Best Open Source Usage-Based Billing Platform for an AI Startup (2025 Guide)
Best Open Source Usage-Based Billing Platform for an AI Startup (2025 Guide)
Sep 13, 2025
Sep 13, 2025
6 mins
6 mins
Koshima Satija
Koshima Satija
Billing is one of the most difficult problems for AI startups to get right. Traditional tools like Stripe Billing, Chargebee, or Recurly were designed around seats and fixed subscriptions, but your business doesn’t run on seats.
It runs on LLMs, GPUs, and APIs. Every token, inference call, or GPU hour adds to your infrastructure bill, and if you’re charging a flat monthly fee, margins can vanish fast.
This is where open-source billing platforms matter. They give you full visibility into the codebase, the freedom to self-host, and the flexibility to shape billing around your pricing model whether that’s subscriptions, credits, or usage-based workflows.
With OSS, you’re not stuck inside a black-box vendor; you control the logic, the data, and the roadmap.
For AI startups, usage-based billing isn’t optional, it’s survival. The question is: which open-source platforms actually deliver the features you need today, and the flexibility to adapt tomorrow?
What is an open-source billing platform?
An open-source billing platform is software that helps SaaS or infrastructure companies track usage, manage subscriptions, and generate invoices while giving developers full visibility into the codebase. Unlike closed systems such as Stripe Billing or Chargebee, these tools can be self-hosted, customized, and extended.
Most open-source billing projects fall under licenses like AGPL-3.0 (strong copyleft) or Apache-2.0/MIT (permissive). This matters because the license determines how freely you can modify the system, embed it into your stack, or commercialize your product without restrictions.
For startups, the key advantage is control: you’re not locked into a black-box vendor workflow. You can shape billing around your pricing model—whether it’s subscriptions, usage-based, or credits without waiting on third-party feature releases.
Why AI startups need usage-based billing
Your product doesn’t run on seats, it runs on LLMs. And LLMs don’t charge per user; they charge by tokens, GPU hours, inference calls, or API usage. That means your infrastructure bill scales with compute, not with headcount.
If you charge customers a flat subscription while your own costs rise with every request, your margins evaporate. Even if you price at $20/month, a single active customer can trigger hundreds of dollars in inference costs. The more capable the models get, the faster this gap widens tasks that once used 1,000 tokens can now consume 100,000.
That’s why you need usage-based billing. It lets you:
Meter usage precisely so revenue maps directly to costs.
Offer credits and roll-overs so prepaid balances line up with real consumption.
Version and iterate plans quickly to keep pace with changing model economics.
Aggregate usage flexibly for metrics like DAU, API requests, or “latest” values.
Stream usage events in real time so billing is always accurate.
Without this, you’re effectively subsidizing compute for your heaviest users and putting your margins at risk as you scale.
Best open-source usage-based billing platforms for AI startups
TL;DR:
Flexprice is #1 for AI-native teams that need full-stack, OSS billing (credits, wallets, metering, subscriptions, invoicing, SOC 2).
OpenMeter is a powerful metering + entitlements backbone that now ships billing, but it’s infra-heavy and leans on Stripe for collection.
Kill Bill is battle-tested subscription OSS with a deep plugin ecosystem, but skews enterprise/Java.
Lago is a modern OSS alternative to Stripe/Chargebee with solid metering/subscriptions; advanced workflows often require more DIY.
1. Flexprice
Flexprice is an open-source, developer-first billing and monetization platform. It’s built for AI-native and agentic SaaS companies, think voice agents, video agents, observability tools, and next-gen infra platforms.
Instead of treating billing as a black box, Flexprice gives your team full visibility and control over pricing logic, credit systems, and metering workflows. You’re not limited by rigid subscription-first designs or vendor timelines. You can shape billing around how your product actually works.
Top features
Credits & Wallets → recurring and one-time grants, roll-overs, and credit prioritization.
Advanced Usage Metering → flexible aggregation types (sum, unique count, latest, custom).
Entitlements → define and enforce feature gating and usage rights directly in billing.
Migration Workflows → move customers between plans seamlessly without billing gaps.
Advanced Subscription Workflows → handle upgrades, downgrades, proration, and calendar vs anniversary billing cycles.
Invoicing → generate invoices, record offline payments, and let customers pay invoices with wallet credits.
