Use cases
Same playbook, your vertical
OpenChat is built around grounded retrieval plus optional tools. These patterns repeat across industries—swap documents, locales, and API integrations for your brand. Below, each use case includes practical implementation guidance plus a live widget-style experience.
Vertical
Car rental & mobility
High-touch, policy-heavy, and inventory-bound—rental is a natural fit for grounded assistants plus API-backed checks. The same console pattern works for dealers, sharing platforms, and franchise groups.
The public demo site mirrors a full rental journey: vehicle classes, add-ons, and a booking handoff the assistant can discuss in natural language. Your production workspace wires the same pattern to your real availability and contract text.
Operators still use chat ops and tickets for edge cases, but the bulk of “what’s available?” and “what does this cost?” is resolved from your rules and live checks instead of a script tree.
- Live fleet and class availability for date ranges and stations—verified against your rental or telematics stack, not generic text.
- Deposits, mileage, insurance tiers, one-way fees, and seasonal rules—answered from your contracts and help content, with escalation paths you control.
- Multilingual desk, web, and chat: one knowledge base per brand with locale-aware retrieval so NL/EN/DE (or any mix) stays consistent.
- Faster handoffs: when an agent takes over, they see what the assistant already checked so customers don’t repeat themselves.
Car rental widget demo
Vertical
Restaurant
Menus, allergens, hours, and policies change often—guests expect instant, accurate answers and simple actions without calling the desk.
The live demo shows a hospitality-style site where the chat matches your tone and menu story. In production, you replace placeholder content with your own PDFs, site copy, and booking connections.
When you connect booking or table APIs, the assistant can move from “what’s gluten-free?” to “move my 7pm to 7:30” in one thread—always within the tools you enable.
- Ground replies in your menu PDFs, site, and house rules so dietary questions and specials match what you actually serve.
- Reservations and changes through governed tools when you connect booking or POS APIs—book a table, modify a time, confirm party size.
- Peak-hour volume: same agent handles “are you open Monday?” and “can I move my booking?” without losing thread context.
Maya - Restaurant assistant
Demo chat replay
Vertical
Marketing agency (reseller)
Run many clients on one platform—per-tenant knowledge, tone, and tools so each brand feels native, not generic.
The agency demo is a thin campaign-style surface; your real value is one console with isolated workspaces, white-label options, and economics you choose with your sales team.
Each client gets the same RAG and actions building blocks, so you standardize delivery without copy-paste consulting for every new vertical.
- Isolate brands with separate knowledge and access; scale onboarding as you add accounts.
- Reseller-friendly economics: pair with whitelabel to earn commission or set your own end-customer prices with sales.
- Reuse patterns—RAG plus actions—across verticals without rebuilding from scratch every pitch.
Jordan — Platform guide
Demo chat replay
Vertical
E‑commerce webshop
Product detail pages and policies don’t cover every edge case—your agent fills the gap with retrieval plus live checks where integrated.
The e‑commerce demo highlights catalog browsing with a path to answers that go beyond the PDP. Connect order and stock tools so “arrives by Friday?” is grounded in your systems, not a guess.
Returns, SLAs, and cross-border rules stay in your policy documents; the assistant cites them, and your team can still take over or open a ticket when a case needs a person.
- Answers from your catalog copy, shipping, and return docs; fewer “I’ll get back to you” tickets.
- Order status, stock, and eligibility via tools when APIs are connected—so “Is SKU‑4821 in stock Friday?” is verified, not guessed.
- Returns, exchanges, and warranty flows grounded in policy text with clear escalation when a human must decide.
Alex - Store assistant
Demo chat replay