•
NASSCOM Foundation • 12d
Feeling bogged down by endless data entry, form-fills, and ticket juggling? 😩 Stremly is built for businesses to automate every repetitive task—in parallel—so your team can focus on what matters. Here’s how: NoX (AI Wingman): Observes your browser workflows end-to-end (emails → tickets, web scrapes, reports) Live “showback” for instant validation and correction Autopilots complex chains of actions alongside you Orion (AI Employee): Learns your desktop app workflows (file handling, form-filling, window management) Executes tasks securely in sandboxed containers Scales out parallel execution across machines or users Over time, Stremly learns your business context and builds its own intelligence—evolving into a full AI employee that thinks and works like you do. 🔗 Visit www.stremly.ai ✉️ Want to know more? Drop me a message or comment below! What one task would you hand off today? 👇 #AI #Automation #Productivity #FutureOfWork #Stremly
Hey I am on Medial • 8m
Recently, Sam Altman has said that AGI may come as early as 2025. It will revolutionize the whole world as we see. I have been training AI LLM models for quite some time. My personal take is that while AI learns things exponentially it may not be abl
See MoreAI Automation | Grow... • 4m
🚀 Agentic AI: The Future of Autonomous Automation 🤖 Agentic AI is transforming how we automate and make decisions. Unlike traditional AI, which follows strict commands, Agentic AI acts independently, sets goals, adapts, and executes tasks with min
See More•
NASSCOM Foundation • 4m
I have an idea of building a simple intuitive drag and drop editor to allow users to build advanced and complex AI agentic workflows for bigger task automations. It will allow the user to customise the agent behaviour to the fullest. Also allowing us
See More。◕‿◕。 • 19d
What’s One Task You’d Gladly Pay to Automate? Lately, I’ve been exploring ways to automate repetitive work and making AI workflows. It's crazy how many hours we waste on things that could be handled automatically. But instead of building random stuf
See MoreAI Deep Explorer | f... • 3m
"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin
See MoreDownload the medial app to read full posts, comements and news.