AI system case study
An AI account-intelligence workflow for GTM teams.
A seller starts the workflow in the CRM. Minutes later, they receive a ten-section account report and slide deck built from company data, public filings, org data, engagement history, and AI synthesis.
The problem
Account research needed to scale.
Strong account research took days and depended on each seller finding, interpreting, and assembling the same kinds of information. The workflow needed to scale that work and automatically generate the research, discovery questions, value propositions, and even a ready-to-present deck.
What I built
One request starts the complete workflow.
I built an end-to-end account-intelligence engine connected to the CRM. It gathers information from approved sources, organizes it into a consistent ten-section report, and creates the presentation materials the seller needs for the next conversation.
How it runs
From CRM request to seller-ready output.
- Request. A seller checks a box in the CRM or fills out a short form.
- Research. The workflow gathers account, organizational, engagement, and public-company data.
- Synthesis. AI organizes the information into the ten-section report structure.
- Validation. Deterministic checks pressure-test the work at defined points in the workflow.
- Delivery. The system generates the final report and ready-to-present deck.
What I learned
I pressure-tested the workflow with deterministic checks throughout and used AI only where synthesis was needed. The system became more reliable when I matched each part of the work to the right solution.