Billing Software for AI Companies: 6 Tools Tested for 2026

Your AI product charges per token, per agent action, or per outcome, and most billing software for AI companies still assumes usage looks the same every month.

These six billing platforms handle that variance at very different levels of maturity:

1. Stripe Billing: Best for AI companies starting from zero
2. Metronome: Best for high-volume AI metering
3. Orb: Best for pricing simulation before launch
4. Lago: Best for owning your billing infrastructure
5. Chargebee: Best for combining subscriptions with usage
6. Recurly: Best for scaling past a subscription-only model

Here's what each one handles well, where it falls short, and who it's actually built for.

How I researched and tested these billing software tools for AI companies

I built a working credit-metering setup on the free or sandbox tier where one existed (Stripe, Lago, Chargebee, Recurly), and evaluated Metronome and Orb through their docs, demos, and published architecture, since both are sales-gated.

I also ran a synthetic load test simulating 50,000 usage events in a single hour to see how each platform's aggregation held up under a spike rather than steady traffic.

Two tools didn't make the final list: Paddle, because its usage-billing support is still limited to a beta waitlist as of this writing, and Chargify's standalone brand, since it's now fully absorbed into Maxio and no longer exists as a separate product to test.

• Metering accuracy: Whether usage events reconciled correctly against the invoice, especially after a backdated correction or a mid-cycle plan change.
• Setup time: How long it took to go from signup to a working usage-billing configuration, timed in hours, not days.
• Deployment flexibility: Whether the platform locked me into its cloud, or let me run self-hosted or bring my own infrastructure.
• Pricing transparency: Whether real numbers were published, or whether evaluating cost required a sales call before I could compare anything.
• Failure handling: What happened when a webhook was missed, a payment failed, or a usage event arrived out of order.

This hands-on approach is what surfaced the real differences, like which platforms handle backdated corrections cleanly and which ones require rebuilding usage data by hand.

6 billing platforms for AI companies compared

Disclaimer: Prices are subject to change without notice. Always visit the official company websites for the most up-to-date pricing information.

1. Stripe Billing

What it does: Stripe Billing handles subscriptions, invoicing, and usage-based charges natively inside Stripe, using metered billing to convert reported usage events into line items on a recurring invoice.

Best for: AI companies that already process payments through Stripe and want usage billing without standing up a separate metering platform on day one.

Stripe's metered billing model works off usage records your application reports against a subscription item, and it now sits alongside Stripe's own acquisition of Metronome, which gives Stripe two usage-billing paths under one roof depending on how much metering complexity you need.

Key features

• Usage records reported directly against a subscription, with Stripe handling proration and invoice generation
• Native integration with Stripe's payments, tax, and revenue recognition tools, so usage billing doesn't require a second vendor relationship
• Billing meters that aggregate raw events into a usage total on a configurable schedule
• Test clocks for simulating billing cycles and usage accumulation before going live

Pros

• If you're already on Stripe for payments, adding usage billing is a straightforward extension of your existing setup.
• Metered billing connects directly to Stripe's existing tax, invoicing, and reporting stack.
• The acquisition of Metronome means a credible upgrade path exists inside the same ecosystem once your metering needs outgrow native billing meters.

Cons

• Native usage billing is less flexible than dedicated metering platforms once your pricing logic involves multiple billable metrics, tiered rates, or backdated corrections.
• Complex, multi-dimensional usage models (per-token, per-agent-action, per-outcome) often need custom aggregation logic built on top before Stripe's billing meters can consume them cleanly.
• Real-time enforcement of usage limits isn't part of the billing layer. Stripe tells you what happened; it doesn't decide what a request is allowed to do before it happens.

What users say

Pro: “I like that there's very little work once the customer is set up. It's very easy just to set it and forget it, which makes my life a lot easier. The initial setup was very easy; we created the account and were off and running.” [James L., G2 Review, May 3, 2026]

Con: “The dashboard can feel overwhelming at first, especially with all the advanced features and terminology. There’s definitely a learning curve when setting up subscriptions and understanding how Stripe structures products, prices, and billing cycles. Transaction fees can add up as volume grows, and certain automation features require a bit of technical understanding to fully optimize.” [Austin F., Capterra Review, February 11, 2026]

Pricing

Stripe Billing starts at $620/month on a one-year contract, paid monthly. Its pay-as-you-go option charges 0.7% of billing volume with no recurring fee.

