Recommend menu bundles and promos based on sales data

An AI system that studies your sales and feedback data, then suggests menu bundles and promos to customers automatically.

How the work actually flows

A straight line. Runs once per each menu item, daily.

Pattern: Sequence (1) ยท Multiple Instances with a priori Run-Time Knowledge (14)

flowchart TD trig>"customer messages ordering bot"]:::trig s0[("look up sales and feedback data")]:::store s1["build bundle and promo suggestions"]:::task s2["ai writes personalized reply"]:::svc s3[["rescore every menu item daily"]]:::mi trig --> s0 s0 --> s1 s1 --> s2 s2 -->|"one per each menu item, daily"| s3 out[/"personalized bundle recommendation sent"/]:::out pay{{"higher order value with no manual analysis"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepAn outside serviceRuns once per itemA record or sheetResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAG
Connects
TelegramOpenAIPineconeDeepSeekPostgreSQL
Featured in

The problem it solves

You know some dishes sell better paired together, but you don't have time to study transaction reports every week. Meanwhile customers get generic menus instead of offers based on what people like them actually order.

Who it fits

Restaurant, cafe, or food and beverage business owners who want smarter menu offers without manual analysis.

How it works

  1. A customer messages your Telegram ordering bot
  2. The system looks up sales, feedback, and ingredient data for the menu they mention
  3. It builds bundle and promo suggestions based on what sells well together
  4. An AI assistant writes a friendly reply recommending the bundle
  5. In the background, it re-scores every menu item daily and updates recommendations
What you get

Bundle orders diners say yes to

You get fresh bundle and promo ideas served up automatically, tailored to what your customers actually enjoy ordering together.

What you get

Personalized bundle and promo suggestions sent to customers, plus ongoing menu performance scores.

What you need

A database of your menu and sales data, a Pinecone account, an OpenAI or DeepSeek API key, and a Telegram bot.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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