Skip to content

Blog · Published · Updated

OpenAI API implementation: workflow, costs and acceptance

Short answer

The OpenAI API brings a model into a process run by the company's software. When an enquiry arrives, the system reads the requirements, checks the catalogue and saves a draft quote for approval in the CRM. At Syntalith such an integration costs from €3,000 net. At 400 enquiries a month the GPT-6.1 Sol model costs about €11, and the implementation pays back in 1 month.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 3 min read

Example: the morning request inbox
Agent · ready

Statistics

Model APIs in companies: statistics 2026

1.0 mo.

payback of a €3,000 integration at 400 quote requests a month: €3,490 by hand, €535 with checking and the model. Scenario.

Figures checked: 22 October 2026

When the API is justified

If an employee chooses the documents and leads the analysis personally, a company ChatGPT plan may be enough. The API helps when you need your own trigger, data format, permissions and a write of the result. The differences in what you buy are covered in the guide a ChatGPT subscription or the API.

ChatGPT or the API
  • An employee chooses the files and leads the analysis

    ChatGPT Business

    rollout from €1,150

  • Every new enquiry from a form goes to the CRM

    an integration through the API

    from €3,000

  • Many steps, tools and decisions in one case

    an AI agent on the API

    from €3,000

From an enquiry to a draft quote

The integration step by step
  1. 01IntakeThe system gives the enquiry an ID and checks it was not processed before.
  2. 02ReadingThe model returns the requirements in a set format, with the gaps.
  3. 03CatalogueThe app pulls products and prices from an authorised source, and code checks the numbers and discounts.
  4. 04DraftA reply is created with links to the sources and data to confirm.
  5. 05WriteAfter approval the app saves the result, and sending has its own permission.

Structured Outputs gives an answer that matches the schema, but you check the correctness of the values separately: a valid price field can hold a wrong price. With tool calling, the app is responsible for authorising and carrying out the operation.

What the integration costs and when it pays back

Scenario: 400 quote requests a month through the API
Today
400 enquiries × 15 min = 100 h (€3,490)
With the system a person checks the output in 15% of the time
€524
Model, 2 calls per case, GPT-6.1 Sol
€11
Cost of one case
€8.73 today, €1.34 with the system
Saving
€2,955 a month

Payback of €3,000

1.0 month

The volume, the time and the checking share are the scenario's assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Model: 4,000 input tokens and 800 output tokens per call at OpenAI's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

GPT-6.1 Sol costs $2 per million input tokens and $10 per million output tokens according to the OpenAI API price list. At 10,000 calls with 2,000 input tokens and 500 output tokens each, that is 20 × 2 + 5 × 10 = $90 a month, which is €80. One case can need several calls, so count the billed usage from the console, including reasoning tokens. A comparison of models at the same volume is in the OpenAI and Claude API price guide.

Which safeguards belong to the implementation

The API key runs on the server side, the test environment is kept apart from production, and access is assigned to a project. Treat a document from a customer as input data, even when it contains instructions. Reading the catalogue, changing a discount and sending a quote have different consequences, so you enforce the limits in code and in account permissions.

OpenAI offers alerts and enforced spending limits for the organisation and the project. Enforcement is not instant, so the app recognises a rejected request and passes the task to the queue without retrying in a loop (spending limits).

What to check before launch

The sign-off trial
  • An enquiry with a missing price and conflicting requirements
  • The CRM unavailable during the write
  • The same event delivered again without a second quote
  • Stopping the work and a person taking the case over by hand
  • New examples that were not used to refine the instruction

Sign-off covers the correctness of the data, permissions, the salesperson's time including corrections and the cost of an accepted case. If quality is too low, narrow the scope before raising the volume. Also check results on a new batch of cases, because an instruction refined on one set can get worse on the next. Syntalith holds OpenAI Select Partner status. We discuss the integration as part of AI apps, and for the conversation a description of your systems, the number of cases a month and an example of the expected result are enough.

Worked example · Scenario

How we count the payback: quotes from customer enquiries

We run the same count for your process in the free process review.

€2,094

a month for preparing 120 quotes from customer enquiries by hand

Payback: 1.7 mo.

30 minutes per quote from an enquiry and checking in 15% of the old time are our assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. Model cost: Claude Sonnet 5.5, about 4,000 + 1,500 tokens per draft quote, at the ECB rate of 1.1205 USD per euro on 22 October 2026. The extra margin is a scenario: we assume that 1 in 40 enquiries quoted the same day ends in an order that a slow reply loses today, with a margin of €344. In the review we count it on your sales process.

See the full calculation →

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

Start with the process that takes the most time each week.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 25, 2026.

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

AI implementation

Start with the process that takes the most time each week.

The engineer chooses one process with you and calculates how much it costs today. Then we build a free prototype on 20-100 cases that your team has already handled. We write down the goal and the fixed price in the contract.

See AI implementation →
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

Questions

  • When does a company need the OpenAI API in place of ChatGPT?

    When you need your own trigger, data format, permissions and a write of the result, for example handling every new enquiry from a form and saving the case in the CRM. When an employee leads the analysis personally, a company ChatGPT plan is usually enough.

  • How much does the OpenAI API cost?

    At 10,000 calls with 2,000 input tokens and 500 output tokens each, GPT-6.1 Sol costs $90 a month: 20 × $2 + 5 × $10. Rates from OpenAI's price list. On top come tools, retries, hosting and checking time.

  • Do API data train OpenAI's models?

    According to OpenAI's documentation, API data are not used to train models by default. Abuse monitoring logs may be kept for up to 30 days, with described exceptions. Setting store: false does not automatically mean Zero Data Retention.

  • How do we limit API spending?

    OpenAI offers alerts and enforced spending limits for the organisation and the project. Once a limit is reached, requests may be rejected, so the app has to recognise that error and put the task back in the queue without retrying in a loop.

  • How much does an OpenAI API implementation with Syntalith cost?

    An automation, an AI app and an AI agent from €3,000 net. We credit an audit from €600 net toward the build. Syntalith holds OpenAI Select Partner status.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.