Best usage-based billing software for AI companies

AI companies face billing challenges that traditional subscription platforms were never designed to handle. Token-based pricing, multi-dimensional usage across models and regions, and high-frequency event streams can require infrastructure that meters very large volumes of usage while maintaining the flexibility to iterate on pricing as market conditions shift. How much throughput a given company actually needs depends on traffic volume, event granularity, and whether usage is streamed individually or batched, since a single usage event can carry a quantity such as tokens rather than requiring one billing event per token. Pricing complexity also compounds over time: credits and wallets, minimum commits with overages, hybrid platform fees, and enterprise-specific terms each add another branch to the billing logic that engineering, product, finance, and RevOps have to keep in sync. This guide evaluates seven usage-based billing platforms through the lens of AI-specific requirements, helping engineering leaders, finance teams, and product managers select the right foundation for monetizing AI products.

Key takeaways

• Raw event architecture enables pricing agility: Platforms that store granular raw usage events rather than pre-aggregated data preserve the detail needed to rerate usage, backfill corrections, and change pricing logic without reconstructing or re-ingesting previously discarded data.
• Event throughput should be sized to your workload: There is no single universal ingestion requirement for AI billing, and platforms describe support for high-volume ingestion in different ways. Orb's Enterprise platform is regularly stress-tested at volumes such as 250K+ events per second, with Hosted Rollups designed for substantially higher sustained workloads.
• Pricing simulations reduce revenue risk: The ability to test pricing changes against historical usage data before deployment reduces guesswork by quantifying how proposed pricing would have affected historical revenue and customer segments.
• Payment processor flexibility preserves optionality: Billing platforms differ in how they support payment processors and the off-platform payment lifecycle. Orb customers can continue working with their preferred payment processing partner, which matters for both processing costs and global payment method coverage.
• SQL-defined metrics support complex AI pricing: Custom billing logic for tokens, models, regions, and feature tiers requires flexible metric definitions beyond simple event counts.
• Billing is a cross-functional system, not a back-office task: Usage-based pricing touches product packaging, sales contracts, engineering pipelines, and the finance close. Platforms that keep metering, pricing, invoicing, and revenue reporting on the same raw usage events reduce the reconciliation work that otherwise lands on those teams.

1. Orb

Orb is a revenue design platform built specifically for the complexity of AI and infrastructure billing. Orb was purpose-built from the start for consumption-based monetization, using deterministic queries over stored raw usage events.

One piece of current context matters for any 2026 evaluation: Orb's acquisition by Adyen closed on July 1, 2026, making Orb officially part of Adyen. Orb states that the product continues to operate as a stand-alone platform and that customers can continue choosing their preferred payment processing partner.

Key capabilities for AI companies

• Raw event architecture: Orb's standard query-based ingestion path stores raw usage events immutably rather than aggregating data at ingestion, and every invoice line item remains traceable back to the specific events that produced it. For extreme-volume workloads, Hosted Rollups can instead pre-aggregate event data in real time during ingestion. Because metrics are queries over event history, metrics can be changed without re-ingesting the underlying events, and Orb's backfill and amendment workflows enable audit-safe backfills and historical corrections with automatic recalculation, reducing manual reconciliation. See Orb's accuracy product page for the broader backfilling and backdating model.

• 250K+ events/second throughput: Orb's pricing page states that its Enterprise platform is regularly stress-tested at volumes such as 250K+ events per second and that customers can continuously send billions of events per day using hosted streaming aggregation. Orb's high-throughput ingestion documentation goes further, describing direct API ingestion well into the thousands of events per second, cloud-bucket ingestion once volumes are consistently above roughly 10K per second, sustained testing beyond 500K per second, and Hosted Rollups customers sustaining several million events per second in production. Orb's overview summarizes Hosted Rollups as handling 1M+ billing events per second in production deployments.

• Pricing simulations: Orb's simulation engine lets teams test pricing changes against historical usage data before deployment, compare scenarios side by side, generate exact invoice previews, and model projected revenue and customer-level impacts.

• SQL-defined metrics: Orb exposes a Custom SQL editor over raw usage events, supporting complex aggregations and subqueries alongside standard COUNT, SUM, MAX, and COUNT DISTINCT logic. Orb's event model explicitly uses properties such as tokens, model, and region.

• Dimensional price groups: Orb's dimensional price groups support pricing across multiple usage dimensions, such as region, instance type, and environment, using a single pricing configuration for dimension combinations.

