Freelancers using Agent.ai in Bhiwandi

Freelancers using Agent.ai in BhiwandiFreelancers using Agent.ai in Bhiwandi

I’m an AI & Machine Learning engineer with expertise in deve

Cover image for One Gate: Voice-controlled Gmail, Calendar,

One Gate: Voice-controlled Gmail, Calendar, and Drive that can't fire the wrong thing Every "AI agent" demo shows a voice command turning into a sent email like magic, but almost nobody shows the part that actually matters: what stops it from sending the wrong thing. I built proof: an agent that runs your Gmail, Calendar, Contacts, and Drive by voice reply to a thread, schedule a meeting, archive an email, find a file hands-free end to end, but never fires anything irreversible without you saying so. The honest hard part isn't getting an LLM to sound smart, it's this: a transcript goes to LLM against a strict JSON schema and comes back as an ordered plan, every step tagged reversible or not and exactly one thing in the whole system is allowed to check that flag. Finding a thread, drafting a reply, creating a calendar event: those just run. The result covers real ground without ever feeling like it's guessing: forward or reply to email with the original quoted underneath, archive/label/trash, resolve a name to a real address through your Contacts first and your mail history as fallback, schedule an event that creates quietly and only emails the invite after a second confirmation, answer "what did John say" or "what's on my calendar Thursday" grounded in content actually fetched from your account not hallucinated. No backend, no server anywhere in the loop

Cover image for What every "AI gesture control"

What every "AI gesture control" demo quietly leaves out Everyone films a hand waving at a screen and calls it AI. Almost nobody shows what's underneath that there's usually no gesture model at all. A "grab" is one distance crossing a line. Here's proof. I built a jigsaw puzzle you solve with your bare hands no mouse, no controller, no gesture classifier, no training.

Cover image for Everyone's building AR filters and

Everyone's building AR filters and calling it "computer vision magic." Almost nobody's asking what's actually happening underneath — that most of these effects are just clever masking, not detection. Here's proof. I built an invisibility cloak that runs entirely in the browser, no green screen, no chroma key, no model training. https://github.com/AnuragNagare/Ghost-frame

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Cover image for What your attention heatmap isn't

What your attention heatmap isn't telling you Everyone's staring at attention heatmaps and calling it "interpretability." Almost nobody's asking whether a single attention map actually tells you what the model used to make its decision. It doesn't. Not on its own. A raw attention map from layer 8 shows you what layer 8 attended to. It says nothing about how that signal got mixed, diluted, or overwritten by every layer before and after it. Attention rollout fixes this — and I built a walkthrough to show why it matters. Here's what makes it more than a "pretty heatmap" demo: Instead of visualizing one layer's attention, I traced how information actually flows through the full transformer stack. → Every layer's attention matrix is extracted, per head, per token → Multi-head attention is averaged, then combined with the residual connection (identity + attention) — this is the step most tutorials skip, and it's the one that actually matters → The combined matrices are matrix-multiplied layer by layer, rolling attention forward from input to output → The result: a single map showing genuine token-to-token influence across the entire network, not just one layer's snapshot The overlay shows you everything: → Per-layer attention vs. rolled-out attention, side by side → Token importance scores overlaid directly on the input text → A comparison view: which tokens raw attention says "matter" vs. which ones rollout says actually matter → Head-level breakdown so you can see which heads specialize vs. which are noise No black box. No "trust me, the model looked here." Just linear algebra, applied honestly across every layer instead of cherry-picking one. Built with PyTorch + HuggingFace Transformers + Matplotlib. Runs on any pretrained transformer, fully offline. ⚠️ Important: attention rollout is an approximation, not ground truth. It assumes attention is the primary information pathway, which ignores MLP layers and can still mislead for very deep models. Treat it as a debugging lens, not proof of causality.

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Agent.ai(1)

Abu Aasif Ansari

Bhiwandi, India

I build AI agents & internal tools that act on data

12: Followers

I build AI agents & internal tools that act on data

Ask My Docs — RAG-Based AI Chat Agent

Sounds Like AI? — AI Writing Authenticity Checker

Cover image for Creative Branding for CapCut: A Coffee Concept Redesign

CUT Coffee — Brew Your Story I reimagined CapCut as a premium coffee brand for creators. The scissors become a cup mark. The timeline becomes a film-strip sleeve. Every great story begins with a cut. Direction A — CapCut as a Different Industry https://www.linkedin.com/posts/abuaasif_capcutdesignstudio-branddesign-capcut-activity-7467333219772952576-53vt?utm_source=share&utm_medium=member_desktop&rcm=ACoAACRm5rcB0nVG0_HUX6-IXfuWqNGquZ-jMQU

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Cover image for SkillSwap Platform: Trade Your Expertise, Learn Something New

🚀 SkillSwap — Trade what you know for what you want to learn. SkillSwap is a peer-to-peer skill exchange platform where professionals trade expertise without money. You teach me Python, I teach you photography. No payments. Just skills. Core features: Skill onboarding — list what you teach & want to learn Discover partners by skill category Send & manage swap requests Personal dashboard — reputation score, upcoming & completed swaps In-app messaging with matched partners Reviews & ratings system Built on Bubble AI — started with one prompt that generated the full foundation: 8 pages, complete database (User, Skill, SwapRequest, Message, Review), and UI. Then manually refined workflows, data sources, navigation, and UX. Category: Social & Community + Dashboard 🔗 Live app: abuasifansari.bubbleapps.io/version-test 🔗 LinkedIn : https://www.linkedin.com/posts/abuaasif_promptandcircumstance-promptandcircumstance-ugcPost-7474244917997957120-JOmo/?utm_source=share&utm_medium=member_desktop&rcm=ACoAACRm5rcB0nVG0_HUX6-IXfuWqNGquZ-jMQU #promptandcircumstance #bubble #skillswap #nocode

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Agent.ai(2)

Abhishek Kumar

proMumbai, India

AI & Full-Stack Developer | Enterprise Software

5.0: Rating

4: Followers

AI & Full-Stack Developer | Enterprise Software

Indigloo Softwares - AI-Driven Software Solutions

Cover image for Meet Your New AI Personal

Meet Your New AI Personal Tutor: Learning, Evolved. Say goodbye to rigid textbooks, passive video lectures, and robotic chatbots that just paste text answers. Welcome to the Agentic Tutor—an intelligent, adaptive learning partner built to guide you step-by-step through any subject, at your exact pace. Why You'll Love Learning with Agentic Tutor Proactive Mentorship: Unlike basic search tools, your AI tutor doesn't just answer questions—it breaks down complex concepts, asks checking questions, and ensures you truly master the material. 100% Personalized Pace: Tailored explanations, custom step-by-step breakdowns, and dynamic real-time guidance adapted specifically to your learning style. 24/7 Unlimited Access: High-quality, one-on-one tutoring whenever you need it, right from your browser. Try the Live Beta Today Experience the future of interactive education right now: 👉 Launch App: agentic-tutor-mvp.replit.app (http://agentic-tutor-mvp.replit.app) Ready to level up your learning? Dive in today and see what autonomous AI mentorship can do for you!🔥

@REPLTMCP Built in with replit

Cover image for Created this video spot for

Created this video spot for Indigloo completely with AI. From conceptualizing the theme ("Clean code is engineered for growth") using Claude to AI video generation and logo animation, here is a look at what modern AI creative workflows can deliver.

Agent.ai(1)