What is Credyt and what does it do?

Credyt is real-time monetization infrastructure for AI products. It tracks what each API call, model, and customer costs you as usage happens, then bills customers against that usage in real time. It fits teams building AI features who pay per call and need to connect those costs to revenue—whether you're a solo "vibe coder" or a scaling AI company. The core idea: every time a user hits your app, it costs you money, and Credyt bills them in real time.

The problem it addresses

Traditional SaaS has costs that don't scale directly with each user action. AI products do: every API call costs real money, so your costs scale with usage while your revenue may not, because the two aren't connected. Credyt's site frames this as three concrete failures:

• No pricing model. You don't know whether to charge per token, per request, per seat, or per output—so you either don't charge or apply a flat fee unrelated to usage.
• Fronting costs you haven't collected. You've "accidentally become a bank," financing users' AI consumption before you bill them.
• No per-customer profitability. Your biggest customer might be your biggest loss—for example, a customer generating $5K/month but costing $6K in compute.

How it works: observe, control, bill

Credyt organizes its product around three functions.

Observe

Real-time cost streaming for every API call, every model, every customer. Instead of waiting for month-end, you see what each user costs as it happens, spot anomalies early, and view profitability at the customer level. The site shows a live event model cost P&L—a stream of entries like a contract analysis call at $0.0187 or a document summary at $0.0412, each tied to a timestamp, model, and customer.

Control

Hard budget ceilings per customer, per agent, or per team. Credyt checks the balance before usage is authorized, not after the invoice is generated. If the balance is insufficient, the action is blocked—so there are no threshold overruns.

Bill

Billing across every pricing model you use today or might use tomorrow—the site names per token, per request, per seat, and per output as the models teams are choosing between.

Who it's for

The site lists two audiences: Vibe Coders and AI Companies that need to scale. The common thread is a product where usage drives cost and where pricing hasn't been figured out yet. If you're pre-revenue or charging a flat fee disconnected from usage, the observe and control functions are the entry point; billing follows once you've picked a model.

Pricing

Credyt's pricing page lists $1 per active wallet. The site also offers a "Start for free" path. Beyond the per-wallet rate, the available material doesn't detail tiers, limits, or what counts as an active wallet—check the pricing page for the current definition before estimating costs.

Background

The Credyt team comes from Visa, Checkout.com, TrueLayer, and SumUp, and the site states they've built monetization infrastructure at scale and know where it breaks. That's the pitch for why the billing edge cases—balance checks before authorization, per-customer cost attribution—are handled rather than discovered by you.

When it fits, and when to look elsewhere

Credyt is a reasonable fit if you pay per AI call, can't yet attribute cost per customer, and want billing tied to actual usage rather than a flat subscription. It's less relevant if your product has no variable AI cost per user, or if you already have metering and billing wired into your stack and only need a pricing-model decision—that's a strategy question, not an infrastructure one. For the pricing-model question itself, the site's framing (per token vs. per request vs. per seat vs. per output) is a useful starting checklist, but the right choice depends on your margins and customer expectations, which you'll need to work out against the per-customer cost data Credyt surfaces.