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marinarosa 
posted an update Jun 5
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158
I'm participating in the Build Small Hackathon! 💖

I chose the Backyard AI chapter: solve a real problem for someone you know.

My idea is to help a business owner extract valuable information from their data. She operates, negotiates and provides support for customers all through Whatsapp. She doesn't use Notion, Obsidian, Spreadsheets and does not like doing repetitive data-entry tasks. It's a messy, chaotic messaging workflow that kind of works for her now.

What if she could open a Space, upload her exported WhatsApp data, and a fine-tuned model tailored to her business domain and conversation style extracted, classified, organized all her customers and deals into a coherent dashboard, along with a chatbot for her to ask questions about her business? That's my current approach.
marinarosa

What have I done so far:

  • Checked Modal pricing since we've received credits for the hackathon. Initially I wanted to use it for inference servers for my coding agents, but It could be prohibitive in terms of costs. I will use it primarly to host @OpenBMB-LLM MiniCPM-o 4.6 (1.3B) model for testing, dataset curation and possibly fine-tuning tasks.

  • The business owner provided me 10 raw WhatsApp exports from her most valuable (ROI) and frequent customers. I already have enough data to start.

  • For my main coding agent, I chose Deepseek-V4-Flash model on OpenRouter because I am already familiar with Deepseek-V4 models, they are good at long running tasks and they are very cheap. I'm also going to use it with OpenAI's Codex harness.

  • I interviewed her to narrow down the most valuable use cases for her business. Came up with these, in order of priority/deliverable value:

    1. Auto-built customer CRM card
    • Given a raw WhatsApp conversation export with its media,
    • When the user uploads it to the Space,
    • Then the system extracts the text, the receipt and ticket images, and the whisper-transcribed voice notes, and assembles a structured card per customer (who they are, who is traveling with them, contacts, and the trips discussed).
    1. Payment tracking and reconciliation
    • Given a customer thread that contains payment receipts (PIX/TED) and quotes,
    • When the user opens that customer's card,
    • Then the system shows the total paid, the outstanding balance, and the profit on the sale.
    1. Sales-pipeline status and next action
    • Given a conversation history that reveals where the sale stands,
    • When the user opens a customer,
    • Then the system places them on the funnel (quote, documents, payment, ticketing, travel), lists the remaining steps, and surfaces the single most important action to take next.

    1. Trip summary and reminders

      • Given an uploaded e-ticket or itinerary with a locator, passengers, and flights,
      • When the user processes it,
      • Then the system produces a structured trip, the trip-summary message in her style, check-in reminders, and a calendar (.ics) file.

    2. Reply drafting in her voice

      • Given a LoRA fine-tuned on her real chats,
      • When a customer message comes in,
      • Then the system drafts the next reply in her warm, personal style for the user to review and send.

    3. Voice-note transcription and timeline

      • Given a thread that contains voice notes,
      • When the user opens it,
      • Then the system transcribes each note with whisper and builds a searchable, summarized timeline of the relationship.

    4. Document-collection tracking

      • Given a trip whose passengers must each submit RG and CPF,
      • When the user prepares ticketing,
      • Then the system shows which documents have arrived and which are still missing.

    5. Cross-customer dashboard and search

      • Given several customers already processed,
      • When the user opens the overview,
      • Then the system aggregates money, time, and profit and answers plain-language questions such as "who still owes me?" or "which trips depart this week?".

Next Steps:

  • Create the space with a skeleton structure.
  • Set up Codex with OpenRouter + Deepseek V4 Flash
  • Set up MiniCPM-o 4.6 (1.3B) on Modal servers.
  • Write an implementation spec, Gherkin test cases, and AGENTS.md instructions for the actual coding (BDD).
·
marinarosa

Published our space: https://huggingface.co/spaces/build-small-hackathon/vivamais

  • Phase 0 built the project skeleton with uv, ruff, mypy, and pytest, plus the framework free domain core (Money, Customer, Trip, Payment, Message, Document entities and PipelineStage/MessageKind enums). We added application ports as typing.Protocol interfaces, deterministic mock adapters for offline testing, a WhatsApp chat parser handling multiline messages and media placeholders, and a config driven adapter factory wired through a composition root in app.py.

  • Phase 1 delivered four core use case interactors: the CrmCardInteractor for structured customer cards, PaymentReconciliationInteractor for total paid and outstanding balance, PipelineInteractor for pipeline stages and next actions, and TripSummaryInteractor for Portuguese summaries and .ics calendar files.

  • Phase 2 tied everything together with a BuildCrmCard orchestrator and CRM presenter, then added DocumentTrackerInteractor for passenger document readiness, DraftReply for in voice reply generation, and DashboardInteractor for cross customer aggregation and search. All 107 tests pass across 8 passing Gherkin scenarios.
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