Real-time Events → webhook streams to sync billing with product, finance, and analytics systems.
Enterprise-ready → self-hostable with SOC 2 compliance, public roadmap, and active GitHub repo.
Cons
The ecosystem and community are still growing compared to older incumbents like Kill Bill.
Best when in the journey
You’re an AI startup where tokens, GPU hours, or API requests are the actual unit of value.
You need credits, entitlements, roll-overs, advanced subscriptions, and migration workflows in one OSS stack.
You want OSS + self-host control, or need SOC 2 trust to close enterprise deals.
Billing is one of the most difficult problems for AI startups to get right. Traditional tools like Stripe Billing, Chargebee, or Recurly were designed around seats and fixed subscriptions, but your business doesn’t run on seats.
It runs on LLMs, GPUs, and APIs. Every token, inference call, or GPU hour adds to your infrastructure bill, and if you’re charging a flat monthly fee, margins can vanish fast.
This is where open-source billing platforms matter. They give you full visibility into the codebase, the freedom to self-host, and the flexibility to shape billing around your pricing model whether that’s subscriptions, credits, or usage-based workflows.
With OSS, you’re not stuck inside a black-box vendor; you control the logic, the data, and the roadmap.
For AI startups, usage-based billing isn’t optional, it’s survival. The question is: which open-source platforms actually deliver the features you need today, and the flexibility to adapt tomorrow?
What is an open-source billing platform?
An open-source billing platform is software that helps SaaS or infrastructure companies track usage, manage subscriptions, and generate invoices while giving developers full visibility into the codebase. Unlike closed systems such as Stripe Billing or Chargebee, these tools can be self-hosted, customized, and extended.
Most open-source billing projects fall under licenses like AGPL-3.0 (strong copyleft) or Apache-2.0/MIT (permissive). This matters because the license determines how freely you can modify the system, embed it into your stack, or commercialize your product without restrictions.
For startups, the key advantage is control: you’re not locked into a black-box vendor workflow. You can shape billing around your pricing model—whether it’s subscriptions, usage-based, or credits without waiting on third-party feature releases.
Why AI startups need usage-based billing
Your product doesn’t run on seats, it runs on LLMs. And LLMs don’t charge per user; they charge by tokens, GPU hours, inference calls, or API usage. That means your infrastructure bill scales with compute, not with headcount.
If you charge customers a flat subscription while your own costs rise with every request, your margins evaporate. Even if you price at $20/month, a single active customer can trigger hundreds of dollars in inference costs. The more capable the models get, the faster this gap widens tasks that once used 1,000 tokens can now consume 100,000.
That’s why you need usage-based billing. It lets you:
Meter usage precisely so revenue maps directly to costs.
Offer credits and roll-overs so prepaid balances line up with real consumption.
Version and iterate plans quickly to keep pace with changing model economics.
Aggregate usage flexibly for metrics like DAU, API requests, or “latest” values.
Stream usage events in real time so billing is always accurate.
Without this, you’re effectively subsidizing compute for your heaviest users and putting your margins at risk as you scale.
Best open-source usage-based billing platforms for AI startups
TL;DR:
Flexprice is #1 for AI-native teams that need full-stack, OSS billing (credits, wallets, metering, subscriptions, invoicing, SOC 2).
OpenMeter is a powerful metering + entitlements backbone that now ships billing, but it’s infra-heavy and leans on Stripe for collection.
Kill Bill is battle-tested subscription OSS with a deep plugin ecosystem, but skews enterprise/Java.
Lago is a modern OSS alternative to Stripe/Chargebee with solid metering/subscriptions; advanced workflows often require more DIY.
1. Flexprice
Flexprice is an open-source, developer-first billing and monetization platform. It’s built for AI-native and agentic SaaS companies, think voice agents, video agents, observability tools, and next-gen infra platforms.
Instead of treating billing as a black box, Flexprice gives your team full visibility and control over pricing logic, credit systems, and metering workflows. You’re not limited by rigid subscription-first designs or vendor timelines. You can shape billing around how your product actually works.
Top features
Credits & Wallets → recurring and one-time grants, roll-overs, and credit prioritization.
Advanced Usage Metering → flexible aggregation types (sum, unique count, latest, custom).
