generative AI

From Prompt to Pipeline: Engineering Deterministic Outputs from Non-Deterministic AI Models

Generative AI and large language models (LLMs) have transformed the capabilities of various industries, from contract summaries to AI assistant prompting. These models, however, are non-deterministic in nature, even with their power, i.e., identical prompts will yield varying outputs when … Read More

AI Observability: The Missing Link Between AI Pilots and Production Deployments

The uptake of artificial intelligence has been fast, yet the success of AI projects is disproportional. Most organisations invest a lot in pilots, chatbots, and recommendation engines, but many of them are unable to stabilise these systems in a scalable … Read More

The Compound AI Systems Revolution: Why Single-Model Solutions Are Already Obsolete

During most of the previous ten years, the development of artificial intelligence was determined by the volume and capacity of specific models. Big data, greater model dimensions, and more exact benchmarks became colloquially referred to as innovation. Since the first … Read More

Understanding the Difference Between Generative AI and Traditional AI

The artificial intelligence landscape is evolving rapidly, with generative AI vs traditional AI becoming a critical decision point for businesses. According to a McKinsey report, nearly 40% of new AI investments target generative AI, yet traditional AI still powers over … Read More