OpenAI and Claude API integration that holds up in production, not just in the demo
An OpenAI or Claude API integration connects your application to a large language model through the provider's API, so your product can summarise, extract, classify, draft or answer questions from your own data. The API call is the easy part. The work is in reliable structured output, choosing the right model for each task, controlling cost and rate limits, handling data correctly, and testing that catches regressions when prompts or models change. Sysvoy adds LLM features to existing web and SaaS products in Python, TypeScript and Node.js. Most integrations cost $3,000–$10,000 and take 2–4 weeks.
Where OpenAI and Claude API integration projects stall
And what we do differently.
Parsing free text
Code that scrapes answers out of prose breaks on the first odd reply. We use structured outputs validated against a schema, which both providers now support.
The biggest model for everything
Sending every request to the top model multiplies the bill for no measurable gain. We test smaller models first and route by task.
Prompt changes with no tests
A tweak that fixes one case quietly breaks ten others. Every change runs against your test set before it ships.
What we build
AI features in your product
Summaries, drafting, classification and search inside your SaaS, behind your own sign-in and permissions.
Document and data extraction
Invoices, forms, emails and PDFs turned into validated JSON that matches your schema, ready for your database.
Assistants grounded in your data
Chat over your product data or documents, with answers tied to sources. For larger knowledge bases, see our RAG development work.
Tool calling into your APIs
The model looks up orders, creates tickets or updates records through your existing API, with confirmation steps for anything risky.
Multi-provider setups
One layer over OpenAI, Anthropic, AWS Bedrock, Google Cloud and open-weight models, so you can switch or fall back without rewriting features.
Cost and reliability fixes
An existing integration that's slow, expensive or breaks on odd inputs, reworked with caching, smaller models where they pass, and tests.
How we deliver
From the first workshop to production. How we work
Define the task and the test
We collect real inputs with the outputs you expect. That set picks the model and catches regressions later.
Choose the model by measurement
We try smaller models first. The largest models cost around 100 times more per token than the smallest, so we use them only where the test shows they're needed.
Build for production
Schema-checked structured outputs, retries and timeouts, streaming, rate-limit handling, and logs with personal data redacted.
Control the bill
Prompt caching, batch processing for work that can wait, token limits, and per-feature budgets with alerts.
OpenAI and Claude APIs compared on data handling and cost features, November 2026
| OpenAI API | Claude API (Anthropic) | |
|---|---|---|
| Training on your API data | No, unless you opt in | No, without express permission |
| Default retention | Abuse-monitoring logs for up to 30 days | Inputs and outputs deleted within 30 days |
| Zero data retention | On approval | On approval, except the most capable models |
| EU processing | Yes, EU data residency per project | Not on Anthropic's own API; through AWS Bedrock or Google Cloud EU regions |
| HIPAA | BAA available for eligible endpoints | BAA available; Batch and Files APIs excluded |
| Batch discount | 50%, results within 24 hours | 50%, results within 24 hours |
| Structured outputs | Generally available | Generally available |
A good fit when
- You want an AI feature live in weeks without hiring an ML team.
- Your prototype works but is slow, expensive or returns output your code can't parse.
- Customers ask where their data goes, and you need clear answers on retention and region.
What we build with
- Python
- TypeScript
- Node.js
- OpenAI API
- Anthropic Claude API
- AWS Bedrock
- Google Cloud
- Microsoft Foundry
- Langfuse
- PostgreSQL
Related work
AI commerce assistant
Self-hosted AI shopping assistant, Typesense product search and HubSpot integration for a US B2B distributor.
US distributormidpage.ai
AI research platform that layers analysis over case law for litigators and legal teams.
midpage.ai ↗AI security platform
AI-driven security platform and SOC tooling for a European cybersecurity company.
Client under NDA
Planning a budget? Read our guides
- AI agent development costReal price ranges from a studio that builds AI agents, with the timelines, running costs and trade-offs behind them.
- RAG development costWhat a retrieval-augmented generation system costs to build and run, from a studio that ships them. Price tiers, monthly infrastructure, build vs buy and two real examples.
Common questions
Not answered here? Email contact@sysvoy.com.
How much does an OpenAI or Claude API integration cost?
Most integrations into an existing app cost $3,000–$10,000 and take 2–4 weeks, depending on the number of features, the data involved and the testing needed. Model usage is billed by the provider per token and paid by you at cost. Larger builds, such as agents or RAG systems, are priced separately in our AI agent and RAG cost guides.
Should we use OpenAI or Claude?
It depends on the task, so we test both on your own examples and compare quality, speed and cost. Both providers offer models from small and cheap to large and capable, structured outputs and tool calling. We build behind a thin provider layer, so switching or using both later is a configuration change, not a rewrite.
Will our data be used to train their models?
Not by default. As of November 2026, OpenAI doesn't train on API data unless you opt in and keeps abuse-monitoring logs for up to 30 days. Anthropic doesn't train on API data without express permission and deletes inputs and outputs within 30 days by default. Both offer zero data retention to approved customers, with some exceptions for Anthropic's most capable models.
Can our data stay in the EU?
Yes. OpenAI offers EU data residency per project, with processing inside the EU. Anthropic's own API has no EU option, so for Claude we use AWS Bedrock or Google Cloud in EU regions. Regional processing costs about 10% more on both routes.
How do you keep API costs down?
Smaller models wherever they pass the test; prompt caching, which bills repeated context at a tenth of the normal input price or less; the batch APIs, which both providers discount by 50% for work that can wait up to 24 hours; tight token limits; and budgets per feature with alerts.
What happens when a provider changes or retires a model?
We pin model versions, so nothing changes without a decision. Before switching, we rerun your test set on the new model and compare results. The provider layer means a switch touches configuration, not your product code.
Can you work inside our codebase?
Yes. We work in your repository through pull requests, follow your conventions and review process, and hand over documentation and tests with the feature.
Other services
- AI agent developmentProduction AI agents and multi-agent systems that take research, triage, document review and operations off your team.
- LLM & RAG developmentRetrieval pipelines grounded in your own data, with evaluation and citations so answers can be checked, not just trusted.
- AI for securityAI-driven security platforms and SOC tooling — and hardened LLM products that can't be talked into leaking data.
- SaaS product developmentFull-stack Next.js, Node and TypeScript products — web and mobile — from a validated MVP to a platform that scales.
- Integrations & cloud migrationSalesforce and HubSpot integrations, legacy systems connected to modern ones, and applications moved to the cloud.
- Dedicated development teamsSenior engineers from our Lahore studio who work inside your tools and rituals, with overlap hours agreed upfront.
Have something to build?
Tell us where things stand and what you need. A short message is enough to start.