Deal Scoring & Call Coaching for B2B Sales
B2B SalesScoring a $50M pipeline for intent, urgency and blockers, and coaching calls against a rubric, with every high-stakes call left to a human.
Overview
A B2B sales organization running a $50M pipeline across two CRM pipelines and sixteen stages wanted AI-scored deal intelligence and call coaching, without a model deciding which deals got resourced. Canvas Labs Partners built a two-agent suite that reads the unstructured record and hands a ranked, rule-governed priority stack to the people who own the number.
7 modules shipped
across scoring, coaching and routing
$50M pipeline scored
deal intelligence across two CRM pipelines and sixteen stages
No verdict left to the model
hard rule overrides decide every high-stakes call
Challenge
Leadership wanted AI-scored deal intelligence and call coaching, and would not let a model make the final call on which deals got resourced. On a live deal a wrong verdict is not a bad suggestion, it is a lost commission. The intelligence had to be useful enough to act on and never authoritative enough to decide.
Solution
The first agent reads the unstructured record. Running on OpenAI o4-mini, it extracts intent, urgency and blockers from deal notes and call transcripts, pulling that material in through the CRM API and a call-intelligence API, with JSON-schema validation holding every extraction to a fixed shape before anything downstream reads it.
The second agent is fully deterministic. It combines those signals with rule-based scores into a five-tier priority stack, and hard rule overrides mean the model never has the last word on where a deal lands. A consent veto blocks re-engagement for opted-out contacts outright, and call coaching is scored against a hundred-point rubric with product references grounded by retrieval.
Three of the seven modules carry no model at all. Forecasting, rep scorecards and lead routing were built deliberately LLM-free, because the business needed numbers that reproduce exactly from one run to the next. The suite is split along that line: language models where judgment helps, plain rules where the figure has to be the same every time.
Results & benefits
Seven modules shipped across scoring, coaching and routing, covering a $50M pipeline that runs through two CRM pipelines and sixteen stages. No high-stakes verdict is decided by the model alone: the five-tier priority stack is produced deterministically and hard rules override it. Three of the seven modules run without a model at all, so the numbers leadership reports reproduce exactly. Leadership got the AI-scored deal intelligence and call coaching it asked for, and the decision about which deals get resourced stayed with the people who carry the number.
Customer
B2B sales organization
Services
- Agentic AI consulting & development
- Deterministic scoring & rules engineering
- CRM & call-intelligence integration
Tech stack
About us
Canvas Labs Partners is a software consulting team that designs and ships production agentic AI systems: multi-agent pipelines, tool-calling architectures, and human-governed automation, together with the trading infrastructure, blockchain, mobile, and product engineering those agents plug into. We publish our work as a case ledger rather than a portfolio, so every claim on this site links to the engagement behind it. Engagements follow the same four-step discipline, Map, Bound, Instrument and Govern, whatever the stack, and every entry in the ledger carries a result we are willing to be measured against.
Delivered individually, in a prior role, by one of Canvas Labs Partners’ founding team members. Not by the firm itself.
Have a system like this one?
We built this one end to end. If you are facing something similar in b2b sales, book a free discovery call and we will tell you what it would take.