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Multi-agent AI system that automatically classifies and routes your customer support
classifying and routing support tickets with multiple agents is a solid pattern, how do you handle edge cases?
The system is built on a fine-tuned model trained on historical ticket data. For edge cases where the confidence score falls below a threshold, LangGraph kicks in as the agent orchestration layer , the LLM re-evaluates the ticket, determines the most appropriate category, and automatically updates it in your support platform.
Moreover, it has a human review fallback for edge cases where the system cannot confidently identify the ticket - it automatically routes those to a human who can manually review, modify, and route it accordingly, ensuring nothing gets missed.
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Your own secure AI workforce, built on your own data.
Most SMEs pay for one expensive, generalist AI that knows nothing about their business. We're flipping that: a small, focused AI assistant for each department (HR, Accounts, Marketing, Sales, and Operations), each trained on your own business data.
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We're piloting this internally at Indigloo first. If you run an SME and want to see a department assistant in action, DM me. 🚀
For the internal pilot, I'd keep a held-out question set per department and compare RAG alone with RAG plus fine-tuning. Which department do you expect to benefit most from tuning, and what errors would you want it to reduce?