AI chatbots that resolve tickets - not just deflect them.

No-code chatbot builders give you a flowchart with a language model bolted on - fine for FAQ deflection, weak the moment a user asks something the flowchart didn't anticipate. We build bots grounded in your actual product data, docs, and past tickets through retrieval-augmented generation (RAG), so answers come from your source of truth instead of the model's guesswork.

Three layers: RAG grounding so the model answers from retrieved passages instead of memory, confidence thresholds that trigger a human handoff instead of a guess, and evaluation testing against a question set before launch. No chatbot is hallucination-proof, but an ungrounded one and a grounded, tested one fail at very different rates.

Yes - and it should. We design explicit escalation paths (low confidence, negative sentiment, repeated questions, or a direct request) that route to your support queue or a live agent with full conversation context attached, not a cold handoff.

Website widget, WhatsApp, Slack, Microsoft Teams, and in-app are all standard integrations. The conversation logic and RAG layer are channel-agnostic, so we build once and deploy to whichever channels your users actually use.

Resolution rate (queries closed without escalation), containment rate, and CSAT on bot-only conversations, tracked from week one. We define the baseline before launch so you're looking at measured performance, not a demo that looked good once.