Capture value with an AI Agent Native Billing System

75% of AI companies struggle with billing and pricing their agents. Paid gives you the flexibility, automation, and control that todayʼs AI economy demands.

Traditional billing systems are not built for the AI agent economy

75% of 160 agentic companies we spoke to struggle with billing for their agents due to:

Rigid Pricing Structures

Agents don't fit into seats or per-user SKUs - they scale beyond.

Unpredictable Unit Costs

Workloads make it impossible to predict spend or protect margins.

Misaligned Pricing Models

Agents deliver outcomes - but legacy billing charges for inputs.

Invisible Value at Renewal

Without clear reporting, customers can't see the ROI - and churn.

“We were using a cobbled-together solution of three different systems until we found Paid. Now our entire billing infrastructure runs on a single platform.”

- AI Agent Founder

Paid is the innovator in billing and pricing agents

We've identified 4 successful models:

FTE Replacement Model

Price per Agent

Turn your agents into teammates that are always on. This model positions your AI agents as digital employees, each being a fractional replacement for a junior hire or a portion of a full-time employee (FTE).

Key Characteristics

•Fixed monthly fee per agent deployed
•Value proposition tied directly to headcount spend
•More predictable cost for your customers' budget.

Best For

AI agents handling broad responsibilities or entire job functions with consistent, predictable workloads where savings from taking over the function are clear.

Companies using this model:

Consumption Model

Price per Action

Scales with usage-based pricing, inspired by cloud infrastructure and Business Process Outsourcing shops (BPOs). Your customer pays everytime your agents performs a discrete action.

Key Characteristics

•Often appears as token consumption with a margin on top
•Sometimes manifests as per-minute pricing
•Direct correlation between usage and cost

Best For

Agents performing varied, discrete tasks with unpredictable frequency or volume.

Companies using this model:

Process Automation Model

Price per Workflow

Monetize complete workflows–not just tasks. This model lets you charge when your agents complete multi-step tasks that deliver specific intermediate outcomes.

Key Characteristics

•Value tied to process automation rather than just task execution
•Pricing based on completed workflows rather than individual actions
•Each workflow represents a chain of related and useful tasks (e.g., conducting research, composing and sending emails, or handling a conversation)

Best For

Agents that execute multi-step processes with clear intermediate deliverables, and as a step towards pricing per outcome.

Companies using this model:

Results-Based Model

Price per Outcome

Charge for the results you know your agent is capable of. A clear and compelling option for your customers, this model charges for completed objectives and delivered results. No results - no charge.

Key Characteristics

•Charges based on completed jobs or achieved results
•Can be standardized outcomes or bespoke per customer
•Directly aligns price with business value delivered

Best For

AI applications with predictable performance and clearly defined success metrics in markets that already expect it.

Companies using this model:

Which pricing model is right for your agent?

Not sure where to start? We can help you pick a model that will provide the most value for you and your customers

QUESTION 1

Is your product mostly reducing headcount costs?

Listen to Our Podcast

So, so we decided to switch our model to outcome based pricing. When we introduced the product, we didn't necessarily have that in mind, but it was quickly, it became obvious pretty quick that that was the best way to go.