• End-to-end billing and finance workflows: Metering, pricing, subscriptions, Orb Invoicing, accounts receivable, and revenue reporting run on the same raw usage events, with exports to data warehouses and a native NetSuite integration for revenue recognition. That keeps the path from product usage to cash collection inside one billing core instead of spreading it across separate metering, invoicing, reporting, and reconciliation systems.

AI billing use cases

Orb powers billing for AI companies across the spectrum, from API-first inference platforms to enterprise AI assistants. Token and agent billing with model-specific rates, prepaid credit blocks with automated drawdown as usage occurs, and hybrid plans combining usage-based pricing, fixed fees, and per-seat charges are all natively supported. Enterprise motions are covered by the same model, including minimum commits with overages and true-ups, custom and blended metrics for individual accounts, grandfathered plans from earlier pricing generations, and customer hierarchies for resellers and marketplace billing.

Orb reports that Vercel decreased the time required to build and launch billing for new products by 80%. Orb also reports 40x revenue growth at Replit since Replit began using Orb to monetize usage. Supabase processes over 1.5 million invoices per month through the platform.

Pricing structure

• Core: Custom pricing with real-time ingestion, Custom SQL metrics, hybrid billing, Orb Invoicing, and finance and tax integrations.

• Advanced: Adds data warehouse sync, Salesforce and NetSuite integrations, customer hierarchy, and premium support.

• Enterprise: Adds enterprise-grade SLAs and dedicated support.

Separately from the plan tiers, Orb maintains SOC 1 Type II and SOC 2 Type II certifications covering financial-reporting and data-security controls at the platform level.

Why Orb leads for AI billing

Orb combines query-based billing, high-throughput ingestion, pricing simulations, flexible metric and pricing configuration, and finance workflows in a platform designed for modern usage-based monetization. Pricing changes do not require re-ingesting usage data or rebuilding ingestion pipelines: immediate migrations take effect right away, while backdated migrations re-query historical events and recalculate affected invoices. That combination gives AI companies the pricing agility they need as they iterate on monetization strategies.

It also changes who owns monetization day to day. Product can package, tier, and bundle in the product catalog instead of filing engineering tickets, finance gets event-level lineage from a usage event through to an invoice line item and a journal entry, and engineering gets to stay on the core roadmap. Orb reports that Supabase reduced billing fees by roughly 0.4% of revenue while improving invoice transparency.

2. Metronome

Metronome is an enterprise billing platform. Stripe completed its acquisition of Metronome on January 14, 2026, and at Sessions 2026 Stripe described Metronome as a Stripe product. Metronome and Stripe Billing (number 4 below) are evaluated separately here because they remain distinct product surfaces, though they now belong to the same vendor ecosystem. The platform focuses on contract management and metering for large-scale AI deployments.

Primary capabilities

• Enterprise contract management: Supports multi-year commits, drawdown schedules, and complex ramp arrangements.

• High-volume metering: Supports high-volume event ingestion without requiring pre-aggregation or rollups.

• Raw-event architecture: Meters and stores raw usage events and supports SQL-based billable metrics built against that raw data, rather than requiring customers to pre-aggregate usage at ingestion.

• Stripe integration: Integration with Stripe for payment processing and invoicing, with documented workflows that can also accommodate external payment providers.

AI billing considerations

Metronome powers billing for several large AI infrastructure companies, and it supports enterprise contract complexity with features for commits, drawdowns, and scheduled rate changes over multi-year agreements. Because it retains raw usage and supports backdated pricing changes, historical corrections are handled through documented workflows that replay and re-rate usage.

Organizational fit

Metronome is designed for enterprise AI companies with complex contract structures, and it offers deep Stripe integration, so teams already standardizing on Stripe will find the tightest coupling there. AI companies that want metering, pricing, invoicing, accounts receivable, and revenue reporting to live in a single billing core, and that expect to run simulations, metric changes, and backfills over historical raw usage events, tend to evaluate Orb as the end-to-end option rather than assembling those layers across systems.

3. Solvimon

Solvimon is a European billing platform headquartered in Amsterdam, with a dedicated Solvimon for AI offering that launched on March 24, 2026. The platform offers competitive pricing for qualifying early-stage AI companies with a focus on hybrid billing models.

Primary capabilities

• Hybrid pricing models: Native support for combining seats, usage, and credits in a single billing configuration.

• High throughput: Supports high-volume event ingestion.

• EU data residency: Netherlands-headquartered with an Amsterdam HQ, offering EU and US data-residency options with EU residency as the default.