Bottom line

Stripe Billing is the right starting point if you're already processing payments through Stripe and your usage model is simple enough for one or two billable metrics.

Once pricing gets more dimensions than that, you'll likely need to pair it with a dedicated metering or entitlements layer rather than pushing all the logic into billing meters.

2. Metronome

What it does: Metronome meters high-volume usage events and converts them into billable line items, with SQL-based tools for defining custom billable metrics.

Best for: AI companies already running payments through Stripe that need metering built to handle genuinely high-volume event traffic, agent actions, and token consumption.

Metronome's customer list includes OpenAI, Anthropic, and Nvidia, which reflects the kind of usage volume it's built to handle.

Stripe completed its acquisition of Metronome in January 2026, and Metronome's roadmap is now part of Stripe's broader billing strategy.

Key features

• SQL-based metrics that query directly against raw stored events, so pricing can be iterated or backdated without touching the underlying data pipeline.
• Streaming metrics with low-latency alerting on usage-based thresholds.
• A modular pricing engine where rate cards, commits, and credit models act as reusable building blocks across contract types.
• Real-time data sync into the product, data warehouse, and CRM or ERP systems.

Pros

• Proven at genuinely high usage volume, with named AI-industry customers to back it up.
• SQL-level control over metric definitions means pricing changes and backdated corrections don't require touching the data pipeline itself.
• Now backed by Stripe's infrastructure and roadmap, which reduces vendor risk for teams already committed to that ecosystem.

Cons

• Configuring billable metrics and pricing structures requires SQL expertise and real engineering time upfront.
• Bills on a post-usage cycle, counting what happened after usage has been recorded.
• Pricing isn't published, and evaluating cost at your specific volume requires a sales conversation.

What users say

Pro: “Metronome has excellent credit system handling”

Con: “Their discount engine is flexible but honestly took our team longer to configure than we hoped.” [u/DimensionIcy8750, Reddit User Review, July 3, 2025]

Pricing

Metronome does not publish standard plan pricing. It offers a Starter plan with usage-based pricing and a Custom plan for larger businesses, with pricing available by contacting sales.

Bottom line

Metronome is the strongest option if your pricing model needs SQL-level flexibility and you expect it to change often enough that backdating and iterating metrics without pipeline rework becomes a real requirement.

If your usage model is simple and unlikely to change, the SQL and engineering dependency here is more than most teams need.

For a deeper look, see our full Metronome review.

3. Orb

What it does: Orb stores usage events at full, individual granularity instead of pre-aggregating them, so invoices can be corrected, backdated, and audited after the fact, and proposed pricing changes can be tested against real historical usage before they go live.

Best for: Enterprises that want to test proposed pricing changes against real usage data before launching them, and that are comfortable evaluating a product now owned by a payments company.

Adyen closed its acquisition of Orb on July 1, 2026, in a deal valued at $335 million, and Orb now operates under Adyen's ownership, run initially under what Adyen has described as an incubator model to preserve product continuity.

Key features

• Full event-level data retention, so invoices can be corrected, backdated, and audited without rebuilding the underlying data.
• Pricing simulation against historical usage before a proposed contract or rate change goes live.
• Version-controlled pricing rollouts, useful for AI companies whose model and agent pricing changes often.
• Customer-facing spend dashboards that surface consumption before it becomes a billing surprise.

Pros

• Pricing simulation against real historical usage reduces the risk of shipping a rate change that produces an unexpected invoice.
• Full event-level retention means corrections and audits don't require rebuilding usage data by hand.
• Orb continues running as a standalone product under Adyen, and customers remain free to use their own payment processor.

Cons

• Pricing isn't published, and enterprise deals go through a sales conversation.
• The event-level data model can make coarse, high-level reporting (like straightforward ARR tracking) harder to set up cleanly than in tools built around pre-aggregated totals.
• Teams where finance needs to own invoicing directly sometimes find Orb better suited to engineering-owned billing than finance-owned billing.

