Explore Research Studies
Hybrid RAG: Boosting RAG Accuracy
Dense vector search is excellent at capturing semantic intent, but it often struggles with queries that demand high keyword accuracy. To quantify this gap, we benchmarked a standard dense-only retriever against a hybrid RAG system that incorporates SPLADE sparse vectors.
Best Design to Code Tools Compared: Detailed Analysis
The design to code landscape has transformed with AI-powered tools promising to bridge the gap between visual design and production-ready code. With 82% of developers now using AI coding assistants daily or weekly, the demand for effective design-to-code solutions has never been higher.
Benchmark 30 Finance LLMs: GPT-5, Gemini 2.5 Pro & more
Large language models (LLMs) are transforming finance by automating complex tasks such as risk assessment, fraud detection, customer support, and financial analysis. Benchmarking finance LLM can help identify the most reliable and effective solutions.
Benchmark of Top 14 AI Excel Tools to Boost Productivity
79% of companies report that they’ve already adopted AI agents, and two-thirds of those users say these agents have boosted productivity in measurable ways. We test and compare 14 AI Excel tools to see how they perform. Results show Claude Max emerged as the top performer, scoring high in both accuracy and capabilities.
AI Agents vs Agentic AI Systems
Adapted from There’s been a lot of buzz around the terms “AI agents” and “Agentic AI systems” lately. While they’re often used interchangeably, they actually refer to slightly different concepts.
10 AI Coding Challenges I Face While Managing AI Agents
From what I have observed, AI agents are particularly helpful during the exploratory phases of work, assisting with implementations or outlining potential approaches. However, they fall short in contexts that require consistent judgment or strategic reasoning. Below, I outlined the most common AI coding challenges. Click the links to jump to each section: [aim_list] 1.
How to Design an AI Infrastructure & Key Components
AI infrastructure is the foundation of current AI applications, combining specialized hardware, software, and operating methods to meet AI needs. Businesses across various industries utilize it to integrate AI into products and processes, such as chatbots (e.g., ChatGPT), facial/speech recognition, and computer vision.
AI Financial Analyst Solutions: Best Way to Maximize Efficiency
AI-powered tools have already outperformed human expertise in predictive analytics. Building on this trend, we test leading AI financial analysts, review their use cases and benefits, and examine the challenges of using AI-based financial analysis tools. Top AI financial analyst solutions * The prices for the basic versions of the tools are provided.
How ACP Enables Interoperable Agent Communication?
We’re starting to see GenAI move toward standardization, similar to how HTTP transformed the internet in the early 1990s. Just as HTTP enabled the rise of the World Wide Web, new protocols are emerging.
Optimizing Agentic Coding: How I use Claude Code
AI coding tools have become indispensable for many tasks. In our tests, popular AI coding tools like Cursor have been responsible for generating over 70% of the code required for tasks. With AI agents still being relatively new, I observed some useful patterns in my workflow that I want to share.