• Integrations · OpenAI API

OpenAI API integration: the model inside your product, not in somebody else's chat window

An OpenAI API integration means the model runs inside your own system: it takes your data, returns a predictable result, and does it for money you can see in advance. The difference from working in a chat window is fundamental. In a chat a person checks the answer and fixes it themselves. In a product there is nobody to check: whatever the model returned goes straight into the product card, into the email to the customer, or into the database. So the work here is not «connect the key» but building a frame in which the model's answer can be accepted without supervision.

See how it works
Price
after a free audit
Guarantee
30 days after project sign-off
What we do
the model inside your system, not in a chat
after a free audit
Price
30
Guarantee

days after project sign-off

the model inside your system, not in a chat
What we do
10
Timeline

to 30 working days

free review of the task
Start
30
Warranty

days from the date the acceptance act is signed

within 2 hours
Reply
What's included

Complete list of work and what you get as a result

  • breaking the task into the steps where the model is genuinely needed and the steps where a rule or a database lookup is cheaper
  • choosing a model for the task with the cost of one call calculated, rather than «take the newest one»
  • prompts as files in your repository, under version control, instead of a chat history
  • a structured answer validated against a schema: whatever fails validation does not go any further
  • rules against invention: the model works with your data instead of adding its own
  • a cache for identical calls — a repeat is not paid for twice
  • a queue with retries: a provider outage postpones the work rather than losing it
  • spending limits and a cut-off: a monthly ceiling after which calls stop instead of eating the budget
  • a log of calls and answers with personal fields masked
  • cost accounting per operation: what one description, one answer, one review costs
  • instructions for your own person: how to change the prompt, how to read the log, how to stop processing
  • sources in Git on your side and a 30-calendar-day warranty on the work performed
When this service isn't right

What's not included — so there are no surprises at delivery

  • training your own model on your data — that is different work and a different budget
  • paying OpenAI itself: the key and the billing account are issued in your name, we do not resell calls
  • responsibility for the content the model returned: the decision to publish stays with you
  • a legal assessment of whether your data may be sent to an external provider
  • guarantees that the model will never be wrong: errors are reduced by checks, not by promises
  • support after the warranty period, including rework for a new API version
Who it's for

Situations where this service delivers results

Scenario 1 of 4

Already tried it in a chat, now it has to run in a flow

Someone in the company pushes texts or data through a chat by hand and pastes the result back into the system. That works while the volume is small; at hundreds of items it turns into a full-time job for a live person.

We'll review your situation in a free audit

Free review of the task

Before estimating we look at what exactly you want to hand to a model and whether it is needed there at all. Often half the task is covered by a rule or a lookup in your own database — cheaper and more predictable.

What we measure

  • Whether the model is neededwe break the task into steps and show which of them are solved without it
  • Which data would leavea list of the fields that would have to be sent to the provider, and which of them need not be
  • The cost of one callan estimate from the volume of text in and out, with an example on your data
  • The shape of the answerwhether the result can be described by a schema the system can validate automatically
  • Volumehow many calls a month your real flow produces

What you get

  • a written review: what we hand to the model, what we leave to rules
  • the cost per call estimated on your data
  • a list of risks naming specific fields, not general words

Timeline: 1–3 working days

Why is it free

Without this review an estimate would be invention: the cost here depends on the volume of text, not on a number of hours.

What's next

After the review — an estimate broken down by stage and a contract with a fixed amount.

Short form: your contact and site URL

  • Contract, act and 30-day warranty

    Every project gets a written contract: scope, deadlines, amount, acceptance procedure. After delivery — act and invoice, then 30 calendar days of warranty.

  • Sole proprietor & bank transfer

    The contractor is a registered sole proprietor. Payment by invoice with closing documents.

  • Rights & access — yours

    Code, design and materials transfer to you after full payment. Domain, hosting, repository and analytics are registered to you.

  • Client portal instead of email chains

    During the project you get access to a portal: contracts, invoices, acts and project status in one place.

  • European clients

    Among our work — projects for Norway, Bulgaria, Moldova and Spain.

  • Verifiable numbers

    Every case in the portfolio comes with a link to a live site and a technical measurement.

  • Audit first, then pricing

    There is no price list on the site intentionally: the scope of the same work differs multiples between clients.

  • We say "no" when unsure

    If the task isn't ours or the deadline is unrealistic — we tell you upfront.

What affects the price

Why two seemingly identical tasks are priced differently

  • Volume of text in and outthe main driver: the provider charges for volume, not for the number of calls
  • Calls per monthdetermines whether a cache, a queue and overnight batch processing are needed
  • Complexity of validating the answera simple three-field schema and a full document with attachments are different amounts of work
  • The state of your datathe model builds an answer out of what exists; empty attributes have to be dealt with separately
  • Where it is embeddeda customer account with a live response costs more than overnight background processing
  • Confidentiality requirementsmasking fields and a separate processing circuit add work
Cases

Tasks and results in numbers — all metrics measured by us

a Ukrainian SaaS platform for AI rewriting of online-store product descriptions

Task
Build a full web application that imports catalogues from Prom.ua, Rozetka, Horoshop, OpenCart and WooCommerce in XML/YML/CSV/Excel, rewrites descriptions with an SEO structure, and sells this on a transparent pay-as-you-go model.
Solution
A Next.js application with catalogue import in four formats, adjustable text style (sales, neutral, technical) and an H2/H3 SEO structure. The public part is 8 pages (/, /login, /register, /offer, /terms, /privacy, /cookies, /dashboard/import). JSON-LD markup: SoftwareApplication, Offer, Organization, WebSite, FAQPage/Question/Answer. A PWA manifest. Payment by bank transfer to the sole trader's IBAN, minimum top-up 50 UAH.
Result
TTFB 0.22 s at 141 KB of HTML — the fastest response among the 16 measured portfolio sites. 8 public pages, JSON-LD markup with SoftwareApplication, Offer, Organization, WebSite and FAQPage, a working PWA manifest. Measured 31.07.2026.

