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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.

Optimize LLM costs

Optimize LLM costs

Large Language Models (LLMs) have become the foundational layer of modern AI products. But as implementations scale, so do costs. Many teams are finding out late that LLM pricing can get out of hand, especially as usage grows across multiple functions, users, and environments. But it's possible to

Monitoring LLMs: Track Performance & Detect Issues

Monitoring LLMs: Track Performance & Detect Issues

One of the most specific and dangerous challenges in implementing large language models is hallucinations – situations where the model generates factually false information while presenting it extremely confidently and convincingly. In a business context, this creates direct risks: * providing customers with non-existent discounts or erroneous instructions. * generating content that

Complete Guide to Labeling Workflows for LLM Training

Complete Guide to Labeling Workflows for LLM Training

The modern artificial intelligence industry has traveled the path from simple pattern recognition to the generation of complex meanings. The key difference between LLMs and classic ML lies in the necessity of instruction tuning. Raw texts from the web often contain contradictory information, errors, and biases. Annotation becomes a tool

Keymakr launches new LLM agent training and data solutions to support the next generation of AI systems

Keymakr launches new LLM agent training and data solutions to support the next generation of AI systems

Keymakr has announced the launch of a new suite of tools and services focused on training data and evaluation workflows for Large Language Model (LLM) agents and agentic AI systems. The new direction reflects growing industry demand for high-quality domain-specific datasets and structured human feedback pipelines as companies

Mastering Prompt Engineering for LLMs in 2026

Mastering Prompt Engineering for LLMs in 2026

In 2026, the capabilities of LLMs have reached a level where they are capable of complex reasoning and autonomous task execution. However, even with the high intelligence of these models, prompt engineering remains a vital component of interacting with artificial intelligence. Any LLM operates on the principle of probabilistic completion.

LLM Deployment: Complete Guide to Production-Ready Model Serving

LLM Deployment: Complete Guide to Production-Ready Model Serving

In today’s AI world, large language models open up new possibilities for automation, text generation, and interactive services. However, for such models to work effectively in real-world applications, it is necessary to properly organize model deployment and ensure stable model serving. An important role here is played by

Multimodal LLM: Visual-language models that understand images and text

Multimodal LLM: Visual-language models that understand images and text

Systems that combine image and text data can reduce interpretation errors in real-world tests. By combining image grids, text sequences, and audio signals, these language models gain richer context for better understanding and generation. These multimodal AI systems leverage multiple modalities for improved context. Each type of input uses