A New Era for AI
For years, adopting AI at scale meant committing to a familiar but punishing set of trade-offs: provisioning servers, paying per-seat licenses whether anyone used the platform or not, and watching infrastructure costs balloon even during quiet weeks. The bigger your team grew, the more you paid, regardless of whether that team was actually leveraging AI. ToothFairyAI is changing that equation. With the launch of its Serverless plan, now the platform's most popular tier, ToothFairyAI has eliminated the infrastructure tax entirely. No servers to manage. No per-license fees. No minimum commitments. You buy intelligence credits from $5, and you pay only for the Units of Intelligence (UoI) you actually consume. This is not a pricing tweak. It is a fundamental reimagining of how businesses should buy, scale, and own AI.
The Problem with Per-Seat Licensing
The traditional SaaS pricing model was built for a world of static tools: dashboards, CRMs, project trackers. In that world, a per-seat license makes sense: every user logs in, clicks around, and derives ongoing value. But AI is not a static tool. It is a dynamic, on-demand resource. Some days your team runs hundreds of queries; other days, none at all. Yet under per-seat pricing, you pay the same monthly fee regardless of usage. A 50-person team might pay $20 per seat per month ($1,000 monthly) even if only 5 people actively use the platform that month. The other 45 seats are dead weight: licenses paid for but never touched. This model penalises growth. It penalises experimentation. And it penalises the very behaviour AI platforms should be encouraging: exploration, iteration, and discovery.
How Serverless Works: Units of Intelligence
ToothFairyAI's Serverless plan replaces per-seat licensing with a consumption-based model built around Units of Intelligence (UoI). A Unit of Intelligence is the atomic measure of work performed by the platform — one query, one analysis, one generated insight. Every action consumes a specific number of UoI, and you only pay for what you use.
The Cost Difference, in Numbers
Consider a mid-sized team of 30 people. Under a traditional per-seat model at $20 per seat per month, the monthly cost is fixed at $600 — regardless of how many people actually use the platform. Under ToothFairyAI's Serverless plan, the team pays only for the UoI consumed. - Light usage (5 active users): Per-seat = $600/month (30 seats × $20) → Serverless = ~$50/month (only UoI consumed by 5 users) - Moderate usage (15 active users): Per-seat = $600/month → Serverless = ~$150/month (only UoI consumed by 15 users) - Heavy usage (30 active users): Per-seat = $600/month → Serverless = ~$300/month (only UoI consumed by 30 users) - No usage (holiday week): Per-seat = $600/month (seats still billed) → Serverless = $0/month (no UoI consumed) Illustrative cost comparison. Actual UoI costs vary based on query complexity and volume.
The pattern is clear: per-seat pricing charges you for the possibility of usage. Serverless charges you for actual usage. In every scenario, Serverless is equal to or cheaper than per-seat — and in low-usage periods, the savings are dramatic.
Getting Started in Under Five Minutes
Switching to the Serverless plan requires no migration, no data transfer, and no downtime. Existing ToothFairyAI customers can switch plans from the billing page with a single click. New customers can sign up, buy $5 in credits, and run their first query before the kettle boils. There are no contracts to sign, no sales calls to schedule, and no procurement forms to fill out. The platform is self-serve from the first click to the last insight. 1. Create a free ToothFairyAI account at toothfairyai.com. 2. Navigate to Billing and select the Serverless plan. 3. Purchase intelligence credits starting from $5. 4. Choose from 60+ ready-made agent templates or start from a blank canvas. 5. Connect your data, tools, and knowledge inside your private Studio. 6. Deploy autonomous agents that run 24/7 on your terms. 7. Monitor your UoI balance and usage in real time from the dashboard.