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Sales teams spend hours every day on tasks that should never see a human. Research a prospect, score them against their fit, and put it all into a CRM. These are repeatable, rule based processes AI workflows driven by multi-agent systems can do all three, with speed and consistency that no human team can match. […] The post AI Workflows for Sales Teams: Prospect Research, Lead Qualification, and CRM Updates on Autopilot Using LangGraph appeared first on Analytics Vidhya.
Read full articleDeepMind's framework highlights the need for robust AI delegation protocols, emphasizing trust, accountability, and resilience in multi-agent systems. The post Google DeepMind proposes Intelligent AI Delegation framework for task management appeared first on Crypto Briefing.
Walmart has reportedly begun limiting employees’ use of an internal AI assistant called Code Puppy after demands placed on the LLM backing the tool were higher than expected. Employees of Walmart were encouraged to use Code Puppy without any stricture or stipulations as to the limits of use, but Walmart is now assigning employees a […] The post Walmart’s AI workflows meet the realities of the balance sheet appeared first on AI News.
JetBrains releases Mellum2 under Apache 2.0 — a 12B MoE model trained on 10.6 trillion tokens for AI workflows. The post JetBrains Releases Mellum2: A 12B MoE Model for Fast, Specialized Tasks in Multi-Model AI Pipelines appeared first on MarkTechPost.
The post NVIDIA’s AI Agents Automate Signal Discovery in Quant Finance appeared on BitcoinEthereumNews.com. Darius Baruo May 22, 2026 00:59 NVIDIA’s NeMo Agent Toolkit enables AI-driven automation for financial signal discovery, reducing research cycles in quantitative trading. NVIDIA has unveiled a new application of its NeMo Agent Toolkit, showcasing how multi-agent systems (MAS) can transform financial signal discovery in quantitative trading. By automating traditionally manual processes, the system reduces research cycles and enhances the efficiency of uncovering alpha-generating signals, a critical component of systematic trading strategies. According to the blog post authored by NVIDIA’s Peihan Huo, the system coordinates three specialized AI agents: the Signal Agent, Code Agent, and Evaluation Agent. Together, these agents operate in a continuous loop of hypothesis generation, backtesting, and refinement. This self-improving workflow leverages NVIDIA’s Nemotron
See how sales teams can use Codex to create pipeline briefs, meeting prep packets, forecast reviews, account plans, and stalled-deal diagnoses from real work inputs.
Some of the positions focus on AI-native development, data engineering and analytics, cloud-based engineering, and agent and model development as well as prompt engineering and new AI workflows.
In this tutorial, we build a Groq-powered agentic research workflow that runs directly using Groq’s free OpenAI-compatible inference endpoint The post A Groq-Powered Agentic Research Assistant with LangGraph, Tool Calling, Sub-Agents, and Agentic Memory: Lets Built It appeared first on MarkTechPost.
Learn the top Python frameworks for LLM apps covering fine-tuning, model loading, serving, RAG pipelines, multi-agent systems, and evaluation.
