A fair comparison site for AI billing infrastructure.
aibilling.dev evaluates AI billing platforms across a fixed 16-dimension rubric. No paid placement. Every provider, including Credyt, is assessed against the same standards.
Traditional billing systems were built for predictable per-seat costs. AI inference breaks that model in three specific ways:
- Every API call has direct infrastructure cost. When a user sends a request to an AI product, the underlying inference costs $0.10 to $0.50 or more depending on the model. That cost hits before you have collected anything from your customer.
- Concurrent requests create credit depletion races. When a customer initiates multiple requests simultaneously, you need to know their current balance atomically. You cannot collect incrementally. You authorize or block.
- Margins change every time you switch models. An AI team switching from GPT-4 to a fine-tuned open-source model might cut its per-request cost by 90%. Traditional billing assumes stable unit economics. AI billing does not have that luxury.
The market responded by splitting into two distinct architectures. Invoice-based platforms (Orb, Metronome, Lago) capture usage events during the billing period and reconcile them into an invoice at cycle end. Real-time platforms (Credyt, Stigg) authorize and bill usage as it happens; the customer's balance is the source of truth, updated on every request.
Neither architecture is universally better. Invoice-based fits enterprise contracts with quarterly reconciliation and high-volume event throughput. Real-time fits AI products where the lag between a request and a billed charge is itself a financial risk.
aibilling.dev is built and maintained by the team at Credyt, a real-time billing platform for AI products.
We found that "AI billing platform" could mean anything from a genuine real-time system with pre-usage authorization to a standard invoice-based metering tool with a new label. That distinction matters. We built this site so buyers can understand the true technical differences between billing solutions and how those differences apply to their specific AI use case. Not marketing copy. Architectural trade-offs, honest limitations, and pricing you can actually compare.
Every provider on this site, including Credyt, is evaluated against the same rubric with the same standards. Credyt's limitations are listed honestly. When invoice-based or open-source platforms are the better fit for a given use case, we say so.
Each provider is assessed across 16 dimensions covering billing architecture, usage authorization model, wallet and multi-asset support, payment processing, customer portal, pricing transparency, deployment options, and enterprise contract support.
For pricing, every provider is run through the same canonical scenario: 100 monthly active customers, 500K billing events per month, no enterprise discount, no annual commitment. This makes pricing comparable across platforms that charge per event, per wallet, per transaction, or as a percentage of revenue.
Data packs are refreshed quarterly. Every claim has a source and a date. Entries older than six months trigger a review.
No provider pays for placement or favorable reviews. Placement order on index pages is alphabetical. Rankings in guides are based on fit for a specific use case, explained explicitly.
All data is sourced and dated. When a provider changes its pricing or features, the relevant pages are updated with a new verification date.
If you find a factual error, contact us at contact@aibilling.dev.
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