• Free tier for qualifying companies: For qualifying AI-native companies, Solvimon advertises the first $3M of billed revenue free and 0.4% of billings thereafter. Eligibility criteria apply: the company must be AI-native, founded within the last three years, and have at least $2M in VC funding or $1M in ARR.

AI billing considerations

Solvimon's discounted AI plan targets younger AI companies with cost-sensitive requirements. The platform supports credit systems and multi-entity billing, and its documentation states that granular usage data can be used to test pricing changes against historical usage data. Its 2026 AI-billing comparison also describes a pricing-simulation feature for modeling changes before going live.

Organizational fit

The AI promotional plan is aimed squarely at early-stage AI companies, while the platform overall is positioned more broadly: Solvimon describes working with companies from Seed to post-IPO, offers Growth and multi-entity capabilities, and supports both EU and US data residency. Solvimon publishes both enterprise and startup customer references. For AI companies whose primary constraint is pricing iteration at scale rather than early-stage billing cost, Orb pairs high-throughput ingestion with simulations, metric changes, and backfills computed over immutable raw usage events.

4. Stripe Billing

Stripe Billing is a component of Stripe's payment infrastructure that adds subscription and usage-based billing capabilities on top of payment processing. Stripe also owns Metronome (number 2 above) following its January 2026 acquisition.

Primary capabilities

• Payment integration: Native connection to Stripe's payment processing and customer management, plus generally available multiprocessor support including lifecycle management for off-Stripe payments.

• Subscription and usage-based billing: Supports subscriptions, high-volume usage metering, credits, hybrid plans, and dimensional pricing, including billing based on multiple attributes from a single meter.

• High-volume metering: Supports high-volume usage event ingestion for its usage-based billing infrastructure, a capability it reiterated at Sessions 2025.

• Developer experience: Familiar APIs for teams already using Stripe.

• Implementation: Relatively straightforward to adopt for teams already using the Stripe stack, though implementation time varies with usage instrumentation, pricing complexity, migration scope, and finance-system requirements.

AI billing considerations

Stripe built a dedicated high-volume usage-based billing pipeline, and its January 2025 engineering description states that one processing path writes streaming events to disk in a transactional ledger, which is then used for invoicing, analytics, and financial records. That same description discusses retroactively resynchronizing historical events with changed pricing, including handling a discount made retroactive to the beginning of the day by opening a lookback window and resynchronizing the pricing and event streams.

Stripe Billing supports multi-dimensional pricing for tokens by model, region, and feature tier: its late-2025 Billing upgrades added dimensional pricing and hybrid pricing plans, and its 2026 materials further integrate multidimensional pricing through Metronome.

Organizational fit

Stripe Billing can support substantial usage workloads: Stripe reports more than 300,000 businesses using Billing and names major AI companies among its customers. Stripe remains a strong choice for payments and global acquiring, and a common pattern among AI companies is to keep Stripe for payment processing while running the usage-based billing core in Orb, where raw usage events power complex hybrid models, account hierarchies, commit and drawdown structures, and revenue reporting, with invoices and revenue data flowing on to payment and finance systems.

5. Lago

Lago is an open-source billing platform that provides self-hosted or cloud deployment options for usage-based billing.

Primary capabilities

• Open-source foundation: Full access to source code with a self-hosting option.

• Usage metering: Event ingestion with aggregation and billing calculations, with support for high-volume event ingestion.

• Credit wallets: Prepaid credit functionality with balance tracking.

• Multiple payment gateways: A PSP-agnostic approach, with native integrations for Stripe, Adyen, and GoCardless, community integrations, and custom payment-provider workflows.

AI billing considerations

Lago appeals to AI companies with strong preferences for data ownership and deployment control. The open-source and self-hosted options give teams direct control over their billing infrastructure, while self-hosting adds infrastructure and operational responsibility. Lago Premium is available as both a cloud deployment and a self-hosted deployment, so implementation scope varies by deployment model.

Organizational fit

Lago is particularly relevant to AI companies that value open source or self-hosting and want complete data control. Teams without dedicated billing engineering capacity can also consider Lago through its managed cloud option. Where the priority is a managed platform that carries metering, pricing, invoicing, and revenue reporting together, Orb provides that scope as a single billing core, so billing does not become an internally maintained surface alongside the core product.

6. Chargebee

Chargebee is a mature subscription management platform that rebuilt usage-based billing as a native part of its platform for the AI era.

Primary capabilities

• Subscription management: Comprehensive subscription lifecycle management with dunning and retention tools.