Entitlements → define and enforce feature gating and usage rights directly in billing.
Migration Workflows → move customers between plans seamlessly without billing gaps.
Advanced Subscription Workflows → handle upgrades, downgrades, proration, and calendar vs anniversary billing cycles.
Invoicing → generate invoices, record offline payments, and let customers pay invoices with wallet credits.
Real-time Events → webhook streams to sync billing with product, finance, and analytics systems.
Enterprise-ready → self-hostable with SOC 2 compliance, public roadmap, and active GitHub repo.
Cons
The ecosystem and community are still growing compared to older incumbents like Kill Bill.
Best when in the journey
You’re an AI startup where tokens, GPU hours, or API requests are the actual unit of value.
You need credits, entitlements, roll-overs, advanced subscriptions, and migration workflows in one OSS stack.
You want OSS + self-host control, or need SOC 2 trust to close enterprise deals.
Get started with your billing today.
Get started with your billing today.
Get started with your billing today.
Get started with your billing today.
2. OpenMeter
OpenMeter started as a real-time usage metering system and has grown into a broader billing platform with product catalogs, entitlements, subscriptions, and invoicing. It’s designed for teams that need high-throughput event tracking, often pairing with Stripe for payments and tax handling.
Top features
High-volume real-time metering → Kafka + ClickHouse backbone, millions of events per second.
Entitlements → manage feature access and usage limits across plans.
Product Catalog & Plan Versioning → design pricing plans and keep customers on old versions if needed.
Subscriptions → recurring plans with basic subscription logic.
Invoicing & Payments → Stripe integration for invoice sync, payments, and tax.
SDKs & APIs → Go, Python, Node.js, and React for developer adoption.
Cons
No credit roll-overs → prepaid balances don’t carry forward.
Limited price iteration support → not built for frequent pricing experiments.
No true plan versioning workflows → harder to evolve pricing seamlessly.
Infra-heavy setup → requires Kafka and ClickHouse expertise if self-hosted.
Stripe reliance → still needs Stripe (or equivalent) for full billing.
Best when in the journey
You’re already using Stripe and want OpenMeter for high-fidelity metering + entitlements.
Your team has the engineering bandwidth to manage data infra or you’re ready to pay for OpenMeter Cloud.
3. Kill Bill
Kill Bill is the longest-standing open-source billing project, widely adopted in enterprise SaaS. It provides a subscription-first architecture with rich catalog and invoicing features, extended by a plugin ecosystem. It’s Java-based and battle-tested, but less aligned with AI-native workloads out of the box.
Top features
Subscription Catalogs → powerful, enterprise-grade subscription and pricing catalogs.
Invoicing & Proration → robust billing cycles, adjustments, and multi-scenario handling.
Plugin Ecosystem → extend functionality or add features like wallets (via Aviate).
Enterprise Proven → long track record of use at scale.
Cons
Legacy stack → heavy Java architecture, steeper setup/maintenance.
No native credits → requires Aviate or custom work for wallets and usage-based billing.
Not built for AI workloads → usage metering/credits feel bolted on, not native.
Best when in the journey
You’re an enterprise-leaning team with complex subscription catalogs and Java expertise.
You can extend with plugins for credits/meters, but don’t need an AI-first design.
4. Lago
Lago markets itself as a modern OSS alternative to Stripe or Chargebee, with strong APIs, dashboards, and a growing community. It covers subscriptions, usage metering, coupons, and invoicing, but still lacks some advanced workflows AI startups often need.
Top features
Usage Metering → track consumption and tie it to invoices.
Subscriptions API → assign and upgrade/downgrade customer plans.
Coupons & Discounts → flexible promotional workflows.
Basic Entitlements → conceptually supported, but enforcement happens app-side.
Invoicing → generate invoices and integrate with payment gateways.
Cons
No advanced entitlements → lacks granular feature gating and enforcement.
No migration workflows → moving customers between plans is manual.
Limited subscription workflows → co-terms, proration, and advanced flows need custom work.
Best when in the journey
You want a Stripe-like OSS tool for subscriptions + usage.
You’re early stage and fine handling migration and advanced workflows manually.
You’re okay wiring entitlement enforcement into your product logic.