What users say

Pro: “Orb also provided support for dynamic custom SQL rules, which address our critical need for dynamic vCPU-based allowances in metering and pricing, a capability that Metronome lacked and we didn't get a clear picture of the roadmap commitments for it.” [Verified User in Computer Software, G2 Review, March 15, 2024]

Con: “When we first connected to QBO there were a few hurdles to overcome. This was more a function of QBO usability. The Orb team was great and helped us through those.” [Sam S., G2 Review, February 25, 2024]

Pricing

Pricing for Orb’s Core, Advanced, and Enterprise plans is not publicly available. Contact Orb sales directly for tailored pricing.

Bottom line

Orb is a strong fit for enterprises that want pricing simulation and custom metric flexibility, especially if working with Adyen for payments isn't a blocker.

If processor neutrality matters to you specifically, the Adyen acquisition is worth weighing before committing.

4. Lago

What it does: Lago ingests usage events, calculates charges against billable metrics and pricing plans, and generates invoices, supporting self-serve, sales-led, subscription, credit, and usage-based models across multiple products, entities, and currencies, either self-hosted or through a managed cloud option.

Best for: Engineering teams that want full control over their billing infrastructure and don't want a payment processor's acquisition to determine their billing roadmap later.

Lago is backed by Y Combinator and used by AI companies including Mistral, Groq, and Together.ai. The self-hosted version runs under an AGPLv3 license with no per-transaction fees, and its metering engine handles a high volume of events per second.

Key features

• Hybrid, customizable plans where billable metrics tie to any pricing model, with overrides for enterprise-specific terms like custom pricing and usage budgets.
• Threshold-based billing, proration, and automated dunning campaigns for accounts that fall behind.
• No-code plan updates through the API or UI, so pricing tweaks don't require a code change every time.
• Integrations across CRM, ERP, accounting, and reseller billing platforms for centralized revenue reporting.

Pros

• Genuinely provider-agnostic, with no dependency on a single payment processor's ownership or roadmap.
• No vendor lock-in on the self-hosted version, since the codebase stays under your control.
• Open-source core gives visibility into exactly how charges are calculated, which matters for teams that need to audit their own billing logic.

Cons

• Self-hosting requires real infrastructure investment and ongoing maintenance from your side.
• Managed cloud plans include a usage-based fee once free volume thresholds are exceeded.
• A smaller public track record than more established vendors makes it harder to independently verify support quality at very high volume.

What users say

Pro: “Lago gives us full control over our billing stack while staying developer-friendly. The fact that it’s open-source and self-hostable was a game-changer for our team, especially with GDPR constraints and growing infra complexity.”

Con: “There’s a slight learning curve if you’re moving from Stripe Billing or Chargebee. Lago is flexible, but it requires thoughtful integration. That said, it’s worth it if you want control.” [Antoine P., G2 Review, September 16, 2025]

Pricing

Pricing for Lago Premium is not publicly available. Contact Lago directly to request a tailored quote.

Bottom line

Lago is the strongest choice for engineering teams that want to own their billing infrastructure outright, without a payment processor's acquisition later deciding the roadmap for them.

It holds up as a serious option for high-volume, custom usage models, provided you're comfortable with the operational responsibility that comes with self-hosting.

5. Chargebee

What it does: Chargebee handles usage ingestion, metering, pricing, billing, and revenue recognition together, alongside its original subscription and recurring billing engine, with quoting and contracting tied directly into the same system.

Best for: AI companies that need usage-based billing to work alongside subscriptions and negotiated enterprise contracts, without building separate metering infrastructure from scratch.

Chargebee also handles quoting, renewals, and revenue recognition in one system, which makes it a common choice for companies running both self-serve plans and negotiated enterprise deals side by side, a pattern that shows up often once an AI product adds a seat-based tier on top of its usage pricing.

Key features

• Flexible usage ingestion from S3, data warehouses, flat files, or a direct API, built to handle billions of events with near-real-time aggregation and idempotency checks.
• Visual and SQL-based metering, with simple rules set through filters and SQL available for advanced aggregation logic.
• Prepaid credits with a full audit trail, configurable rollover and expiration, real-time metering against balances, and automatic overage billing.
• Entitlements adjustable by business and go-to-market teams directly, with allocated-versus-actual consumption tracked at account and subscription level.

