A Private Alternative to OpenAI
If you're using OpenAI's API and wondering whether there's a way to keep the same interface while gaining control over where your data goes, this page explains what that looks like in practice.
Why consider an alternative
OpenAI's API works. The models are capable. The developer experience is mature. But for some organizations, the defaults create friction.
Data privacy concerns
Every prompt you send to OpenAI travels to their infrastructure. For many workloads, that's fine. For sensitive data—client information, internal documents, proprietary processes—it may conflict with your data policies or your clients' expectations.
Cost unpredictability
Pay-per-token pricing scales with usage, which is flexible but hard to budget. A spike in demand can mean a spike in costs. For organizations that need to forecast expenses, this model creates uncertainty.
Regulatory requirements
If you operate under GDPR, handle healthcare data, or work with clients who require specific data handling guarantees, sending inference requests to a US-based provider may complicate your compliance position.
Juice Factory vs public AI providers
| Dimension | Public AI (OpenAI, etc.) | Juice Factory |
|---|---|---|
| Data residency | US-based servers | EU-only infrastructure |
| Data retention | Provider's policy | No retention, no logging |
| Pricing model | Pay-per-token | Predictable capacity-based |
| Interface | OpenAI API | OpenAI-compatible |
| Vendor lock-in | High | Low (standard interface) |
Data residency
Your inference requests stay within the EU. No transatlantic transfers. No ambiguity about jurisdiction.
Pricing model
Instead of paying per token, you get dedicated capacity. Costs become predictable. Budgets become manageable.
Vendor independence
Because the interface is OpenAI-compatible, switching doesn't require rewriting your applications. If you later decide to move elsewhere, your code still works.
What stays the same
OpenAI-compatible interface
If your code calls the OpenAI API today, it can call Juice Factory's endpoint instead. Same request format. Same response format. Same SDK compatibility.
Same models, different infrastructure
You're not downgrading capability. You're changing where inference happens—from shared infrastructure to dedicated, EU-based infrastructure.
Existing code works
No refactoring. No new SDKs. Change the base URL, and your applications continue to function.
What changes
Your data stays in the EU
Inference happens on infrastructure located in the European Union. Data residency is guaranteed, not aspirational.
You control the infrastructure
This isn't multi-tenant. Your inference runs on capacity dedicated to you. No shared queues, no noisy neighbors.
Predictable monthly costs
No more calculating token budgets or worrying about usage spikes. Capacity-based pricing means you know what you'll pay.
Migration path
Endpoint swap
Migration is a configuration change. Point your OpenAI client to Juice Factory's endpoint URL. That's it.
# Before
OPENAI_BASE_URL=https://api.openai.com/v1
# After
OPENAI_BASE_URL=https://api.juicefactory.ai/v1
No code rewrite required
Your existing integrations, SDKs, and workflows continue to function. The API contract is the same.
Next steps
If you're evaluating alternatives to OpenAI—whether for compliance, cost, or control—request access to see how Juice Factory fits your requirements.
We'll help you understand what integration involves and whether private inference makes sense for your use case.