OpenAI agency: GPT integration, assistants and agents

AI in real use with OpenAI

With OpenAI we deploy language models where teams really save time: in support, research, automation and internal assistant systems.

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OpenAI or Claude? Workshop as a first step

90: Releases in the last 12 months, a median of 4 days apartMany small releases usually mean bugs get fixed quickly.Green from 50 releases a year, orange below 7, red below 3.
7.46.0: Latest version, released 31/10/2026Useful to compare with the version you run.Green when at most 14 days old; orange over 120 days, red over 365 days.
168M: Downloads per month via npmIncludes automated builds: a usage trend, not a user count.Green from 50M downloads a month, orange below 100K, red below 1K.

What does an OpenAI agency do?

An OpenAI agency integrates OpenAI's language models into a company's software and processes via the API: chatbots, internal assistants, document analysis, automation. nextlevels selects the use case with you, connects the model to your data and systems, defines rules and approvals, and monitors quality and cost in operation.

From email to CRM record

Pick one of three sample emails and process it: the model fills a fixed JSON schema, we check the answer and only then write to the CRM. One email fails the check – then you see the second attempt. The answers are prepared, the schema check runs in your browser.

From:: j.berger@example.com
Subject:: Request: equipping 40 workstations

Hello, we are moving offices in spring and need monitors and docking stations for 40 workstations. Could you send us a quote by the end of the month? Best regards Julia Berger Berger Logistik GmbH

1. Prompt
2. Model
3. Schema check
4. CRM fields

{
  "type": "object",
  "required": [
    "company",
    "contact",
    "email",
    "intent",
    "urgency",
    "summary"
  ],
  "additionalProperties": false,
  "properties": {
    "company": {
      "type": "string"
    },
    "contact": {
      "type": "string"
    },
    "email": {
      "type": "string",
      "format": "email"
    },
    "intent": {
      "enum": [
        "quote",
        "support",
        "complaint"
      ]
    },
    "urgency": {
      "enum": [
        "low",
        "normal",
        "high"
      ]
    },
    "summary": {
      "type": "string"
    }
  }
}

CRM record

Company: –
Contact: –
Email: –
Request type: –
Urgency: –
Summary: –

Prepared sample answers, no live model. Emails and companies are made up, the schema check runs in your browser.

What we build for you with OpenAI

Bookable individually or as a project. If another model or no AI at all fits better, we tell you beforehand.

Finding the use case
Workshop: where does your team lose time on text and language today? We prioritize by benefit and effort.
Assistant with your own knowledge
An assistant that answers from your documents and systems and cites its sources instead of improvising.
Customer service chatbot
Answers recurring questions and hands over to a human when needed.
Document analysis
Extract data from invoices, emails or forms, in a fixed format and with a check before further processing.
AI agents
Processes in which the model uses tools: look things up, create records, write drafts. With limits and approvals.
Operations
We measure answer quality and cost per request and switch to new models when OpenAI retires old ones.

How an OpenAI project runs

We go into operation with a concrete use case, not with a demo.

First call
You describe the task, data and systems. We tell you whether a language model is the right tool for it.
Data protection and scope
We clarify which data the model may see and which provider it runs through, and define how we measure quality.
Prototype with real data
You test early with your own cases. We measure how often the answers are right and improve.
Rollout and operations
Gradual release to your team, with monitoring of quality and cost.

Discuss your project

Brands that work with us

Pros and cons of OpenAI

Pros

A wide range of models, from small, low-cost ones for classification to strong ones for complex text, all behind one API.
Structured outputs that follow a fixed schema, so results can flow straight into your CRM, ERP or shop.
A large ecosystem: many tools, libraries and developers already know the OpenAI API.
Through Azure OpenAI, the same models can run in an EU data zone at Microsoft if you need that.

Cons

European data residency requires approval and an additional agreement, and newer models cost extra there.
OpenAI retires models and APIs on a regular basis, so your solution needs planned migrations.
Billing is usage-based: without measurement and limits, running costs are hard to predict.
Answers can be wrong; important decisions need grounded sources, validation rules and human sign-off.

Is OpenAI right for you?

A good fit if …

your team spends hours every day on recurring requests, emails or documents that can be handled as text.
you want an assistant that answers from your own manuals, data sheets and systems.
you want to pull data from invoices, orders or forms into your ERP in a fixed format.
you already work with Microsoft Azure and want to run the models in an EU data zone there.

Probably not if …

fixed rules or a simple automation already solve the task reliably.
every output has to be exactly the same for the same input.
your data must never leave your company and neither an EU nor an Azure setup is an option.
nobody in the company has time to keep an eye on answer quality and costs after launch.

OpenAI and data protection: what applies

The first question is almost always: what happens to our data? For the API, OpenAI states: data sent via the API is not used to train the models unless you explicitly opt in. For abuse monitoring, OpenAI retains logs for up to 30 days by default.

OpenAI offers data residency in Europe. It requires approval by OpenAI and an additional amendment, and comes with a surcharge for newer models. Zero data retention is likewise only available after approval. An alternative is Azure OpenAI from Microsoft: there, prompts and completions are not available to OpenAI, and with an EU data zone processing stays within the EU.

Which option fits depends on your data. We clarify that with you and your data protection officer before the first prototype and document the data flows. This does not replace legal advice. Background: our post GDPR and AI: using ChatGPT and AI tools compliantly at work.