• High-volume usage metering: Chargebee's January 2026 product materials describe raw, schemaless event ingestion, streaming and batch ingestion, SUM, COUNT and advanced SQL metering, AI-token and compute-unit use cases, and support for high-volume usage event ingestion. Chargebee's usage documentation and its usage engine post cover the same capabilities.

• Integrations: Chargebee's current platform messaging advertises 60+ integrations, and its pricing page separately lists 35+ payment gateway integrations.

• Free tier: The Starter plan is free for the first $250K of cumulative billing, after which a 0.75% fee applies to subsequent billing.

AI billing considerations

Chargebee has deep subscription-management roots, and in January 2026 it stated that it had rebuilt usage-based billing from the ground up as a native part of the platform. Its current materials target AI-native usage cases including token usage, compute units, high-volume events, and hybrid pricing.

Organizational fit

Chargebee suits companies that want subscription lifecycle depth alongside a usage engine. Fit tends to follow actual requirements such as metering scale, contract complexity, finance stack, price experimentation, credits, and deployment model. For AI and infrastructure companies whose pricing is expected to keep changing, Orb's query-based model means new metrics and packaging are defined over already-stored raw usage events, so pricing evolution and historical corrections stay inside the billing platform.

7. Maxio

Maxio (formerly Chargify and SaaSOptics combined) is a B2B SaaS finance platform with billing, revenue recognition, and metrics reporting, and it added a re-architected Metering product in 2026.

Primary capabilities

• Revenue recognition: Automated revenue-recognition workflows designed to support ASC 606 and IFRS 15 compliance.

• SaaS metrics: Built-in ARR, NRR, and churn analytics for board reporting.

• B2B billing: Support for complex B2B contracts with invoicing and collections.

• NetSuite integration: Native connection to NetSuite for financial operations.

• High-volume metering: Maxio announced in May 2026 that Metering had been re-architected for SaaS and AI businesses managing high-volume, variable usage. Its current usage-based billing page advertises event streaming and support for high-volume event ingestion.

• Flexible usage pricing: Per-unit, tiered, volume, hybrid, and custom pricing, plus prepaid usage, credit burndowns, and usage metering.

AI billing considerations

Maxio pairs finance and revenue-recognition depth with a newer high-volume Metering product aimed at AI and usage-heavy SaaS. Its 2026 finance-focused material also describes modeling the revenue impact of a proposed pricing adjustment before it goes live, and its product page advertises built-in analytics and backtesting for how pricing, credits, or bundles affect revenue.

Organizational fit

One strong Maxio profile is the finance-led B2B software company where revenue recognition complexity is a primary driver. That is one buyer profile rather than the platform's boundary: Maxio may also be attractive where usage billing must remain tightly connected to revenue recognition and SaaS financial reporting, including for hybrid or multi-signal pricing. AI companies with very high-volume metering at the center of the business often anchor on a usage-native billing core such as Orb, which keeps event-level truth, invoicing, and revenue reporting in one place and syncs cleanly into ERPs such as NetSuite and QuickBooks.

Why Orb stands out for AI usage-based billing

For AI companies where pricing agility and billing accuracy directly affect revenue, Orb combines query-based billing, high-throughput ingestion, pricing simulations, flexible pricing configuration, and finance workflows in a platform designed for modern usage-based monetization.

Pricing simulation changes the game

Orb Simulations lets teams test pricing changes against historical usage before deployment, model customer-level impacts, and compare projected revenue outcomes before committing. When an AI company considers shifting from per-token to per-request pricing, or introducing a new model tier, Orb can generate exact invoice previews from historical usage and model projected revenue effects across customer segments. That reduces guesswork and live-deployment risk by letting teams evaluate a change on real historical usage before exposing customers to an untested configuration.

Raw events enable fast iteration

Because Orb's standard query-based architecture stores raw usage events immutably rather than pre-aggregated summaries, Orb can change pricing without re-ingesting usage data or rebuilding ingestion pipelines. Immediate migrations take effect right away, while backdated changes re-query historical events and recalculate affected invoices. The backfilling and backdating capabilities handle the inevitable corrections that arise in complex billing environments. At extreme volumes, Hosted Rollups pre-aggregate event data in real time during ingestion, extending the same billing model to the highest-throughput AI workloads.

Pricing execution without engineering bottlenecks

New metrics, tiers, bundles, and credit models are defined over usage events that Orb has already stored, so product and finance can execute pricing in the product catalog and in SQL rather than shipping code for each change. Vercel unlocked pricing agility across 60+ SKUs, and Replit launched Autoscale with usage-based pricing while retaining the ability to tune pricing up to a week before launch, then reused the same billing motion for subsequent products. Pricing stops being a quarterly engineering project and becomes a repeatable motion the business can run on its own cadence.

