Bizgraph vs LLM Gateway: Which Do You Actually Need?

You're building AI solutions and you've heard about LLM gateways. Maybe you found LLM Gateway (llmgateway.io) while searching for a way to manage your API calls. Maybe you found Bizgraph while looking for a way to bill clients.

They sound similar. They both sit between you and AI providers. But they solve fundamentally different problems.

Here's the short version: LLM Gateway helps you access multiple AI models. Bizgraph helps you monetize AI services for clients.

Let's break down when you need which—and when you might need both.

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What LLM Gateway Does

LLM Gateway is an open-source unified API that routes your requests across multiple AI providers. Instead of managing separate connections to OpenAI, Anthropic, Google, and others, you use one API endpoint.

Core features:

• Multi-provider routing: Access 170+ models from 25+ providers through a single API
• OpenAI-compatible format: Swap your endpoint URL, keep your existing code
• Cost analytics: Track spending across providers and models
• Self-hosting option: Deploy on your own infrastructure for free (AGPLv3 license)
• Failover: Automatic switching if a provider goes down

Pricing:

LLM Gateway positions itself as the "open source alternative to OpenRouter"—and it delivers on that promise. If you want model flexibility without vendor lock-in, it's a solid choice.

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What Bizgraph Does

Bizgraph is an LLM gateway built specifically for agencies. Instead of tracking your own usage, it tracks usage per client. Instead of just routing requests, it calculates what each client owes you.

Core features:

• Per-client API keys: Each client gets isolated keys with separate tracking
• Custom pricing models: Set margin percentages, fixed fees, or flat monthly rates per client
• Profit tracking: See exactly what you're making on each client relationship
• Usage dashboards: Real-time visibility into costs and revenue
• Budget controls: Set spending limits and alerts per client

Pricing:

Bizgraph exists because agencies have a specific problem: they need to bill clients for AI usage without becoming accountants. Spreadsheets don't scale. Guessing margins erodes profit.

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The Key Difference

Here's the fundamental distinction:

LLM Gateway answers: "How do I access Claude, GPT-4, and Gemini without managing three different APIs?"

Bizgraph answers: "How do I charge Client A for their chatbot usage and Client B for their research tool—automatically?"

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When to Choose LLM Gateway

LLM Gateway is the right choice if:

You're building a product, not selling services.

You're a startup building an AI-powered app. You need to switch between models for cost optimization or capability matching. You don't have "clients" in the agency sense—you have users of your product.

You want maximum model flexibility.

You're experimenting with different models for different tasks. Maybe GPT-4 for complex reasoning, Claude for writing, Gemini for multimodal. LLM Gateway's 170+ models give you options.

You want to self-host everything.

Data sovereignty matters to you. You want the gateway running on your infrastructure, not someone else's. LLM Gateway's open-source license makes this possible.

You're optimizing your own costs, not billing others.

You care about your API spend. You want analytics on which models are expensive, which are fast, which fail often. But you're not passing these costs to clients with markup.

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When to Choose Bizgraph

Bizgraph is the right choice if:

You're an agency billing clients for AI.

You build AI solutions for other businesses. They pay you monthly. You need to know what each client costs you—and what you're earning from them.

You need per-client isolation.

Client A shouldn't see Client B's usage. Each client needs their own API keys, their own limits, their own billing. Shared API keys are a nightmare waiting to happen.

You want to set custom pricing per client.

Client A is on a percentage markup. Client B wants a fixed monthly fee. Client C negotiated a flat rate. You need flexibility in how you charge, not just how you access models.

You're building recurring revenue.

You've read about the agency trap—one-time projects with no ongoing income. You want to turn AI solutions into monthly retainers. That requires billing infrastructure, not just API routing.

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When to Use Both

Here's where it gets interesting: these tools aren't mutually exclusive.

Scenario: You're an agency that wants model flexibility AND client billing.

You could:

1. Use LLM Gateway as your model routing layer (access to 170+ models, failover, self-hosting)
2. Use Bizgraph as your client management layer (per-client keys, pricing, billing)

LLM Gateway handles the "which model should this request go to?" question. Bizgraph handles the "how much does this client owe me?" question.

This setup makes sense if:

• You need models that Bizgraph doesn't directly support
• You want to self-host the routing layer for compliance reasons
• You're already invested in LLM Gateway's infrastructure

For most agencies, though, the simpler path is choosing one tool that solves your primary problem. If billing clients is the pain point, start with Bizgraph. If model access is the pain point, start with LLM Gateway.

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Feature Comparison

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The Bottom Line

Choose LLM Gateway if you're a developer or team building AI products and you want flexible, cost-effective access to multiple models. You're tracking your own usage, optimizing your own costs, and not billing external clients.

Choose Bizgraph if you're an agency or freelancer selling AI services to clients. You need per-client tracking, custom pricing, and the infrastructure to turn AI projects into recurring revenue.

Consider both if you need advanced model routing AND agency billing—though this adds complexity most teams don't need.

The question isn't "which is better?" It's "what problem are you solving?"

If the answer is "I need to bill clients for AI," you know where to start.

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Bizgraph gives agencies the infrastructure to manage AI solutions across multiple clients—isolated API keys, flexible pricing models, real-time usage tracking, and automated revenue calculations. See how it works →