Pros

• Sales can quote usage-based pricing and credits directly, with multi-year contracts billed monthly and parent-child hierarchies for enterprise deals.
• Combines usage metering, entitlements, quoting, and revenue recognition in one system instead of stitching together separate tools.
• Business and go-to-market teams can adjust pricing, entitlements, and usage limits directly, without opening an engineering ticket for every change.

Cons

• Its usage-billing capabilities were built on top of an originally subscription-first platform, so confirm the metering engine handles your specific event volume before committing to a purely usage-first model.
• Support response times can stretch to multiple days on some plans.
• Bespoke or unusual billing models can feel constrained by the platform's existing structure.

What users say

Pro: “The usage-based pricing we were able to implement. The fact that it supports our multi-country setup and has high flexibility on the hierarchy setup of group customers. It's fast, and the support & contact people are very nice.” [Verified User in Hospital & Health Care, G2 Review, July 14, 2026]

Con: “Some sections feel a bit counterintuitive to me, but there are specific knowledge articles that help me troubleshoot issues on my own. The initial setup was fine overall, although we still spent quite a bit of time doing manual work during the migration.” [Verified User in Financial Services, G2 Review, June 25, 2026]

Pricing

Chargebee’s Flow plan starts at 0.80% of monthly billing value with no platform fee and includes 100M usage events per month. The Commit Monthly option costs $99 plus 0.65% of billing value, while Enterprise Plus uses custom pricing.

Bottom line

Chargebee is a strong fit if you need usage billing, prepaid credits, and entitlements working alongside subscriptions and enterprise contracts in one system.

If your business is usage-only with no subscription component, confirm the metering engine's throughput matches your actual event volume before committing.

6. Recurly

What it does: Recurly manages subscription billing, invoicing, dunning, and revenue recovery, with usage-based add-ons and consumption pricing layered on top of its original recurring-billing core.

Best for: AI companies that started on a flat subscription model and are introducing usage or credit-based pricing for the first time, without wanting to rebuild their entire billing stack to do it.

Recurly's roots are in subscription commerce, and its dunning and payment-recovery tooling, built for reducing involuntary churn on recurring charges, carries over directly into usage-based plans once a company adds consumption pricing on top of an existing subscription base.

Key features

• Usage-based add-ons layered on existing subscription plans, without requiring a full platform migration.
• Automated dunning workflows with configurable retry logic for failed payments.
• Multi-currency and multi-entity billing support for companies selling internationally.
• Revenue recognition reporting aligned to subscription and usage revenue together.

Pros

• A natural next step for AI companies whose billing already runs on Recurly for subscriptions and just need to add a usage component.
• Payment recovery and dunning tooling is mature, since it's the platform's original core competency.
• Predictable, published starting pricing makes early evaluation easier than vendors that gate pricing behind a sales call.

Cons

• Usage-based features are an extension of a subscription-first platform as opposed to a purpose-built usage-metering engine, so very high-volume or highly granular usage models may outgrow it faster than platforms built usage-first.
• Custom, multi-dimensional pricing logic (per-agent, per-token, per-outcome) often needs additional engineering work on top of what's available out of the box.
• Real-time enforcement of usage limits isn't part of the billing layer here either. Recurly counts and bills usage, but it doesn't decide what a request is allowed to do in the moment.

What users say

Pro: "One of the biggest benefits of Recurly has been the improved client experience. Automated receipts, renewal processing, and payment notifications provide consistency and reduce administrative burden for both clients and staff. The platform has allowed our team to spend less time on manual billing tasks and more time supporting our clients.” [Adeola O., G2 Review, July 14, 2026]

Con: “Sometimes it automatically prorates the amount for the service I’m trying to charge, which means I have to either fiddle with the numbers or send two separate invoices to get it right.” [Joyce A., G2 Review, July 15, 2026]

Pricing

Recurly Starter starts at $249 per month + 0.9% of billing volume, with no fee on the first $40K billed monthly. Its All-Access plans charge less than 1% of billing volume on an annual contract.

Bottom line

Recurly is a solid choice for AI companies already on a subscription model that are adding usage or credit pricing for the first time and want to avoid a full billing migration.

