Should You Build Your Own Agent Billing System? (Probably Not)

You added agents to your previously seat-based SaaS product. Now you need to bill for them. Should you build billing infrastructure or buy it?

This guide helps you decide in under 10 minutes.

The 60-second decision test

Answer these three questions:

1. Do you need to bill for agents in the next 90 days? → YES: Buy a platform. Building takes 6-12 months. → NO: Continue to question 2.
2. Can you dedicate 2-3 engineers full-time to billing for a year? → NO: Buy a platform. You can't build this as a side project. → YES: Continue to question 3.
3. Do you have unique margin optimization needs? → NO: Buy a platform. The ROI doesn't justify building. → YES: You might be a candidate for building. Read on.

Why agent billing is different

Your SaaS billing won't work for agents. Here's why:

SaaS billing typically assumes

Agent Reality

Fixed number of seats

Variable agent deployment (2 to 30+ per customer)

Predictable usage patterns

Autonomous 24/7 operation with usage spikes

Humans trigger actions

Agents make decisions independently

Features drive value

Outcomes drive value

Business hours consumption

Continuous operation across timezones

The bottom line: Forcing agents into seat-based pricing leaves money on the table and confuses customers.

Should you price agents differently than SaaS?

Yes. Companies switching to outcome-based agent pricing see 20-60% revenue increases within 6 months.

1. Why different pricing works:One customer cut seat prices 50% but added outcome fees. Revenue jumped 60% in 90 days.Another went from 20% to 60% YoY growth by switching to outcomes. They won deals from seat-based competitors by proving better ROI.
2. What customers actually want to pay for:Not seats. Not API calls, but outcomes.Meetings booked. Tickets resolved. Documents analyzed. Results delivered.

The true cost of building

Cost Category

Building

Buying Paid

Initial development

$500K - $2M

$0

Time to first invoice

6-12 months

2-4 weeks

Engineering team

2-3 full-time engineers

0 dedicated engineers

Ongoing maintenance

$200K-$500K/year

Included

AI provider integrations

You build and maintain

Automatic updates

Tax compliance

Your team monitors

Automatic updates

Feature development

Months per feature

Configure or request

Year 1 total

$700K - $2.5M

Platform fees only

Year 3 total

$1.1M - $3.5M

Platform fees only

Hidden costs of building:

Edge cases consume you. Custom deals, tax changes, failed payments for autonomous agents.

Maintenance never ends. AI providers change APIs monthly. You track and implement updates forever.

Opportunity cost kills you. Every hour on billing is an hour not improving your agents.

What you actually need for agent billing

Capability

Why It Matters

Build Yourself

Buy Paid

AI cost tracking

Track spend across OpenAI, Anthropic, Google, etc.

Maintain integrations forever

Built-in, auto-updated

Outcome-based pricing

Charge for results, not resources

Design data model, build engine

Configure without code

Margin visibility

Know profitability by customer/agent

Build analytics infrastructure

Real-time dashboards

Value reporting

Prove ROI to customers

Build customer portal

Drop-in components

Fast implementation

Start billing quickly

6-12 months to MVP

2-4 weeks to invoice

Flexible pricing

Change models as you learn

Rebuild when requirements change

Configure on the fly

When to build (<5% of companies)

Build only if you meet ALL these criteria:

1. Genuinely unique billing logicNot "we want custom fields." Your pricing would confuse agent billing experts. Test this by explaining to other agent companies.
2. Dedicated billing team2-3 engineers full-time for years. Not borrowed for sprints.
3. Massive scale / extreme margin optimization needsThis is true for more than $50M annually + margin optimization that impacts millions (think Netflix, OpenAI, etc.)
4. Billing is competitive advantageHow you charge creates differentiation customers care about. Billing innovation is core to your business.
5. Indefinite maintenance commitmentYou'll track AI provider changes monthly. New models, pricing updates, API changes.

If you checked all five boxes, calculate total cost over three years. Compare to buying. Factor in opportunity cost.

Most companies that pass this test still buy when they see the numbers.

When to buy (>95% of companies)

Buy if any of these are true:

• Timeline pressure: Need to bill for agents within the next 3 months.
• Common pricing patterns: Outcome-based, workflow-based, or hybrid models. Most agents fit these.
• No dedicated resources: Engineering should focus on product, not billing infrastructure.
• Multi-provider needs: Agents use OpenAI, Anthropic, Google, specialized APIs.
• Margin visibility required: Need to understand profitability without building BI infrastructure.