A single source of truth for finance

Orb ties event-level usage to invoice line items and on to revenue reporting, so finance can explain any charge rather than reconstruct it. Orb Invoicing extends that lineage through to cash collection, the native NetSuite integration creates standard transaction records with exact service-period dates for revenue recognition, and Accounting period locks keep closed periods stable through month-end close. Finance teams at companies such as Pinecone and Stytch chose Orb specifically to get to one source of truth for usage and billing across spiky, usage-heavy workloads, and Opus moved to Orb for accurate credits-based billing with transparent customer-facing balances.

Built for AI-scale throughput

Orb's Enterprise platform is regularly stress-tested at volumes such as 250K+ events per second, and customers can continuously send billions of events per day using hosted streaming aggregation. Orb's high-throughput ingestion documentation describes sustained testing beyond 500K events per second and Hosted Rollups customers sustaining several million events per second in production, while Orb's overview summarizes Hosted Rollups as handling 1M+ billing events per second in production deployments. High-throughput ingestion is foundational architecture rather than added capacity.

Payment processor independence

Orb is not tied exclusively to one payment-processing relationship. Following the close of Adyen's acquisition of Orb on July 1, 2026, Orb states that it continues to operate as a stand-alone product and that customers can continue working with their preferred payment processing partner. Orb's public documentation covers Stripe as a payment gateway and invoicing provider, with supported methods including cards, ACH, Link, Apple Pay, and Google Pay.

Proven with AI leaders

Orb reports that Vercel reduced the time required to build and launch billing for new products by 80%, that Replit saw 40x revenue growth since using Orb to monetize usage, and that Stytch cut time spent processing bills and invoicing by 75%, saving eight hours per month. These outcomes reflect Orb's purpose-built approach to AI monetization.

Frequently asked questions

What is usage-based billing and why is it important for AI companies?

Usage-based billing charges customers based on actual consumption rather than fixed subscriptions. For AI companies, this can align revenue more closely with variable infrastructure costs, because compute expenses generally increase with consumption, although the relationship is not necessarily linear: cost per unit varies with model, input and output token mix, caching, batching, hardware, provider pricing, and workload type. Token-based pricing, API call metering, and model-tier billing all require platforms designed for high-frequency event ingestion and flexible pricing configuration.

How does Orb handle complex pricing models like dimensional pricing for AI services?

Orb's dimensional price groups support pricing across multiple usage dimensions, such as region, instance type, and environment, using a single pricing configuration for dimension combinations, with unlimited dimensions. An AI platform can price inference by model type, token category, region, and feature tier simultaneously. Custom SQL metrics enable custom billing logic for complex aggregations and subqueries beyond simple event counts.

Can usage-based billing software integrate with existing financial systems like NetSuite?

Yes, Orb provides native NetSuite integration that creates standard NetSuite transaction records rather than summary imports. This includes invoices, credit memos, customer deposits, and sales orders, with exact service-period dates attached at line level to support revenue recognition requirements. Finance teams can reconcile and audit billing data directly within their existing workflows.

What are the key benefits of using Orb's pricing simulation tools for AI product pricing?

Orb Simulations lets teams test new pricing models against historical usage data before going live. This quantifies how proposed pricing would have affected historical revenue across customer segments, identifies potential issues with specific accounts, and reduces the risk of deploying a pricing change that looks good in theory but fails in practice.

How does usage-based billing affect engineering, product, and finance teams?

Usage-based pricing is a cross-functional system rather than a back-office task. A useful way to keep it straight is to sort every billing problem into one of three lanes: automate billing, which is always-accurate event-level billing that keeps up with rapid change and complex contracts; execute pricing, which is the ability to model, test, and roll out pricing changes quickly without breaking systems or customer trust; and grow revenue, which is using granular usage data to simulate new models, spot expansion opportunities, and design monetization intentionally. When all three lanes run on the same raw usage events, engineering is not the billing team by accident, product can treat pricing as a first-class part of the product, and finance can both trust and explain the numbers.

How does Orb ensure data accuracy and compliance for AI billing?

Orb maintains granular event logs accessible for audit and analysis, with query-based billing that makes every invoice line item traceable to the specific events that produced it, and Orb Invoicing extending that lineage from a single usage event through to a dollar received. SOC 1 Type II and SOC 2 Type II certifications address financial reporting and security controls. Accounting period locks prevent changes to closed periods, with catch-up adjustments flowing into the first day of the next open period so prior closed-period revenue remains unchanged.