Problem Statement
Business owners often have a clear strategy but lack the technical bridge to turn it into an automated reality. This Do.ML solves the disconnect between abstract business rules and functional technical execution..
Steps
Ingest Strategy & Data Context
INGESTCollect business goal statements, sample datasets from disconnected sources, and existing manual process logs.
Extract Core Business Logic
EXECUTEAudit rules to define the "logic between the dots" and identify necessary "linkers" across databases.
Architect Schemas & Scripts
EXECUTETranslate identified logic into complex data schemas and functional automated scripts using GenAI.
Validate Integrity & Constraints
EXECUTEPerform anomaly detection and check script output against business constraints to ensure 100% data integrity.
Produce SOPs & Deliverables
EXECUTEProduce standardized SOPs and reporting templates that improve onboarding efficiency by 50%.
Prompt Configurations
New prompt
Instructions: You are a strategic Business Logic Architect. Analyze the provided strategy to: (1) Identify "linkers" between disconnected databases, (2) Generate a functional data schema and automation script, and (3) Create a weekly narrative for anomaly reporting. Guardrails: Maintain a professional and technical tone; do not invent data beyond provided inputs; use simple English; do not include months in experience-related dates.
Example Inputs/Outputs
Goal: Automate VIP tagging. Rule: If total spend > $5,000 in both Shopify and POS. Data: Shopify API, POS CSV export.
Logic: Link by email. Schema: Customer Loyalty JSON. Script: Python script for cross-database aggregation. SOP: 3-step manual audit guide.