By: Sergii Khlivnenko / AI / RAG / iGaming / Posted on: March 3, 2025
/ Comments: 0 An iGaming provider's team was spending hours every week searching Google Drive for answers that existed somewhere in their 200+ internal documents. Game rules, compliance procedures, integration specs, onboarding guides — all written, all stored, all effectively invisible in practice. People stopped searching and started asking colleagues instead, creating a secondary tax on senior team members' time.
The solution Sergii built through Consysteam was a RAG-powered Slack bot trained on the company's entire document library. RAG — Retrieval Augmented Generation — means the bot doesn't hallucinate answers. It retrieves the actual relevant document chunks and generates a response with source citations. The team gets a cited answer in seconds without leaving Slack.
The best AI implementation is the one people actually use. Embedding it in Slack, where the team already lives, was the highest-leverage design decision.
Sergii Khlivnenko The implementation took six weeks from scoping to handover. The system runs on infrastructure the client owns. No ongoing Consysteam dependency, no subscription to a third-party SaaS tool. Total indexed documents at launch: 200+. The team now uses it daily, and senior staff report spending significantly less time answering internal questions.
Zero workflow disruption. 200+ documents. Answers in seconds.
- RAG eliminates hallucination by grounding answers in real documents
- Slack integration means zero workflow change for the team
- Full handover — client owns the infrastructure and can run it independently
The solution Sergii built through Consysteam was a RAG-powered Slack bot trained on the company's entire document library. RAG — Retrieval Augmented Generation — means the bot doesn't hallucinate answers. It retrieves the actual relevant document chunks and generates a response with source citations. The team gets a cited answer in seconds without leaving Slack.
Posted in : AI Operations
