ZeroCredit AI
About ZeroCredit AI
One AI layer. Every model. Automatically optimized. ZeroCredit AI gives enterprises one intelligent layer for AI infrastructure — automatically understanding each request, selecting compatible models and providers, optimizing cost and performance, and handling provider-specific complexity behind one API.
Teams use it to see AI spend per request, per feature, and per customer, to forecast and cap budgets, and to prove exactly where their savings came from — without changing how they build.
Avi Goel
Founder & CEO
Our Story
Why we started ZeroCredit AI
As AI adoption accelerates, companies are spending thousands of dollars every month on OpenAI, Anthropic, Gemini, and other model providers. Yet most teams have little visibility into where that money goes or how to optimize it.
We started ZeroCredit AI after seeing teams struggle with growing AI bills, limited cost visibility, and manual optimization efforts. Our mission is simple: help organizations spend less on AI while maintaining quality and performance.
The Problem
The AI cost problem
Four patterns we see at nearly every AI-native team we talk to.
AI costs grow faster than expected
Monthly bills from OpenAI, Anthropic, and Gemini balloon without warning as usage scales.
Teams lack per-request visibility
Engineers ship features blind to the unit economics of every call they make.
Model selection is often inefficient
Frontier models get used for tasks that a cheaper model would handle just as well.
Finance receives bills without context
Invoices arrive with no breakdown of customers, features, or product lines.
How it works
How ZeroCredit AI helps businesses control AI spending
Your application points to the ZeroCredit AI base URL using a ZeroCredit API key, instead of calling each model provider directly. This drop-in integration works with any OpenAI-compatible client. Every request is priced at the model's current rate, recorded with its input and output tokens, and attributed to a feature, team, or customer. Nothing about your prompts or product logic has to change.
From there the platform reduces the bill in a few concrete ways: routing a request to the cheapest model that still meets the quality bar, serving a semantically equivalent cached answer instead of paying for a new completion, compressing prompts that carry redundant context, and capping runaway output length. Budgets, forecasts, and anomaly alerts sit on top so finance can see spend before the invoice arrives.
Engineering gets per-request unit economics. Finance gets per-customer cost allocation and margin. Leadership gets a forecast instead of a surprise.
Drop-in API + BYOK
Point your API to ZeroCredit
Keep your existing OpenAI-compatible client and prompts. Replace the provider API key in your application with a ZeroCredit API key, then set the base URL to https://zerocreditai.com/api/public/v1. Your application now calls ZeroCredit through one drop-in API.
Separately, connect your own OpenAI, Anthropic, Google, DeepSeek, Perplexity, or other provider credentials in ZeroCredit. Those provider keys execute model calls against your accounts at your negotiated rates; your ZeroCredit key authenticates your application to the gateway. Provider keys are encrypted at rest and used only for your traffic.
Your provider relationship, rate card, and data agreements stay yours while ZeroCredit adds routing, optimization, and accounting on top. See the integration guide.
Transparency
Our accounting philosophy: savings you can audit
Most cost tools report savings as an estimate. We don't. Every optimization writes an event to a ledger with the evidence behind it: which model would have run, the exact token counts, the price version used, and the resulting difference. If the evidence isn't there, the saving is shown as unverified rather than counted.
We also separate savings that are deterministic — a cache hit that avoided a real completion — from savings that are measured on a sample rather than observed on every request. Sampled measurements are labelled as such and never extrapolated into verified totals. Optimization credit is capped so that stacked optimizations can never claim more than the request could have cost.
The rule we hold ourselves to: a number we show you should be one you can reconcile against your own provider invoice.
Our Mission
To become the operating system for AI cost management, helping every company optimize, forecast, and control AI spending with confidence.
Our Values
What we stand for
Transparency
We believe teams should understand every AI dollar spent.
Efficiency
The best model is not always the most expensive model.
Trust
Enterprise-grade security and reliable reporting come first.
Customer Obsession
We build around measurable customer outcomes.
Meet the Founder
Meet the founder
Avi Goel
Founder & CEO
Avi is a Cloud and Data Engineer with expertise in Azure, data platforms, and AI infrastructure. After working closely with cloud technologies and large-scale data systems, he recognized a growing challenge facing modern businesses: controlling AI costs while maintaining performance. ZeroCredit AI was created to solve that problem.
“The future belongs to companies that can scale AI efficiently, not just those who spend the most.”
What We're Building
The future of AI cost optimization
AI Spend Visibility
Per-request, per-feature, per-customer cost attribution.
Model Routing
Send each request to the cheapest model that meets the bar.
Semantic Caching
Reuse intelligent responses across similar prompts.
Forecasting & Budget Controls
Project spend and enforce hard limits before they hit.
Vendor Risk Analysis
Track provider concentration, outages, and pricing changes.
Executive Reporting
Board-ready dashboards finance and leadership can actually read.
Trust & Security
Built for modern teams
Documented Security Controls
Published control-by-control overview — no certification claims we do not hold.
Encryption in Transit & at Rest
HTTPS everywhere, encrypted storage, and provider keys encrypted before they are saved.
Role-Based Access Controls
Granular permissions for engineering, finance, and leadership.
Enterprise Reporting
Exportable, auditable records for procurement and compliance.