Customer Support Chatbot
Handle 80% of tickets automatically, 24/7
Deploy a conversational agent that resolves common support queries — order status, returns, account issues — without human intervention. By routing only edge cases to human agents, you reduce average handle time and support headcount while improving response speed.
GPT-6 Luna
for 2M tokens a month · 60% input / 40% output
Why this model
For this workload — 2M tokens a month, 60% of them input — it comes to about $0.52 a month, the lowest of the models suggested here.
Alternative models
Implementation tips
- 1
Keep your system prompt under 500 tokens and use a knowledge base retrieved via RAG rather than stuffing all product info into the prompt — this slashes per-call cost by 40–60%.
- 2
Add a confidence threshold: if the model scores the query below 0.7 certainty, escalate to a human automatically rather than risking a hallucinated answer.
- 3
Cache your static system prompt using provider context-caching APIs to save on input tokens for every conversation turn.