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Inna Nomerovska

Inna Nomerovska

Inna Nomerovska is the VP of Marketing and Brand Strategy at Keymakr | Keylabs. She is a tireless technology enthusiast with 15 years of experience in international marketing and startup background.

Building Robot Training Data for Warehouses

Building Robot Training Data for Warehouses

Warehouse premises are among the most complex environments for artificial intelligence systems, where standard computer vision algorithms trained on classic open datasets regularly fail. The main challenge here is the organization of the assortment, where thousands of visually identical boxes differing only by a serial number on a tiny barcode

Tactile Sensor Data Annotation for Robotic Grasping and Manipulation

Tactile Sensor Data Annotation for Robotic Grasping and Manipulation

The rapid development of robotics, AI, and machine learning technologies contributes to the creation of autonomous systems capable of effectively interacting with the environment. One of the key tasks of modern robotics is to ensure reliable capture and manipulation of objects under conditions of uncertainty. To successfully perform such operations,

Keymakr is the official annotation partner for RUKOPYS

Keymakr is the official annotation partner for RUKOPYS — the first open dataset of Ukrainian handwritten text

In April 2026, the first comprehensive open dataset of Ukrainian handwritten text - RUKOPYS - was officially released. As its official data annotation partner, Keymakr contributed to the creation of the dataset with hundreds of hours of ground truth labeling. The dataset was initiated by the Ministry of Economy, Environment,

Keymakr launches egocentric and robotics training data solutions for Physical AI systems

Keymakr launches egocentric and robotics training data solutions for Physical AI systems

Keymakr has officially launched a new suite of tools and services focused on egocentric data for Physical AI and robotics systems. It combines complex multimodal data collection "in the field" and the updated infrastructure of its own SaaS platform, Keylabs. This step confirms that the industry is now

Preventing LLM Hallucinations: Techniques & Best Practices 2026

Preventing LLM Hallucinations: Techniques & Best Practices 2026

One of the key challenges of modern large language models (LLMs) remains the phenomenon of hallucination - situations in which the model generates convincing but factually false or fabricated information. Despite significant progress in model quality in 2025-2026, this problem has not yet been fully eliminated, especially in open queries,

Transformer architecture explained

Transformer architecture explained

Before the advent of transformers, natural language processing systems struggled to handle long-term dependencies, preserve context, and scale to massively parallel learning. Traditional recurrent neural networks (RNNs) and long short-term memory (LSTM) networks processed language sequentially. The introduction of the transformer model replaced recursion with parallel attention-based processing. Today, transformers

Enterprise LLM Solutions: Custom AI Systems Guide

Enterprise LLM Solutions: Custom AI Systems Guide

A rapid transition toward multimodal systems and autonomous AI agents capable of executing complex sequences of actions in real-time is being observed. This technological wave promises the complete automation of intellectual labor; however, its implementation at the enterprise-scale faces barriers that cannot be overcome with mass consumer solutions. The primary