IT Consulting

Over the past few years, many companies have started using artificial intelligence to generate text, summarize documents, or answer questions. However, a large part of business information does not exist only as clean, structured text. There are also scanned invoices, photographs, forms, screenshots, blueprints, delivery notes, contracts, receipts, product images, and documents in different formats.

As a company digitizes its processes, more and more systems need to communicate with one another. The CRM needs to connect with the ERP, the e-commerce platform with the inventory system, sales tools with marketing platforms, and automations with different data sources. In this context, APIs are no longer just a technical matter. They become

Expense management may appear to be a straightforward administrative process. However, in companies with professionals distributed across different projects, clients or locations, it can easily become a constant source of delays, errors and manual work. Receipts sent by email, photographs stored in shared folders, incomplete information and approvals involving several people are part of everyday

A technology solution may work correctly while a company has only a limited number of users, customers or processes. The problem arises when the business grows and its systems begin to fail, slow down or require increasing amounts of manual work. Technological scalability makes it possible to anticipate this scenario without overinvesting from the outset.

A demonstration can make an artificial intelligence solution appear convincing. However, answering a few questions correctly does not guarantee that it will perform reliably in a real-world process. Generative AI evaluation makes it possible to determine whether a solution meets the quality, cost and security requirements of the business. Why is evaluating AI different? In

As a company expands its digital products, its technology teams must manage an increasing number of environments, tools, permissions and processes. Platform engineering aims to reduce this complexity by creating a shared foundation that makes software development and delivery easier. What is Platform Engineering? Platform engineering is an approach based on creating an internal technology

When several systems share information, even a small change can affect reports, automations and business decisions. Data contracts establish clear rules for how data should be produced, modified and used. In this article, we explain what they are, what they should include and the benefits they offer. What is a data contract? A data contract

Cloud services, SaaS platforms and artificial intelligence have given companies greater speed and flexibility. They have also made technology spending more variable and harder to explain. FinOps helps organisations regain visibility and connect technology consumption with the value it delivers to the business. In this article, we explain what FinOps is and how to start

In B2B sales, a sales meeting does not end when the call is over. Very often, real progress happens afterwards: in the follow-up email, in the CRM update and in the clarity of the next steps. But in startups with small sales teams, this process is usually managed manually. After each demo, the team has

Artificial intelligence is already being used inside many companies, even when there is still no official strategy in place. Teams writing documents with ChatGPT, employees summarizing meetings with external tools, salespeople automating emails or departments testing AI solutions to save time. The problem is that teams often want to be more efficient without clear criteria