Small Business: $1,500/month (up to 500 customers)
Growth: $5,000/month (up to 2,500 customers)
Scale: $15,000/month (up to 10,000 customers)
Why it works: SaaS companies want predictable costs tied to their customer base size
When to choose agent-based pricing
✅ Your agent performs a comprehensive set of tasks replacing a job function
✅ Customers want budget predictability from headcount allocations
✅ You can demonstrate clear FTE replacement value
✅ Competition prices on seat-based models
✅ You want to avoid race-to-bottom pricing pressure
⚠️ Future-proofing tip: As LLM costs drop 10-100x, shift your value prop from "cheaper than human" to "vastly more capable than human"
⚡ Action-based pricing
Action-based pricing charges customers for every discrete action their agents perform.
Used by agentic companies like Bland and Parloa, this consumption model mirrors cloud infrastructure and BPO pricing.
It's transparent but vulnerable to commoditization as AI costs decline.
How It Works
Pricing principles
Transparent Consumption: Direct correlation between usage and cost
Low Barrier to Entry: Customers only pay for what they use
BPO Competition: Target the $900/employee BPO market
Volume Discounts: Incentivize higher usage with tiered pricing
Implementation guide
Step 1: Calculate unit economics
Determine base LLM/infrastructure costs
Add 50-300% margin based on value delivered
Build in cushion for future cost reductions
Step 2: Define billable actions
Real-World Examples
Example 1: AI Voice Agent (Bland.ai Model)
Agent: Call AI
Functionality: Handles inbound customer service calls
Pricing Model:
$0.12/minute for inbound calls
$0.18/minute for outbound calls
Volume discounts: 10% off at 10,000 minutes/month
Why it works: Direct competition with call centers at 70% lower cost
Example 2: Document Processing Agent
Agent: Document parsing AI
Functionality: Extracts data from invoices, receipts, contracts
Pricing Model:
$0.10 per page processed
$0.02 per data field extracted
Bulk pricing: $500 for 10,000 pages/month
Why it works: Clear unit economics vs. manual data entry costs
When to Choose Action-Based
✅ Competing directly with BPOs or call centers
✅ Highly variable usage patterns
✅ Customers want "pay only for what you use"
✅ Simple, discrete, measurable actions
✅ Testing market fit with low commitment
⚠️ Warning: This model faces the highest pricing pressure as AI costs plummet. Plan to transition to workflow or outcome-based pricing within 12-18 months.
⚙ Workflow-based pricing
Workflow-based pricing charges for complete sequences of agent actions that deliver specific intermediate outcomes.
Companies like Rox, Salesforce, and Artisan use this model to balance between pure consumption and outcome pricing. Each workflow represents a meaningful business process with clear deliverables.
How It Works
Design Principles
Process-Level Value: Price complete workflows, not individual actions
Clear Deliverables: Each workflow produces measurable intermediate outcomes
Margin Management: Monitor workflow costs to avoid negative margins on complex processes
Implementation Guide
Step 1: Map your workflows
You want to identify the actions and assign some values to the steps.
Identify all discrete actions your agent performs
Estimate resource consumption per workflow
Assign business value to each workflow
Step 2: Design pricing structure
Here, you set prices to cover your margins and costs.
Set base platform fee (covers overhead)
Price each workflow based on:
Computational cost
Business value delivered
Market alternatives
Step 3: Add commitment tiers
Commitment tiers and included quantities are easy ways to force a minimum revenue, but they can backfire if you don’t explain to your customer what they get.
Here’s how you set them in Paid:
Priced at $0.05 per record, with a minimum of $500 a month (10,000 included), and $0.20 for any overage.
