Deal Copilot & Sales Memory
An AI-powered CRM companion that tracks chronological deal interactions, automatically scores 'Deal Temperature', and dictates exact next steps based on your sales SOPs.
Impact Summary
The Problem
Enterprise sales cycles are long and complex. Reps lose track of what was said 3 weeks ago, fail to identify hidden stakeholders, and often miss critical security blockers until it's too late.
This automation acts as a persistent 'Sales Memory'. It ingests every deal interaction, compares it against previous states, and uses an LLM to automatically score deal momentum. It then cross-references your internal Sales SOPs to generate concrete, prioritized next steps for the rep.
±40 pts
Dynamic temp scoring
100%
SOP compliance
How the workflow runs end to end
From raw data to booked meetings in 4 autonomous steps
Context Aggregation
Reads three Google Sheets simultaneously: the raw chronological interaction logs, the internal Sales SOP rules, and the previous 'Deal Memory' state.
Deal Grouping & Sorting
A JavaScript node filters and groups all interactions by Deal ID, compiling a complete, chronological transcript of every touchpoint for the AI to analyze.
AI Temperature Scoring
OpenAI analyzes the transcripts to calculate a dynamic 'Deal Temperature' (0-100), extracting specific stakeholder sentiments and identifying hidden blockers.
Memory Update & Next Steps
Generates concrete, SOP-backed next actions (with owners and deadlines) and writes the updated state back to the Deal Memory tracker.
Before vs After
The Old Way
- Reps forgetting past call details
- Subjective, gut-feeling pipeline forecasting
- Sales SOPs living in unused PDFs
- Missed follow-ups on critical blockers
The Automated Way
- Persistent chronological deal memory
- Mathematical momentum scoring (Cold/Warm/Hot)
- SOPs automatically enforced via LLM prompts
- Actionable, prioritized next steps generated
Under the
hood
Built with modern, scalable low-code tools and enterprise-grade APIs to ensure reliability and speed.