AI Insights
The customer-intelligence layer Ray asked for on the call.
"Throw it at the LLM and ask it to analyse."
You said it directly: "we can analyse more data — we just collect as many as we want and throw them into the large language model and ask it to analyse that amount of data." Once Customer 360 unifies the signals, this is the layer that reads across the data and tells your team what to act on.
Runs on Cloudflare Workers AI (edge inference, ~10× cheaper than OpenAI direct, no data leaves Australia) with optional GPT-4 / Claude routing for higher-stakes queries.
Example queries (illustrative)
What your team would actually type in
Customer auto-summary
Pulls Unleashed orders, Klaviyo activity, Review.io reviews and LiveChat history into a one-paragraph briefing the moment the phone rings.
Natural-language search
"Who bought Bed Pads in NSW in March and chatted about delivery?" — written like a question, executed like a SQL query.
Daily morning digest
Auto-emailed summary of yesterday's standout signals: spike in returns by SKU, customer at risk, new high-LTV customer signup, etc.
Pattern detection
Surfaces things no one asked about: customers buying Chair Pads but not Bed Pads (cross-sell), Aged-Care accounts ordering below historical average (early warning).
Data residency + cost
- Default model: open-source Llama running on Cloudflare's Sydney GPUs — your data never leaves Australia.
- Optional escalation to GPT-4 / Claude for complex queries — routed through Cloudflare AI Gateway with full audit log.
- Token budget controls per user role — no surprise bills.
- At Conni's expected query volume (a few hundred queries per day) total LLM cost is in the $20–$50 / month range.