Padlock on an old wooden door with a latch

We are OpenAI integrators

We connect language models with your data, rules and approvals. The result is productive AI solutions instead of demo gimmicks.

Assistants, chatbots and agentic workflows
Prompt design, output schemas and guardrails
Integration with CRM, ERP, shop and knowledge sources
Monitoring, cost control and continuous optimization

OpenAI or Claude?

We work with both and connect models so that switching stays possible. In the end a test with your real cases decides – five questions show beforehand which way it leans, and why. The weighting follows the decision table below.

Question 1 of 5

Which cloud do you already use?

All trade-offs as a table

When OpenAI – and when Claude?

We work with both and connect models so that switching stays possible. In the end, a test with your real cases decides. Before that, these questions help:

Decision	Lean toward OpenAI	Lean toward the alternative
Cloud environment	OpenAI, if you already work with Microsoft Azure and want to run the model there through Azure OpenAI in an EU data zone.	Claude, if your infrastructure runs on AWS or Google Cloud. Claude is available there directly and can be used under your existing contracts.
Type of output	OpenAI, if you need images or speech input and output as well as text – all through the same API.	Claude, if the result is text or structured data. For image or speech output you'd need a second service.
Long documents	OpenAI, if requests are short, such as classifying emails or pulling fields from forms.	Claude, if whole contracts, tenders or manuals need to be analyzed in one go.
Existing solution	OpenAI, if code, prompts and tests are already tuned to the OpenAI API and the quality is right.	Claude, if its answers are noticeably better for your task in testing. Then the switch is worth it despite new prompts and tests.
Talent and tooling	OpenAI, if you want the widest choice of libraries, examples and developers who already know the API.	Claude, if answer quality matters more to you than the platform. With frameworks such as LangChain, both providers run on the same code.

As of October 2026

OpenAI compared

OpenAI next to technologies of the same category, measured with the same public sources.

OpenAI compared
Figure	OpenAI	Anthropic (Claude)	LangChain
Releases in 12 months	90	92	85
Median between releases	4 days	3 days	4 days
Latest version	7.46.0 (31/10/2026)	1.3.0 (23/10/2026)	1.6.0 (28/10/2026)
Downloads per month	168M (npm)	185M (npm)	12M (npm)
Security advisories (12 months)	0	2	1

Sources: OSV.dev, npm · as of 31/10/2026. Figures are indicators, not a verdict on quality. Go to the pages: Anthropic (Claude) · LangChain

Natural language as an interface

OpenAI suits support, knowledge access and internal assistants because language directly becomes the interaction model. We define clear roles, contexts and quality boundaries.

Structured output instead of free-text chaos

Where processes must stay deterministic, we combine models with output schemas, validation and downstream rules.

Retrieval and tool integration

OpenAI only becomes truly useful with access to your data and systems. We connect knowledge sources, APIs and approval processes in a controlled way.

Quality, cost and governance

We measure response quality, token consumption and failure paths. That keeps AI economical and traceable, even as the use case grows.

Support, sales and internal knowledge work

OpenAI accelerates answers, summaries and research. With clean source integration, teams measurably reduce manual effort.

Automated process decisions

Classification, extraction and prioritization can be integrated directly into operational workflows when approvals and escalations are well modeled.

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Frequently asked questions about OpenAI

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Is our data used for training?

Not with the API: OpenAI states that API data is not used for training unless you explicitly opt in. Abuse monitoring logs are retained for up to 30 days by default (as of October 2026).

Can the data stay in the EU?

OpenAI offers data residency in Europe; it requires approval and an additional amendment. Alternatively, the same model runs through Azure OpenAI in an EU data zone. Before the project we clarify which option fits your data.

How do you prevent wrong answers?

It cannot be ruled out completely. We have the model answer from your own sources, set fixed output formats, check results automatically and build in human approval for important decisions.

OpenAI or another model?

We decide that per task. We also work with Claude from Anthropic and connect models in a way that keeps switching possible. What counts is quality on your task, data protection and cost.

What does an OpenAI solution cost to run?

OpenAI charges by usage, that is, by the amount of text processed. Cost depends on model, request volume and text length. We measure it from the prototype onwards and choose the smallest model that solves the task reliably.

When is OpenAI not the right choice?

When fixed rules or simple automation solve the task reliably. That is cheaper and more predictable. And if every output has to be exactly the same, a language model is the wrong tool.

Sources

As of October 2026

Your edge with OpenAI

LLM projects rarely fail at the model – they fail at processes and integration. We build OpenAI solutions that deliver measurable value and stay operationally safe.

Focus on real business processes instead of AI theatre
Clean system integration and clear responsibilities
Privacy and quality requirements considered from day one
Fast prototypes with a viable production path

Ready for your OpenAI project?

Let's talk about your requirements – we'll get back to you within one business day with concrete next steps.

What's it about?

Discuss your project +49 (0) 2161 539 71 60

Paul Kalisch

Executive Partner

30 minutes by video or phone
You talk directly to a partner, not to sales
You get the order of steps, risks and rough costs

+49 (0) 2161 539 71 60 info@next-levels.de

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* Sources: npm (31/10/2026) · Green: strong, orange: weaker, red: notably weak, each against usual values. A pointer, not a verdict.