Technology
OpenAI Development Services — GPT, Embeddings & Realtime APIs
Production-grade integrations with GPT-4o, GPT-4.1, o-series reasoning models, Realtime voice, embeddings, and the Assistants API.
What we build with OpenAI
- GPT-4o, GPT-4.1, and o-series model integration with cost-aware routing
- Retrieval-augmented generation using OpenAI embeddings + vector stores
- Realtime API voice agents with streaming audio and tool use
- Function calling, structured outputs, and JSON-schema-validated tool flows
- Fine-tuning, distillation, and evaluation pipelines for domain-specific tasks
- Guardrails, prompt injection defense, and PII-safe redaction layers
Why DiveScale
Built by engineers who ship OpenAI in production
DiveScale ships OpenAI-powered products that work past the demo stage. Our engineers have deployed GPT-4-class systems for healthcare, hospitality, and SaaS clients — handling production traffic, audit logs, and the unglamorous edges that decide whether an AI feature earns its place in the product.
We design for evaluation first. Every system we build comes with golden datasets, regression tests, and a feedback loop, so when OpenAI ships a new model your team can roll forward in days instead of months.
Beyond the API call: rate-limit handling, retries, streaming UX, observability with Langfuse or OpenTelemetry, and a thoughtful cost model that lets you switch between GPT-4o and o-series reasoning models based on the actual task — not a guess.
OpenAI use cases we deliver
How we deliver
Our OpenAI delivery process
- 01
Use-case validation
We co-run a discovery sprint to qualify the AI use case, pick the right model tier, and define what 'good' looks like with measurable evals.
- 02
Prototype with evals
A working prototype in under 2 weeks, backed by a golden dataset and an automated eval harness — so we can measure quality, not vibes.
- 03
Production hardening
Rate-limit and retry strategy, fallback models, cost budgets, prompt versioning, PII redaction, logging, and SOC 2-aligned controls.
- 04
Ship, monitor, iterate
We deploy, instrument with Langfuse or OpenTelemetry, and stay on for model upgrades, prompt iteration, and cost optimization.
Related technologies
Anthropic (Claude)
Production builds on Claude Opus, Sonnet, and Haiku — long-context reasoning, tool use, prompt caching, and Computer Use agents.
Learn moreLLMs
Production LLM engineering — model selection, RAG, fine-tuning, evals, guardrails, and the operational layer that keeps quality high.
Learn moreAgentic Workflows
Multi-step AI agents that plan, call tools, write to systems, and stay inside policy — with human-in-the-loop checkpoints where it matters.
Learn morePython
Production Python engineering — FastAPI services, async pipelines, AI/ML workloads, data engineering at scale, and the typed, tested, observable discipline production Python deserves.
Learn moreOpenAI — Frequently Asked Questions
We pick per task. GPT-4o handles most chat, vision, and tool-use traffic; o-series reasoning models cover planning, math, and code-heavy work; GPT-4.1 mini and nano cover high-volume cheap calls. We benchmark on your data before locking in.