Did not find your case?

Describe how it works on your side — we will tell you whether “OpenAI API integration” fits and what it means in your situation. No brief and no call: one question, one answer.

Process steps

Transparent stages with approval at every step

Total duration:10–30 days

  1. Reviewing the task

    1–3 days

    We break the process into steps and separate what needs the model from what a rule covers. We record which data would leave your perimeter.

  2. A prototype on your data

    2–5 days

    We take a real sample and show the result before any promises about quality. This is also where the cost of one call gets measured.

  3. The acceptance frame

    3–7 days

    The answer schema, the checks, the refusal rules. Whatever fails validation goes into a separate queue for a human, not into the system.

  4. Embedding

    3–10 days

    Queue, retries, cache, spending limits, log. The provider key is issued in your name.

  5. Full run and handover

    2–5 days

    We push the real volume through, check a sample by hand, hand over the instructions and the access. Then the 30 warranty days.

Technologies & integrations

What we build on and what it connects to

Stack

  • OpenAI API (Chat Completions, structured outputs validated against a JSON Schema)
  • Node.js or Python on your side — depending on what your system is already written in
  • a queue with retries and exponential backoff (BullMQ, Redis, or whatever you already run)
  • an answer cache keyed by a hash of the call, so a repeat is not paid for twice
  • a log of calls and answers with personal fields masked
  • a per-operation cost counter with a monthly ceiling and an automatic stop

Integrations

  • your CMS or catalogue: OpenCart, WooCommerce, Horoshop, Prom, a custom database
  • CRM and the support desk, if the model handles enquiries
  • file storage for documents and attachments
  • a notification channel (Telegram or email), so the queue does not stay silent on failure
A model in the product versus working in a chat

How this option differs from the alternative

Volumethousands of items overnight, bounded only by the provider's limits
Checking the resultautomatic against a schema, rejects go into a separate queue
Costvisible per operation, with a monthly ceiling
Repeatabilitythe prompt is in Git, the result reproduces
Provider outagethe queue postpones and retries
What we need from you

We can't start without this — best to prepare in advance

  1. access to the system we are embedding into, or its API
  2. a real sample of data for the prototype — without it any estimate would be invention
  3. a decision on which fields may be sent to an external provider and which may not
  4. your own OpenAI billing account: the key is issued in your name
  5. a responsible person on your side who accepts the result by sampling

If something is missing — let us know, we'll help you gather it or do it as a separate task.

FAQ

Most frequently asked questions — with concrete answers

How much does one call to the model cost?

The provider charges for the volume of text in and out, not for the number of calls. So the cost is calculated on your sample during the free review: we take real data, run it through, and show the figure for one operation. Before that any number would be invention.

Whose OpenAI account is it — yours or ours?

Yours. The key and the billing details are issued in your name, we do not resell calls and we do not keep your key after handover. That way you see the spending directly and can stop it without us.

What if the model invents something that is not in the data?

This is the main reason the work is not just plugging in a key. The answer is described by a schema and validated automatically; whatever fails validation does not reach the system but goes into a separate queue for a human. On top of that the prompt is built so the model works with the attributes provided instead of adding its own. Nobody can rule the mistake out entirely — but it is visible before publication rather than after.

Our data will go to a third party. Is that safe?

Part of the data does leave the perimeter — which is exactly why the review lists separately which fields would have to be sent and which can be replaced or dropped. Personal data is masked in the log. The legal assessment of whether such a transfer is permissible is your lawyer's; ours is the technical list.

Can another model be used instead of OpenAI?

Yes, and the frame does not change: the queue, the answer schema, the checks and the cost accounting stay the same. What changes is the supplier and the price per call. If the task requires that data never leaves at all, there is the option of a model on your own server — that is a different scope of work and a separate conversation.

How long does it take?

10 to 30 working days depending on where it is embedded and how complex validating the answer is. The prototype on your data is shown in the first days — it is what decides whether the rest makes sense.

What is left with us after the work?

The sources in Git on your side, prompts as versioned files, the log, instructions for your own person, and access issued in your name. A 30-calendar-day warranty from the date the acceptance act is signed: mistakes that are our fault are fixed free of charge.

And if after the prototype it becomes clear the model is not needed here?

We will say so first and show what covers the task more cheaply. The review is free precisely so this comes out before the contract rather than after.

Let us look at what in your task really needs to go to a model

We will break the process into steps, calculate the cost per call on your data, and say where the model is redundant. The review is free, we reply within 2 hours.

From measured casesTTFB 0.22 s at 141 KB of HTML

View cases
  • Reply within 2 hours
  • No commitment
  • We work under a contract

There is no price list on the site on purpose: the same work differs several times over between two clients, and a “from” figure explains nothing in that case. First a free audit — we count your pages, duplicates and speed — then we name the sum and the deadline and fix both in the contract.