I want to know whether the proposed price still protects margin.
An AI chat calculates a discount, but does not know last purchase, supplier increase and customer terms.
Bruno connects prices, history and increases, then flags prices to review before quoting.
Sales replies fast without selling at the old price.
Bruno makes this useful by connecting daily interruptions to durable follow-up: message, task, follow-up, approval and memory.
Mobilized foundations- Connected tools: calendar, email, spreadsheets, Drive, lightweight CRM or team messaging feed the file without retyping.
- Action memory: each request keeps its customer, context, received documents, follow-ups and next step.
- Human control: Bruno prepares, sorts and follows up, while sensitive messages and committing actions stay approved.
- Field gain: the goal is not to produce a long report, but to move a real request forward without retyping.
Apply the "Avoid obsolete prices and forgotten discounts" use case in my company context.
- The priority deliverables are produced: Order file, Pricing points, Supplier follow-up, Customer message.
- Assumptions, risks and required human approvals are explicit.
- The result is reusable by the team, as in the Materiaux Pro Sud, distributor for tradespeople example.
Info to clarify
- What is the exact context of your company, customer or project?
- Which documents, data or conversations can Bruno use as a starting point?
- Which deliverables do you want first, and which ones can wait?
- Who must approve the result before any external action is launched?
A major customer asks for annual pricing on twenty SKUs. Meanwhile, two suppliers raised prices and an exceptional discount was granted last year.
Bruno surfaces old prices, spots supplier increases and prepares a grid with margin alerts. The owner validates exceptions before sending to sales.
Created agents
- Order agent
- Margin agent
- Transport agent
Delivered assets
- Order file
- Pricing points
- Supplier follow-up