Real-World Examples
Example 1: Sales Development Representative (SDR) Agent
Why it works: Sales teams can start small and scale with success
Example 2: Financial Analysis Agent
Agent: Automated CFO Assistant
Hybrid setup:
Base platform fee: $5,000/month
Workflow Pricing:
Report creation: 20 included, $100 for every overage
Cash Flow Forecast: $250 per forecast
Budget vs Actual Report: $50 per department
Board Deck Generation: $500 per deck
Real-time Dashboard Update: $25 per refresh
Optional volume discounts: 20% off after 50 workflows/month
Why it works: Finance teams have varying needs throughout the month/quarter
When to Choose Workflow-Based
✅ Your agent executes multi-step processes with clear deliverables
✅ Workflows are standardized but complex enough to avoid commoditization
✅ You can demonstrate ROI for each workflow type
✅ Different workflows deliver different business value
✅ You want pricing flexibility between action and outcome models
⚠️ Watch Out For:
Complex workflows (document parsing, security scans) risk negative margins. Make sure you segment your workflows for length or complexity to avoid having your margins crushed. Monitor costs carefully to maintain profitability!
🎯 Outcome-based pricing
Outcome-based pricing represents the pinnacle of value-aligned pricing and the model most resistant to commoditization.
Companies like Zendesk, Intercom, Airhelp, and Chargeflow charge only for successful business results. As we note in our frameworks article with Kyle Poyar,, this model will likely dominate as AI costs plummet.
It's the only model that completely decouples pricing from underlying technology costs.
How It Works
This model is similar to the workflow-based pricing model. Even though you can combine it with a platform fee and others, you should avoid pricing individual “attempts”.
Has there been success? Bill.
No success? Don’t charge.
The outcome-based pricing model is similar to workflows, but only bills the customer when an outcome (or outcomes) have been reached.
Design Principles
Results-only focus: Charge only for achieved outcomes, not attempts.
Clear attribution: Develop robust methodologies to prove your impact
Shared risk AND reward: Include performance guarantees or success bonuses, like revenue share.
Premium positioning: Command highest prices through guaranteed results
Future-proof: This model is the most resistant to AI commoditization
Implementation guide
This model is the trickiest to get right, so follow carefully!
Step 1: Define success metrics
These must be objectively measurable
Directly tied to business value for best success
Step 2: Calculate Risk-Adjusted Pricing
Estimate success rate of your agents
Add risk premium (typically 30-50% with most of our customers)
Include a base platform fee to cover operational costs if no success is reached
Setup in Paid is similar to the workflow setup, but prioritizes outcomes and not just actions.
Real-World Examples
Example 1: Recruiting Agent
Agent: Automated Recruiter
Base Fee: $2,000/month (platform access, unlimited searches)
Outcome Pricing:
Qualified Candidate Submitted: $500
Interview Scheduled: $1,000
Offer Accepted: $5,000 or 15% of first-year salary
Success Metrics:
Interview: Candidate completes first round with hiring manager
Offer Accepted: Candidate signs offer letter
Why it works: Recruiting is already outcome-based; AI agent follows industry model
Example 2: E-commerce Optimization Agent
Agent: Conversion Rate Optimizer
Base Fee: $500/month (A/B testing infrastructure)
Outcome Pricing:
Conversion Rate Improvement: $2,000 per percentage point
Revenue Increase: 5% of incremental revenue
Cart Abandonment Reduction: $50 per recovered cart
Success Metrics:
Conversion: Measured via integrated analytics, 30-day attribution
✅ You want maximum pricing power and differentiation
✅ You're confident in your agent's performance
💡 Tip: This is the most future-proof model. As AI costs approach zero, outcome-based pricing maintains margins by focusing on value delivered, not resources consumed.
💡 Paid’s best practices for agent monetization
1. Start simple, evolve sophisticated
Launch with agent-based pricing
Add usage components as you learn
Introduce outcomes once proven
2. Transparency builds trust
Real-time usage dashboards
Clear billing breakdowns and value receipts
Proactive cost alerts
Paid’s value receipt with Human Equivalent Value helps cement your agents’ value in a transparent way.
3. Price for value (not cost)
Research alternative solutions
Understand customer budgets
Price below human equivalent
Leave room for discounting
4. Monitor and iterate - experiment frequently
Track key metrics:
Customer acquisition cost
Lifetime value
Churn rate by pricing model
Usage patterns
A/B test pricing changes
Survey customers quarterly - not just those who churn
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