Meeting Source Tracer
- Description: What is it?
Our product Meeting Source Tracer records meetings, catches cross-team conflict, and traces every claim back to its source.
- Problem: What problem is this solving?
Our product aims to help with cross-functional alignment. This problem includes the fact that during meetings, the PM will often hear similar words/topics from various teams; however, they may have distinct meanings.
- Why: How do we know this is a real problem and worth solving?
Cross-functional collaboration is a critical part of product development, yet misalignment and communication gaps remain common challenges across teams. We interviewed 11 product managers, and 8 of them reported experiencing similar challenges, again showing how lack of effective communication can lead to confusion, delayed decisions, and inefficient execution.
- Success: How do we know if we’ve solved this problem?
First, since our product is primarily B2B, we would track business metrics such as the number of companies onboarded, ARR, and the number of active users within each company. Second, we would track product effectiveness like the number of meaningful conflicts identified during meetings, measured by how many flagged conflicts are actually accepted by employees. Another metric is conflict resolution activity, tracking how frequently employees update the status of identified conflicts (e.g., To Do, In Progress, Resolved).
- Audience: Who are we building for?
Our product is primarily designed for cross-functional teams that regularly collaborate on projects and need to stay aligned across different departments. We chose to focus on fintech companies as our initial target market, where collaboration across product, engineering, compliance, and business teams is especially important.
- What: Roughly, what does this look like in the product?
Our product records meetings and labels every line spoken by who said it and the team that they are on, detect conflict – when two or more teams believe different things our tools will flag it, will allow you to trace any flagged points back to the exact transcript, then allows you to make decisions to select one true source of meaning and retains on the tool the reason why a certain meaning was overturned.
- How: What is the experiment plan?
After building the prototype our experiment plan includes talking with 5 new PMs. From these interviews we will have them walk through the product, speaking their thoughts out loud and providing feedback whether they are likely to use this product over their current manual workflows. Additionally we are going to have some pilot users for the product and track analytics of how many conflicts arise/get solved.
- When: When does it ship and what are the milestones?
Weeks 1–4 – Validation: Test our core workflow using real meeting transcripts and validate conflict-detection use cases with potential fintech customers.
Weeks 5–8 – MVP Development: Build transcript processing, speaker and team identification, AI-powered conflict detection, and source tracing.
Weeks 9–12 – Private Beta: Pilot the product with 2–3 fintech teams and introduce conflict review, resolution tracking, and decision history. Evaluate the usefulness and accuracy of flagged conflicts.
Weeks 13–16 – Limited Launch: Refine the product based on pilot feedback, implement essential security and privacy controls, and launch to initial B2B pilot customers.
We will launch once at least 70% of AI-flagged conflicts are confirmed as meaningful by users during pilot testing, based on a minimum of 50 reviewed conflicts across 2–3 fintech teams, subject to security and privacy readiness.
- Business Plan
Our product will operate as a B2B SaaS platform using a per-seat subscription model, charging companies $20 per user per month. Each subscription includes AI-powered conflict detection, source tracing, and conflict resolution tracking, along with a monthly meeting-processing allowance. For teams that exceed their included usage, we will offer usage-based add-ons for additional meeting-processing hours or for specific features. This hybrid approach provides predictable recurring revenue while allowing us to scale with customer usage.
Idea from the Reading
One idea from the reading that we used was Lenny’s one-pager template to structure our one-pager for our product.
