AI Chatbots & Copilots
Support that resolves, not deflects
A chatbot that cannot see an order is a search box with a personality. We connect the assistant to the systems that hold the answer — CRM, order management, billing, docs — so it can tell a customer where their order is, process the return, or hand over to a human with the full context attached. In-product copilots use the same spine, scoped to what the signed-in user is allowed to see and do.
$ run --trace --budget 0.05
14:02:11.204plandecompose → 3 steps124ms
14:02:11.328retrievepolicy/returns#4 · score 0.91318ms
14:02:11.646tool:crmgetOrder(#48210) → shipped412ms
14:02:12.058tool:omscreateReturn(#48210) → RMA-7741377ms
14:02:12.435verifygrounded ✓ · citations 2/2 · policy ✓88ms
14:02:12.523respondstreamed 412 tokens · $0.0041.2s
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- Assistant trained on your knowledge base with citation-backed answers
- CRM, OMS and billing integrations for real account-level answers
- Escalation to human with transcript, intent and suggested resolution
- Deployment across web, mobile, WhatsApp and in-product surfaces
- Analytics: deflection rate, resolution rate, CSAT, top unresolved intents
- Brand voice and refusal behaviour defined and tested
- 01
Mine real conversations
Historical tickets and chats tell us which intents carry the volume.
- 02
Connect the systems
Account-level answers require real integrations, not a FAQ scrape.
- 03
Design the handover
The escalation path is designed first, because it is what protects the customer.
Web, mobile app, WhatsApp Business, email and in-product surfaces, from one assistant definition so behaviour stays consistent across channels.
It says so and escalates. A confident wrong answer costs far more than a handover, so refusal behaviour is defined explicitly and tested in the eval suite.