Bindesh Vijayan

We built @Myndlab_ai security-first — and that's not a slogan, it's the architecture. Jailbreaking AI has become a favourite move for bad actors lately: trick the model into dropping its guardrails, then misuse it. We closed that door before it could open. Every instruction on Myndlab passes through a safety layer that screens it before the AI responds — catching manipulation and abuse attempts even when they're disguised, while letting genuine builders work without friction. Security as the first tenant. Everything else builds on top. #AISecurity #ResponsibleAI #TrustAndSafety #Myndlab #MIITE #AgenticAI

Powered by custom multi-agents graph ecosystem built on #rust, while the industry is chasing #python based AI frameworks,@Myndlab_ai's architecture is unique and performant and might be one of the few AI platforms written in #rust from the ground up.

Tomorrow, I’ll be speaking at @MENABCW 2026 in Dubai. Looking forward to sharing what we’re building at Myndlab, and why AI app generation needs to move closer to real deployment, ownership, and regional use cases. See you at Hadron Founders Club.

There’s a difference between something that looks like an app and something you can actually run. Myndlab generates single and multi-architecture applications that are deployable, extendable, and built to integrate into real workflows with its AI App Recognition Agent. Not locked environments. Real systems. And real sophistication. For builders who want to ship rather than scaffold.

Collaborative AI runs on interactivity: machines and people, working in real time, across every modality. Solving it takes a community, join us.

First native Arabic AI app builder launched in UAE: Here's how it works khaleejtimes.com/business/tech/…

Can an AI app-builder actually *think* in Arabic, or is it just translating English under the hood? So I ran the test on MyndLab this morning. One Arabic prompt. Build me a POS. **2/** 12 minutes later — a production-grade POS. RTL layout, Arabic taxonomy, Arabic analytics, native navigation. Inventory, sales, expenses, reports — working, deployed. **3/** Every major AI app builder is English-first. For founders, students, and analysts across the GCC, that's a tax on imagination — translate your idea before you're allowed to build it. **4/** And the English-first tools - share another problem: they keep the human inside the loop. Prompt → read code → spot the gap → prompt again. Without engineering skills, the loop never closes. **5/** MyndLab inverts it. One intent in. Multi-agent pipeline handles spec, modules, design, code, database, deployment, error recovery. A working app comes out. No loop. No coding required. **6/** What it did with my Arabic prompt: • Parsed *intent*, not words • Identified the modules on the fly • Picked an Arabic-first design template • Shipped production code with DB + auth in 10–15 minutes **7/** Built in Dubai. Thinking in Arabic. Shipping to the world. This is what agentic building looks like when it's designed for our region — and for people whose first language isn't code. @Myndlab_ai #MIITE #GCCTech #Dubai2026 #UAE #AIAppBuilder

Most AI builders generate interfaces. Myndlab generates systems. Fully connected applications single or multi-architecture with backend logic, database structure, APIs, and authentication already in place. Not MVPs. Not demos. Enterprise-ready, deployable systems you can actually run. With tech stacks that you choose. For builders who want to ship rather than scaffold.

We just launched the Myndlab site. myndlab.ai A closer look at what we’re building. For builders who want to ship rather than scaffold.

Introducing Myndlab. Turn a prompt into a full-stack application you can actually run. Frontend. Backend. Database. Auth. Containerised code. Built in the UAE by @Permus_io, with Arabic-native support from day one. Open beta is live globally. For builders who want to ship. Start building: myndlab.ai

@_vmlops The GitHub link to the project is incorrect. Here is the corect one -> github.com/RightNow-AI/op…

The chatbot framework era might be over OpenFang just open-sourced a Rust-based Agent OS that runs autonomous agents 24/7 not just prompt-response bots 180ms cold start 40MB idle memory 40+ integrations 123+ model routing Single 32MB binary Has anyone stress-tested it yet? github.com/anmaped/openfa…

@_Investinq The fact that the RAG pipeline feeding on private data will be hit by models like ChatGPT (OpenAI), Grok, Gemini, it's already exposed!

Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell. He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data.​ The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos.​ Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data.​ The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle.​ Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai.​ It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault.​ They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time.​ Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA.​ A defense contractor could let AI reason across classified operations without data leaving a secure environment.​ Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout.​ He called it the largest and fastest growing market in history.​ The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone.​ Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent.​ But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI.​ And that's a level of power that should make everyone uncomfortable.