Why Flexprice is the best open source billing platform for AI startups
AI startups don’t just need billing, they need a full monetization engine that matches how compute is consumed and how pricing evolves. Flexprice stands out because it’s the only open-source platform that unifies all of this into one stack.
Here’s why Flexprice leads:
AI-native design → Credits, wallets, token/GPU metering, and roll-overs built into the core, not bolted on.
Advanced workflows baked in → Entitlements, migration flows, and subscription handling are first-class features.
Pricing agility → Plan versioning and real-time iteration so you can adapt as models, infra costs, or customer behavior changes.
Visibility + control → Unlike black-box systems, Flexprice gives you transparent billing logic, auditable data, and flexible APIs.
Enterprise trust → SOC 2 compliance, self-hosting options, and a transparent roadmap that builds long-term confidence.
So instead of stitching together multiple tools (metering + invoicing + credits + subscriptions), you can run your entire monetization stack in Flexprice—while keeping the flexibility to align billing directly with your product’s usage patterns.
Trust and adoption signals
Choosing a billing platform isn’t just about features it’s about trusting the system that manages your revenue. Flexprice backs up its capabilities with transparent adoption markers:
Open-source by default → Full codebase available under AGPL-3.0, so you can self-host or audit every workflow.
Active GitHub presence → Stars, issues, and contributions that show a growing community and continuous iteration.
Slack community → Direct access to founders and other builders solving the same billing problems.
SOC 2 compliance → Enterprise-grade security certification that unlocks procurement at larger customers.
Transparent roadmap → Publicly shared features and timelines so you know where the platform is heading.
These signals matter because billing isn’t a feature you can easily rip out later. With Flexprice, you’re not gambling on a side project you’re aligning with a platform that’s designed to scale with your product, your revenue, and your compliance needs.
Key takeaways
If you’re building an AI startup, your billing model can’t be an afterthought. Seat-based or flat subscriptions simply don’t map to how LLMs, GPUs, and APIs are consumed.
That’s why usage-based billing is becoming the default and why open-source platforms matter.
Lago, Kill Bill, and OpenMeter each solve part of the problem. But they either lack critical workflows (entitlements, migrations, advanced subscriptions) or force you to glue together multiple tools.
Flexprice is the only OSS billing platform that brings it all together—credits, wallets, roll-overs, entitlements, subscriptions, invoicing, and real-time events—while giving you full transparency and control.
If you want a system that grows with your AI company, instead of holding it back, Flexprice is where you start.
Explore the Flexprice Docs to see how credits, wallets, and metering work in practice.
Star the GitHub repo to follow the open roadmap and get involved.
Join the Slack community to connect with other AI founders and engineers tackling billing challenges.
2. OpenMeter
OpenMeter started as a real-time usage metering system and has grown into a broader billing platform with product catalogs, entitlements, subscriptions, and invoicing. It’s designed for teams that need high-throughput event tracking, often pairing with Stripe for payments and tax handling.
Top features
High-volume real-time metering → Kafka + ClickHouse backbone, millions of events per second.
Entitlements → manage feature access and usage limits across plans.
Product Catalog & Plan Versioning → design pricing plans and keep customers on old versions if needed.
Subscriptions → recurring plans with basic subscription logic.
Invoicing & Payments → Stripe integration for invoice sync, payments, and tax.
SDKs & APIs → Go, Python, Node.js, and React for developer adoption.
Cons
No credit roll-overs → prepaid balances don’t carry forward.
Limited price iteration support → not built for frequent pricing experiments.
No true plan versioning workflows → harder to evolve pricing seamlessly.
Infra-heavy setup → requires Kafka and ClickHouse expertise if self-hosted.
Stripe reliance → still needs Stripe (or equivalent) for full billing.
Best when in the journey
You’re already using Stripe and want OpenMeter for high-fidelity metering + entitlements.
Your team has the engineering bandwidth to manage data infra or you’re ready to pay for OpenMeter Cloud.
3. Kill Bill
Kill Bill is the longest-standing open-source billing project, widely adopted in enterprise SaaS. It provides a subscription-first architecture with rich catalog and invoicing features, extended by a plugin ecosystem. It’s Java-based and battle-tested, but less aligned with AI-native workloads out of the box.
Top features
Subscription Catalogs → powerful, enterprise-grade subscription and pricing catalogs.
