Explore Research Studies
Synthetic Data Chatbot: Top 26 Tools to Test and Train Them
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.
Top 8 Agentic CRM Platforms
Customer relationship management tools are getting smarter. Instead of just storing data, agentic CRM platforms can plan tasks, execute workflows, and adjust strategies autonomously. Think of them as CRM systems with built-in intelligence that actually do the work instead of waiting for you to click buttons.
LLM Parameters: GPT-5 High, Medium, Low and Minimal
New LLMs, such as OpenAI’s GPT-5 family, come with different versions (e.g., GPT-5, GPT-5-mini, and GPT-5-nano) and various parameters, including high, medium, low, and minimal. Below, we explore the differences between these versions of the models by gathering their benchmark performances and the costs to run these benchmarks. Price vs.
Multi-GPU Benchmark: B200 vs H200 vs H100 vs MI300X
For over two decades, optimizing compute performance has been a cornerstone of my work. We benchmarked NVIDIA’s B200, H200, H100 and AMD’s MI300X to assess how well they scale for Large Language Model (LLM) inference. Using the vLLM framework with the meta-llama/Llama-3.1-8B-Instruct model, we ran tests on 1, 2, 4 and 8 GPUs.
12 Reasons AI Agents Still Aren't Ready
For all the bold promises from tech CEOs about AI agents “joining the workforce” and driving “multi-trillion-dollar opportunities,” the reality is far less inspiring. What we currently have are not autonomous agents, but glorified chatbots dressed in fancy packaging; mostly mimicking scripts. Give them the same task twice, and you’ll often get wildly different results.
Agentic AI Architecture for Industrial Systems
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.
The Industrial AI Agent Landscape: 30+ Platforms to Watch
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.
AI Agent Deployment: Steps and Challenges
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.
Top 12 Patch Management Software with Pricing & Features
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.
Agentic AI Finance Benchmark: FinRobot vs FinRL vs FinGPT
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.