Together we discuss your process automation projects along three different dimensions: cost savings, strategic value and technical feasibility. After settling for a specific project, we put special emphasis on the needs of the end users.
We are an experienced team of machine learners. Our algorithms find complicated patterns in unstructured, mostly visual and text data. Once detected, these patterns are the basis for the automation of the underlying process.
We make a point of integrating our customers in the project's code repository as well as in weekly progress meetings. Agility, clean code and a modular program structure help us to deliver easy-to-maintain software, that simply works.
Neural networks are used to detect and filter out patterns of fraud cases. Conspicuous damage reports are reported to claim handlers and checked manually.
Runways are controlled by air traffic controllers observing the runways from the tower. As this task requires constant attention and the detection of security sensitive objects on the runway or in...
Customer service agents enter information on complaints or complaints in forms. Information from these clusters can flow into the optimization of business processes.
Defective components can cause major production losses. To prevent this, an algorithm can recognize patterns and distinguish faulty parts from faultless ones at an early stage.
In high-growth cities (mainly in Asia and Africa), it becomes a major challenge for urban planners to keep track of settlements and infrastructure need.
Photos of defective spare parts are analyzed by a machine learning algorithm and the damage is classified. This information is used in the development of new products and in the selection of...
The optimum price of a building insurance can be determined by the customer specifying the address of a building, for example, and any existing pictures of the customer.
Our team has a wealth of experience in the field of software development and IT project management. We take pride in never losing sight of our customers' goals and attach great importance to designing projects from the outset in such a way that both time and budget constraints are met. Some of our employees contribute remotely from other European countries, but most of us work in our modern office in the heart of Berlin.
In February 2020 dida was selected to present ASMSpotter at the [Nvidia Inception Summit / GTC](https://www.nvidia.com/en-us/gtc/topics/ai-startups/) (see Presentation Gallery > Computer Vision /...
-- Thank you for participating in the first webinars! You can download the slides from the first webinar [here](https://dida.do/downloads/webinar-1-text-recognition-ocr-or-slides) and the slides...
dida's Dr. Petar Tomov and Philipp Jackmuth had been invited to speak at this year's Deep Learning World (DLW) on May 12th. DLW is a conference with a focus on commercial deployment of deep...
dida successfully completed the ESA project "ASMSpotter". The project investigated the feasibility of automatically identifying artisanal gold mining sites (ASGM) on satellite images using machine...