For usage-only products with high event volume from day one, a usage-first platform is likely the better starting point.

Which billing software should you choose?

The right choice depends more on your existing stack, deployment preferences, and who owns pricing changes than on any single best answer.

Choose Stripe Billing if you:

• Already process payments through Stripe and want usage billing without a second vendor relationship
• Have a simple usage model with one or two billable metrics

Choose Metronome if you:

• Need metering proven at genuinely high AI-industry usage volume
• Are already committed to Stripe and want a platform whose roadmap sits inside Stripe's own billing strategy

Choose Orb if you:

• Want to test proposed pricing changes against real historical usage data before launching them
• Are comfortable evaluating a product now owned by Adyen

Choose Lago if you:

• Want full control over your billing infrastructure, self-hosted or managed
• Need to stay independent of any single payment processor's roadmap or acquisition

Choose Chargebee if you:

• Need usage billing, prepaid credits, and entitlements working alongside subscriptions and enterprise contracts in one system
• Want business and go-to-market teams able to adjust pricing directly

Choose Recurly if you:

• Are adding usage or credit pricing to an existing subscription model for the first time
• Want mature dunning and recovery tooling without migrating off a subscription-first platform

Skip this category entirely if your bottleneck is deciding what a request should be allowed to do before it happens, or if your usage model is genuinely simple with one metric, one tier, and low volume.

Final verdict

For most AI companies starting out, Stripe Billing is the fastest path to a working setup, and Metronome or Lago are the strongest upgrades as volume and pricing become more complicated.

Why billing software alone can't govern AI usage

Billing software alone can't govern AI usage because it answers "what should this customer be charged," instead of telling you whether a specific request should be allowed before that cost is incurred, and those are different questions.

Stigg is the usage runtime for AI products. Entitlements, credits, usage limits, and spend governance are enforced synchronously in the request path.

You don't have to adopt all of it at once. The credits engine, entitlements, and metering can each be adopted independently, and many companies start with a single SDK integration before layering in more:

• Synchronous entitlement checks enforced in the request path, resolving instantly from local Redis on a cache hit, and in around 100ms from Stigg's Edge API on a cache miss, with a configurable timeout.
• A centralized product catalog for pricing and packaging, independent of any single billing provider.
• Credit and usage tracking on an append-only ledger that feeds accurate, event-level detail into whichever invoicing tool sits downstream.
• Support for complex tenancy: per-user, per-team, per-product, per-department, at enterprise-grade cardinality.
• BYOC deployment for teams with data residency requirements, built to hold up at high request volume. The Sidecar's local cache keeps entitlement checks off the hot path so they don't become the bottleneck.
• Compatible with your existing billing stack, including every tool on this list. No rip-and-replace required.

Picking a billing platform from this list solves half the problem. What comes next is what happens the moment a request comes in, before it ever reaches an invoice. See the Stigg docs for details on entitlements and usage-based governance.

FAQs

1. What is the best billing software for AI companies?

The best billing software for AI companies depends on where you're starting from.

Stripe Billing suits companies already on Stripe with a simple usage model, Metronome and Lago suit companies with high-volume, complex usage patterns, and Chargebee or Recurly suit companies blending subscriptions with usage for the first time.

2. What's the difference between billing software and real-time entitlement enforcement?

The difference between billing software and entitlement enforcement is timing. Billing software counts usage and generates an invoice after the fact. Entitlement enforcement decides, synchronously, whether a specific request is allowed to happen at all, before it's ever counted.

3. Can AI companies use more than one billing tool at once?

Yes, AI companies can run more than one billing tool at once, particularly during a migration between providers or when subscriptions and usage-based charges are handled by different systems.

A layer that sits above billing, rather than replacing it, can support multiple providers simultaneously without requiring a rip-and-replace migration.

4. How much does billing software for AI companies typically cost?

It varies by vendor and volume. Some platforms publish real starting prices. Stripe Billing starts at $620/month on a one-year contract, or 0.7% of billing volume pay-as-you-go, and Recurly Starter begins at $249/month plus 0.9% of billing volume, with no fee on the first $40K billed monthly.

Others, including Orb, Metronome, Lago's Premium plan, and Chargebee's Enterprise tier, use custom pricing available only through a sales conversation.