AI Agents
AI agents are software systems that use reasoning, planning, and tools to assist or automate complex tasks. We compare the top open-source and commercial agents.
Remote Browsers: Web Infra for AI Agents Compared
AI agents rely on remote browsers to automate web tasks without being blocked by anti-scraping measures. The performance of this browser infrastructure is critical to an agent’s success. We benchmarked 8 providers on success rate, speed, and features. To do this, we executed 160 automated tasks, running 4 distinct scenarios 5 times for each service…
Large Action Models: Hype or Real?
Following the launch of Rabbit, an AI device that can use mobile apps, the term large action models (LAMs) is getting popular. These models move beyond conversation by turning LLMs into “agents” that can connect the siloed, app-driven world without requiring users to click on apps or integrate APIs. The line between hype and reality…
Computer Use Agents: Benchmark & Architecture
Computer-use agents operate real desktops and web apps. Their designs, limits, and trade-offs are often unclear. We break down how leading systems work, how they learn, and how their architectures differ. We also reference a focused UI-grounding benchmark on 100 desktop screenshots, across 4 task types and 5 runs per sample. It isolates the quality…
Mobile AI Agents Tested Across 65 Real-World Tasks
We spent 3 days benchmarking four mobile AI agents (DroidRun, Mobile-Agent, AutoDroid, and AppAgent) across 65 real-world tasks using an Android emulator with applications such as calendar management, contact creation, photo capture, audio recording, and file operations. See benchmark results including real-world performance comparison, costs and execution times: Mobile AI agents performance comparison DroidRun Highest…
Top 30+ Agentic AI Companies
Though AI agents are being hyped and some companies rebrand their chatbots as agentic tools, there are still a few agents in production. Previously, we benchmarked several capable AI agents over several real-world tasks. We listed: Enterprise in agentic AI developments that conduct AI research or provide agentic development environments/tools. Companies with agentic AI applications…
AI-Based Stock Trading: Which Gen AI Tool Is Better
LLM tools have been used in AI-based stock trading since their emergence.37 I tested 14 generative AI models for AI-based stock trading to evaluate their ability to forecast price changes of 132 stocks using the provided information. The results show that ChatGPT 5 Thinking model and the Gemini 2.5 Pro model delivered the best performance.…
Agentic AI Finance Benchmark: FinRobot vs FinRL vs FinGPT
79% of executives report that their companies have started adopting AI agents, yet 34% are currently using them in accounting and finance.51 We conduct a benchmark on 3 agentic AI finance tools tailored for financial workflows. Results suggest that FinGPT appears better suited for financial statement analysis, FinRobot shows relative strength in valuation tasks, and…
Agentic AI for Cybersecurity: 10 Use Cases & Examples
Agentic AI refers to AI systems that combine models like large language models (LLMs) with automated workflows, tool integration, and decision support. These systems assist security teams in SecOps and AppSec by analyzing alerts, automating routine tasks, and supporting investigative work. Explore structured, real-world use cases of agentic AI in cybersecurity, as well as what…
Top 15 Accounting AI Agents
Tools like Dext, AutoEntry, and Hubdoc have automated data extraction and transaction posting. But these systems are fundamentally still rule-based, often requiring accountants to jump between spreadsheets. Thus, after reviewing the documentation and watching demos, we picked the top 15 AI-based accounting agents: Commercial accounting AI agents that autofill forms for daily bookkeeping and the…
AI Agent Vulnerability with 192 Real-life Incidents
Understanding how AI agent vulnerability makes systems fail, whether through security exploits, guardrail breakdowns, or data exposure, has become critical as these systems take on increasingly autonomous roles in business workflows. To map the real-world risk landscape of AI agents, we reviewed 192 documented vulnerability incidents spanning March 2016 to May 2026, drawing on sources.…