Implementing an AI-Powered Telephony Service Center with ElevenLabs & LiveAPI Over the past year, advancements in real-time AI models and high‑fidelity speech synthesis have accelerated the development of AI-driven telephony systems. At Inero, we’ve had the opportunity to integrate modern telephony solutions with LiveAPI technology and ElevenLabs’ voice engine to…
Artificial intelligence and Large Language Models are buzzwords heard in nearly every industry. Many companies are wondering how to use them safely and which solution will be the most effective. There are plenty of options—and they’re often hard to tell apart. In this article, we break them down in a clear and easy-to-understand way.
In this article, we’ll break down the data privacy policies of top AI platforms. You will also learn what to do to ensure your data is not used for training Large Language Models (LLM).
In this post, we’ll explore several top open-source lightweight LLMs and how to run them on a local Windows PC—whether CPU-only or with a limited GPU—for document processing tasks.
This article explains what to focus on before deploying an AI agent, which areas of the business need to be well-prepared, and how to avoid common mistakes.
Whether you’re building a custom chatbot, agent, an AI-powered code assistant, or using AI to analyse documents offline, local deployment empowers you to experiment and innovate without relying on external services.
In this post, we conduct a comparative analysis of three popular LLMs—OpenAI’s GPT based models: 4o-mini and o3-mini, and open-source DeepSeek R1—to evaluate their effectiveness in reading and analyzing statistical data from large PDFs.
AI-driven tools are becoming increasingly prevalent across various industries, streamlining processes from simple graphic design and translations to advanced document, email, and database analysis. In this article, we will present a practical business application of an AI assistant in action. AI Agents have a wide range of applications, and their…
