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What this area includes

Four services covering the path from idea to a working process: understand why, prepare the foundation, implement and train people.

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AI implementation

Use cases with measurable return: triaging incoming enquiries, drafting standard replies, extracting data from documents, drafting product descriptions. We roll them out through a pilot on a limited area.

Strategy and roadmap

An inventory of processes, selection of automation candidates, assessment of impact and risks, and a rollout order for the year ahead.

Infrastructure for model training

GPU capacity and storage for training and fine-tuning on your data, including deployment inside your own perimeter.

Training employees to work with AI

Practice on real work tasks rather than general theory. We separately cover what must never be sent to external services and why.

Where this usually pays off

A good automation candidate always looks the same: many repetitive operations, tolerance for a small error rate and a person checking at the end.

Incoming enquiries

An operator checks it. The model classifies an enquiry and routes it to the right department.

Source documents

An accountant checks it when posting. The model extracts details and amounts from scanned invoices and certificates.

Product cards

A content manager checks it. The model drafts descriptions from the product specifications.

Support knowledge base

An engineer checks it before sending. The model finds the answer in your own procedures and instructions.

Contracts

A lawyer always checks it. The model compares a document with the template and highlights the differences.

Company data must not leak into someone else services. Before the pilot we decide what may be processed by an external model and what must stay inside your perimeter. For sensitive data we deploy the solution on your own infrastructure, even though that costs more.

How the implementation runs

Always through a pilot. Only what has shown results against a measurable metric is worth scaling.

01

Selecting the use case

We review the processes and count how many person-hours go into routine work. We pick one area with a clear metric.

02

Pilot

A limited launch on real data with mandatory human review. We measure the accuracy and the time saved.

03

Decision based on the results

We compare the result against the original metric. If there is no effect we close the pilot honestly, which is cheaper than scaling something that does not work.

04

Rollout and training

We embed it into the working tools, write the procedure and train employees, including the rules for handling data.

Frequently asked questions

In the scenarios we implement, no. The model prepares a draft or a preliminary decision, and a person checks it and remains responsible for the outcome. The saving is in time, not in headcount: an employee handles more requests rather than losing their job.

It will make mistakes; the question is the rate, not whether. That is why we do not take on scenarios where a single error is costly and there is no human check. In the pilot we always measure accuracy and set a threshold below which the solution is not rolled out.

For many tasks a ready-made model with well-written instructions and access to your knowledge base is enough, and it is faster and cheaper. Fine-tuning on your own data is needed when the task is industry-specific and general models do not understand it.

Noticeably cheaper than a full implementation: usually a few weeks of work on a single process. The point is to test the hypothesis cheaply before investing in infrastructure and integrations.

Related areas

The whole catalogue
Area 07 Cloud services and hosting Capacity for model training Area 09 Information security Protection of models and training data Area 16 Data and analytics Clean data before any AI Area 21 Training Hands-on practice for employees

We will find where AI pays off

Tell us about the routine work at your company: what employees do by hand every day. We will pick the use cases and propose a pilot with a clear metric.