sales follow-up rates improved and conversion rates increased by up to 30%.

Technologies

AI Architecture: RAG pipeline, vector search, LLM reasoning. Data Integrations: ERP, CRM, PIM, e-commerce, internal knowledge bases. Interfaces: Web widget, internal chat, API, CRM plugin, mobile. Security: Data isolation, encrypted indexes, role-based access. Infrastructure: ETL pipelines, semantic tagging, document preprocessing.