How to evaluate agent billing platforms

Use this checklist when evaluating:

Must-have capabilities

1. ☐ AI-native architecture Built for agents from the ground up, not retrofitted from SaaS billing.
2. ☐ Agent-specific primitives Signals, workflows, outcomes. Not just "users" and "API calls."
3. ☐ Outcome-based pricing Native support without custom development.
4. ☐ Real-time cost tracking Across all AI providers with automatic updates.
5. ☐ Fast implementation 2-4 weeks to first invoice, not months of professional services.
6. ☐ Margin visibility By customer, agent, and workflow in real-time.
7. ☐ Flexible pricing models Outcome, workflow, hybrid without code changes.
8. ☐ Automatic tax compliance Updates handled by platform.

Red flags (automatic disqualification)

1. Forces agents into seat-based pricing
2. Requires months of professional services
3. No AI provider cost tracking
4. Can't support outcome-based pricing
5. No agent-specific primitives

The hybrid trap

Some teams try to split the difference. Build part, buy part.

I've been there, and this usually fails.

Why hybrid doesn't work:

You maintain integration points between systems. You need deep billing expertise for both. You inherit complexity of building AND constraints of buying. However, edge cases fall into gaps - debugging spans your code and the platform and then extends into RevRec systems, ERPs, and data warehouses for analytics.

When changes touch multiple systems, you are trapping yourself in maintenance hell.

The only exception:

Buy core billing engine. Build thin customization layers on top through APIs.

This requires clear boundaries and discipline, and incredible depths in the business processes both for the now and the future. Most companies let customization spread until they've rebuilt half the platform.

What Paid offers

We built Paid specifically for agent billing after seeing companies waste months building what exists.

Launch faster

• Outcome, workflow, hybrid, and FTE pricing models
• 2-4 weeks from integration to first invoice
• Works with LangChain, CrewAI, major frameworks

Manage margins

• Real-time cost tracking across AI providers
• Profitability by customer, agent, workflow
• Alerts when margins drop

Show value

• Customer-facing dashboards
• Human value equivalent calculations
• Automated value reports for renewals

Iterate on pricing

• Change models without migrations
• Configure without code
• Custom terms preserved automatically

Some of the frequent questions we've heard

Q: Can we build an MVP and add features later?

This is the most common mistake. The MVP never stays minimal. I've personally spent 3 years building billing systems for SaaS and B2C companies - it will eat up 8-14 engineers' time and you'll spend 3-4 months building, then discover you need tax compliance, dunning logic, outcome attribution, margin tracking, and dozens of other features.

Companies going this route end up rebuilding after 6-12 months. By then, you've lost a year of proper monetization.

Q: Our billing is unique. Won't a platform limit us?

Paid supports outcome-based, workflow-based, hybrid models, and custom signals. Most "unique" requirements are configurable, not custom.

Test this: explain your requirements to other agent companies. If they understand you, a platform can handle it.

Q: Should we really price agents differently than SaaS?

Yes - a thousand times yes! Companies switching to outcome-based pricing see 20-60% revenue increases within 6 months.

Seat-based pricing breaks when customers deploy variable numbers of agents. Outcome-based pricing aligns revenue with value delivered.

Q: What about vendor lock-in?

Paid uses standard APIs and exportable data formats. Your usage tracking uses OpenTelemetry.

The real lock-in is building yourself. You're locked into your technical decisions, team expertise, and maintenance burden forever.

Q: How do we convince our CTO not to build?

Show the numbers:

Total cost over 3 years to build and maintain vs buying.

Opportunity cost of engineers on billing instead of product.

Time to revenue: 2-4 weeks vs 6-12 months.

Ask: is billing where we want our best engineers focused?

Q: Can we start with a platform and migrate to building later?

Yes. Lower risk than building first.

Start billing quickly with Paid. Learn real requirements. If you discover truly unique needs, migrate with real data.

Most companies never need to migrate. The platform handles everything as they grow.

Q: How does outcome-based pricing affect revenue?

Data shows 20-60% increases within 6 months.

Pricing aligns with value. Customers deploy more agents when pricing makes sense. Renewals improve because ROI is clear.

One customer cut seat prices 50%, added outcome fees, and saw 60% revenue jump in 90 days.

Q: What if we already have SaaS billing?

Your existing SaaS billing probably won't handle agents well. Seat-based systems break with variable agent deployment. Usage-based systems struggle with outcome attribution.

Evaluate whether extending makes sense or if purpose-built agent billing is better. Most companies find agent billing different enough to warrant new infrastructure.

The bottom line

An absolute majority of SaaS companies should buy agent billing infrastructure and not build it. The opportunity cost is massive. The 5% that should build have genuinely unique models, or billing as competitive advantage.

For everyone else, focus engineering on better agents, not billing logic.

Ready to start billing for agents?