AI
Explore practical insights, research, and benchmarks on artificial intelligence, including generative AI, large language models, RAG, governance frameworks, MLOps practices, and AI hardware. Gain an understanding of key tools, implementation strategies, and enterprise use cases shaping the AI landscape.
10 AI Procurement Use Cases & Case Studies
As the benefits of artificial intelligence (AI) are appreciated by a greater audience, the number of AI use cases in different industries expand daily. AI in the procurement sector is no different.
Test Automation Documentation with Best Practices
Test automation is vital for ensuring the quality and reliability of applications in software testing and development. Businesses and QA teams are transitioning from manual testing to automation testing as it can: [aim_list] [/aim_list] What often goes overlooked is the role of effective documentation in maximizing the benefits of test automation.
Large Quantitative Models: Applications & Challenges
Modern systems are becoming too complex for traditional statistical analysis, as institutions now handle massive datasets, including patient data, weather data, and financial market data. Large quantitative models (LQMs) help by processing these datasets, integrating structured and unstructured data, and applying predictive modeling to uncover patterns and provide data-driven insights that traditional methods cannot deliver.
AP AI Applications & Tools for Accounts Payable Processes
Manual accounts payable processes are often slowed down by preventable issues such as fraud exposure, data entry mistakes, delayed approvals, and limited visibility into spending. AI-driven AP solutions address these pain points by automating routine tasks, improving accuracy, and creating clearer oversight across the payment cycle.
Top 7 Speech Recognition Challenges & Solutions
Speech recognition systems (SRS) power voice assistants, transcription tools, and customer service automation. Although speech recognition improves efficiency and user experience, choosing the right solution is challenging. Key questions include its accuracy in noisy settings, ability to handle specialized terms and accents, balance between speed and reliability, and approach to privacy and hallucination risks.
Top 5 IBM Watsonx Competitors
Businesses use conversational AI to handle customer questions at scale and reduce wait times. While IBM’s Watsonx Assistant is one of the more established solutions in this space, it isn’t always the best fit for every team. Factors like company size, budget constraints, and technical resources can all influence whether it’s the right choice.
Top 7 Open Source AI Coding Agents
In prior evaluations, we benchmarked both open-source and proprietary Agentic CLIs, focusing on their performance in web development tasks, and some open-source agents performed as successfully as the paid options. Therefore, we also listed the top open source coding agents for users with privacy concerns.
Generative AI for Email Marketing: Applications & Examples
Generative AI has evolved beyond basic email content creation to enable real-time personalization, multimodal interactions, and cross-channel orchestration that responds to customer behavior.
State of OCR technology in 2026: Is it dead or a solved problem?
Optical Character Recognition (OCR) is one of the earliest areas of artificial intelligence research. Today, OCR is a relatively mature technology, and it is no longer called AI, which is a good example of Pulitzer Prize winner Douglas Hofstadter’s quote: AI is whatever hasn’t been done yet.
Best RAG Tools, Frameworks, and Libraries
RAG (Retrieval-Augmented Generation) improves LLM responses by adding external data sources. We benchmarked different embedding models and separately tested various chunk sizes to determine what combinations work best for RAG systems. Explore top RAG frameworks and tools, learn what RAG is, how it works, its benefits, and its role in today’s LLM landscape.