Having evaluated numerous SaaS analytics platforms, I find MeetGeek's pricing model, like many others, employs a tiered "per seat" structure that isn't immediately transparent. The core confusion stems from what constitutes a "seat" versus a "license," and how features are gated across tiers (Starter, Pro, Business). Based on my team's procurement process and a detailed review of their current pricing page, here is a breakdown.
The fundamental unit is the **host seat**. Anyone who needs to *schedule* meetings where MeetGeek will be the designated recorder requires a paid seat. However, the model is not strictly 1:1 for consumption. Key nuances include:
* **Attendee Access vs. Editor Roles:** Guests or regular attendees who simply receive summaries or recordings do **not** count as seats. The cost escalates when you require team members to have editing capabilities—for example, to highlight key moments, edit transcripts, or manage the knowledge base. These are often termed "editor seats" or "contributor seats" in higher tiers.
* **Tiered Feature Allocation:** The per-seat monthly cost unlocks different ceilings of usage and features **per seat**, not per account. For example:
* **Starter:** A seat might include AI summaries and transcripts, but with a monthly cap on total recording minutes *per user*.
* **Pro/Business:** The cap increases or is removed, and features like video recording, custom branding, and advanced integrations (e.g., Slack, Notion) become available. Crucially, some tiers grant access to "Shared Libraries," but editing rights for that library may require the more expensive seat type.
* **The "Team" vs. "Company" Distinction:** Lower tiers are often limited to a single "team" (a defined group of hosts). Scaling to multiple teams across the organization typically forces an upgrade to a "Business" or "Enterprise" plan, which carries a significantly higher per-seat cost but enables cross-team knowledge management.
From a data pipeline perspective, consider the cost implications for exporting data. While basic CSV export might be included, automated webhook integrations or direct API access for piping meeting metadata, transcripts, and analytics into a data warehouse (like BigQuery or Snowflake) are typically locked behind the highest tiers. This is a critical consideration for building reliable data products from meeting intelligence.
A practical example of cost calculation:
Let’s assume a 10-person engineering team needs meeting intelligence.
- Scenario A: Only 3 people schedule meetings requiring recording. They need basic summaries and transcripts. → You likely need **3 Pro seats**.
- Scenario B: Those same 3 schedulers, but now 5 other team members need to actively highlight and tag key moments across all recordings for a knowledge base. → You now need **8 Pro seats**, as the editors consume a seat.
- Scenario C: The above, plus you need to send all raw transcript data to your data lake for NLP analysis. → You now require **8 Business seats**, a substantial cost jump.
The salient point is that "per seat" is better understood as **"per privileged user,"** where privileges are defined by the need to schedule *or* edit/curate. Always map your anticipated user roles (Scheduler, Editor, Consumer) directly to the feature matrix of each tier before estimating costs. The headline per-seat price is rarely the final landed cost for a functional team deployment.
--DC
data is the product