Kategorie: KI Forschung

79% of executives report that their companies have started adopting AI agents, yet only 34% are currently using them in accounting and finance. We conduct a benchmark on 3 agentic AI finance tools tailored for financial workflows. Results suggest that Along with benchmark details, see use cases of AI agents in finance and challenges of […]

Keeping your IT infrastructure secure is a constant challenge. Unpatched systems and outdated software are among the most common entry points for cyberattacks. Following a comprehensive review of the market’s leading patch management solutions, we’ve identified the best tools to help you defend against these vulnerabilities. See the best patch management solutions to protect your […]

Synthetic data is expected to surpass real-world data as the primary source for AI training by 2030, and chatbots are no exception. Once mainly used to train bots when real conversations were scarce or sensitive, it’s now just as vital for testing, validating performance, stress-testing, and ensuring compliance when real logs aren’t safe or available. […]

Organizations are increasingly relying on AI agents to manage tasks that once required constant human effort, such as responding to customer queries, automating workflows, or coordinating data across different systems. While these agents can extend productivity and reduce operational load, their value is realized only when they are deployed correctly in production. Deployment ensures that […]

Agentic CRM platforms are customer relationship management tools that can plan, execute, and adjust workflows autonomously without constant human supervision. Here are the main agentic CRM platforms, ranked by their actual capabilities, market presence, and real-world results. How We Selected These Platforms We focused on platforms that actually work in real businesses and have proven […]

Industrial AI agents address the limitations of siloed data by autonomously integrating and deriving actionable insights from IoT, controls systems (e.g. SCADA), and connected assets. Below is a categorized review of over 30 key vendors offering AI agent platforms and tools: To explore each section and discover the relevant vendors, tools, platforms, capabilities, and focus […]

Agentic AI allows natural language interaction with industrial systems, enabling users to query data and receive actionable insights. We will outline a reference architecture designed for industrial environments, describe how task-specific agents and tools can be orchestrated. We will also explore current state of natural language interfaces (NLIs) in industrial systems. Why do industrial systems need […]

Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).  Mean Average Precision (mAP) served as our primary accuracy metric, supplemented by latency, cost and class-specific performance […]

We have been experimenting with AI development tools in our code generation and code editing benchmarks for months. We have seen that AI agents like Claude Code are highly capable of software development, achieving ~%90 success rate.  To provide a clearer picture of the current state of AI agents for software development, below, we listed […]

Deploying your own AI model or, in some cases, fine-tuning pre-existing models comes with several challenges: Open-source platforms that offer unified APIs help address these challenges by enabling multi-cloud deployment, optimizing GPU resource management. Below, I listed 11 examples of open source platforms/libraries: Brief overview of 11 platforms and libraries When picking these platforms, I […]