An architecture for Wiseway's first two AI assistants — the Knowledge Assistant and the Sales Quoting Assistant — that delivers fast value today and is unlikely to need rebuilding as the AI industry evolves.
Rather than picking a single vendor — Microsoft, Databricks, Snowflake — and accepting whatever they offer, we build on the open standards the AI industry agreed upon in late 2025. Five small components, each replaceable, together delivering one coherent platform. Click any card to see what it does.
Click any box to see what it does, in plain English. The shape repeats for every future agent — Customer Service, AP, AR, Reporting — so you scale by writing new playbooks on the same foundation, not by adding new platforms.
Two agents, one foundation. The Knowledge Assistant proves the architecture is real; the Sales Quoting Assistant proves it is commercially valuable. Both reuse the same connectors, the same identity flow, the same audit trail.
Staff ask HR or SOP questions in Teams, by email, or on the web. The assistant retrieves the right policies from SharePoint, answers in plain English, and cites the source document.
The safety property that matters: the assistant only ever sees documents the person asking is already entitled to see. If you remove someone from a permissions group on Monday, they immediately stop getting answers from documents they no longer have rights to.
An RFQ arrives. The agent reads it, looks up current rates and surcharges from a governed rate-card store, applies client-specific terms, and drafts a quote in your branded format.
The rep always sends. Below-margin quotes are flagged for manager approval in Teams. Every rate used and every approval is logged with full audit trail — the SHEIN-style wrong-rate scenario is prevented by design, not by good intentions.
In the last eighteen months the AI industry has agreed on a small set of open standards — the way it once agreed on Wi-Fi, SQL, and HTTP. The most important one was donated to the Linux Foundation in December 2025, and is now backed by every major AI lab and cloud provider. History tells us that when this kind of consolidation happens, the open standard wins the long run, and proprietary platforms eventually rebuild around it.