Invoicing & Proration → robust billing cycles, adjustments, and multi-scenario handling.
Plugin Ecosystem → extend functionality or add features like wallets (via Aviate).
Enterprise Proven → long track record of use at scale.
Cons
Legacy stack → heavy Java architecture, steeper setup/maintenance.
No native credits → requires Aviate or custom work for wallets and usage-based billing.
Not built for AI workloads → usage metering/credits feel bolted on, not native.
Best when in the journey
You’re an enterprise-leaning team with complex subscription catalogs and Java expertise.
You can extend with plugins for credits/meters, but don’t need an AI-first design.
4. Lago
Lago markets itself as a modern OSS alternative to Stripe or Chargebee, with strong APIs, dashboards, and a growing community. It covers subscriptions, usage metering, coupons, and invoicing, but still lacks some advanced workflows AI startups often need.
Top features
Usage Metering → track consumption and tie it to invoices.
Subscriptions API → assign and upgrade/downgrade customer plans.
Coupons & Discounts → flexible promotional workflows.
Basic Entitlements → conceptually supported, but enforcement happens app-side.
Invoicing → generate invoices and integrate with payment gateways.
Cons
No advanced entitlements → lacks granular feature gating and enforcement.
No migration workflows → moving customers between plans is manual.
Limited subscription workflows → co-terms, proration, and advanced flows need custom work.
Best when in the journey
You want a Stripe-like OSS tool for subscriptions + usage.
You’re early stage and fine handling migration and advanced workflows manually.
You’re okay wiring entitlement enforcement into your product logic.
Why Flexprice is the best open source billing platform for AI startups
AI startups don’t just need billing, they need a full monetization engine that matches how compute is consumed and how pricing evolves. Flexprice stands out because it’s the only open-source platform that unifies all of this into one stack.
Here’s why Flexprice leads:
AI-native design → Credits, wallets, token/GPU metering, and roll-overs built into the core, not bolted on.
Advanced workflows baked in → Entitlements, migration flows, and subscription handling are first-class features.
Pricing agility → Plan versioning and real-time iteration so you can adapt as models, infra costs, or customer behavior changes.
Visibility + control → Unlike black-box systems, Flexprice gives you transparent billing logic, auditable data, and flexible APIs.
Enterprise trust → SOC 2 compliance, self-hosting options, and a transparent roadmap that builds long-term confidence.
So instead of stitching together multiple tools (metering + invoicing + credits + subscriptions), you can run your entire monetization stack in Flexprice—while keeping the flexibility to align billing directly with your product’s usage patterns.
Trust and adoption signals
Choosing a billing platform isn’t just about features it’s about trusting the system that manages your revenue. Flexprice backs up its capabilities with transparent adoption markers:
Open-source by default → Full codebase available under AGPL-3.0, so you can self-host or audit every workflow.
Active GitHub presence → Stars, issues, and contributions that show a growing community and continuous iteration.
Slack community → Direct access to founders and other builders solving the same billing problems.
SOC 2 compliance → Enterprise-grade security certification that unlocks procurement at larger customers.
Transparent roadmap → Publicly shared features and timelines so you know where the platform is heading.
These signals matter because billing isn’t a feature you can easily rip out later. With Flexprice, you’re not gambling on a side project you’re aligning with a platform that’s designed to scale with your product, your revenue, and your compliance needs.
Key takeaways
If you’re building an AI startup, your billing model can’t be an afterthought. Seat-based or flat subscriptions simply don’t map to how LLMs, GPUs, and APIs are consumed.
That’s why usage-based billing is becoming the default and why open-source platforms matter.
Lago, Kill Bill, and OpenMeter each solve part of the problem. But they either lack critical workflows (entitlements, migrations, advanced subscriptions) or force you to glue together multiple tools.
Flexprice is the only OSS billing platform that brings it all together—credits, wallets, roll-overs, entitlements, subscriptions, invoicing, and real-time events—while giving you full transparency and control.
If you want a system that grows with your AI company, instead of holding it back, Flexprice is where you start.
Explore the Flexprice Docs to see how credits, wallets, and metering work in practice.
Star the GitHub repo to follow the open roadmap and get involved.
Join the Slack community to connect with other AI founders and engineers tackling billing challenges.
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