Why we use OpenAI
We integrate OpenAI models into production systems — from GPT-4 for complex reasoning to embeddings for semantic search. Function calling, structured outputs, and streaming make GPT-4 a reliable building block for enterprise AI.
Key benefits
- GPT-4 handles complex reasoning and multi-step tasks reliably
- Function calling enables structured AI → system integration
- Embeddings power semantic search without ML expertise
- Streaming responses for real-time chat experiences
- JSON mode ensures parseable AI outputs for automation
- Fine-tuning available for domain-specific optimization
OpenAI — Frequently Asked Questions
OpenAI vs self-hosted models — when to use which?
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OpenAI for complex reasoning, rapid prototyping, and when data sensitivity allows API calls. Self-hosted (Llama, Mistral) for data sovereignty, cost optimization at scale, or offline requirements.
How do you handle OpenAI rate limits in production?
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Request queuing, exponential backoff, model fallback chains (GPT-4 → GPT-3.5 → local model), caching frequent queries, and token budget management per user/tenant.
Is it safe to send sensitive data to OpenAI?
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OpenAI's API does not train on your data (with data usage policy opt-out). For highly sensitive use cases (healthcare, finance), we use Azure OpenAI with enterprise compliance guarantees.
Ready to build with OpenAI?
Let's discuss your project requirements and how OpenAI fits your architecture.
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