---
title: "Akshat Vedant - Software Engineer in Bengaluru | Tal"
description: "Meet Akshat Vedant, Full-Stack Engineer building high-scale OTT platforms and Web Apps | Improved performance for millions of users | React, Node.js, TypeScript | Micro Frontends based in Bengaluru. AI stack includes antigravity, claude code, and claude. Explore public work links including github."
image: "https://tal.club/meet/akshat-vedant-1/share-image"
---

# Akshat Vedant on Tal

## Headline

Full\-Stack Engineer building high\-scale OTT platforms and Web Apps \| Improved performance for millions of users \| React, Node\.js, TypeScript \| Micro Frontends

## About

I build high\-performance OTT streaming platforms used by millions of users across Smart TVs and web\. At ZEE5 and To The New, I’ve worked on scaling video platforms, improving rendering performance, and delivering seamless playback across constrained devices like webOS and Tizen\. Currently, I contribute to VideoReady — a modular OTT framework powering multiple streaming products —where • Improve performance and load times across devices • Build reusable, scalable UI architecture • Work on ad integrations \(CSAI/SSAI\) and playback systems • Optimize user experience for Smart TV environments Previously at ZEE5: • Worked on Smart TV apps \(webOS, Tizen\) • Built personalization and deep linking features • Improved cross\-device accessibility and reach I’m particularly interested in solving performance and scalability challenges in high\-traffic consumer platforms

## Location

Bengaluru

## AI stack

antigravity

claude code

claude

cursor

deepseek

gemini

## Work experience

Software Engineer at TO THE NEW, Oct 2024 \- Present · 1 yr 11 mos, South Asia, • Improved and optimized VideoReady, an in\-house OTT framework, enhancing performance and enabling faster development of cross\-platform streaming applications\. • Improved rendering performance of the Astro Go application by reducing DOM nodes from \~12,000 to \~4,000 \(\~66%\) and CPU usage from \~92% to \~50–55%, enhancing stability on low\-end Smart TV devices\. • Optimized application load times by 5–7% through Web Workers, virtualization, and data prefetching\. • Reduced Video Start Time \(VST\) by \~26% \(10s → 7\.4s\) via CSAI & SSAI ad integrations and manifest caching\. • Further improved startup time by \~3 seconds on low\-end Smart TVs through manifest caching and data prefetching strategies\. • Built end\-to\-end CDVR \(Cloud DVR\) functionality \(currently in development phase\) and implemented player fingerprinting for analytics and personalization\. • Revamped Player UI, improving responsiveness and consistency across Smart TV platforms\. • Led development of Profile Management system, supporting millions of users with seamless multi\-profile and personalized experiences\. • Leveraged AI\-assisted development tools \(code generation, debugging, refactoring\) to accelerate delivery, reducing timelines by \~2 sprints\.

SDE 1 at ZEE5, Nov 2023 \- Sep 2024 · 11 mos, • Built the "For You" page, utilizing Gen AI capabilities to create a personalized user experience\. • Integrated Gen AI APIs to deliver content recommendations based on user activity and viewing history\. • Developed new recommendation rails for Zee5 customers in the US, offering tailored content suggestions\. • Leveraged data analytics to identify and resolve issues, reducing "App in App" feature failures by 20%\.

Associate Software Developer at ZEE5, Jul 2022 \- Nov 2023 · 1 yr 5 mos, • Developed the "App in App" feature for LG Smart TVs, leveraging webOS events for various OTT partners\. • Implemented Deeplink for Single Sign\-On \(SSO\), enabling seamless transitions to partner applications, enhancing user experience\. • Led the development of "Concurrent Viewership" during ILT20 matches for Chromecast devices\. • Increased viewership of the Smart TV web app by 5%\. • Converted multiple components to TypeScript, boosting TypeScript coverage by 18%\.

Software Engineer Intern at ZEE5, Jan 2022 \- Jun 2022 · 6 mos, \- Built Device Details page and Settings pages using reusable UI components\. \- Integrated with REST APIs for the rewrite of the LG Smart TV Web Application\. \- Increased unit test code coverage by 12%\. \- Led the development of the Smart TV Web application for Malaysia's leading OTT platform, ASTRO\.

## Education

Bachelor of Technology, Computer Science, PES University

High School Diploma, Mathematics, Trident Pubic School

## Public links

- github: https://github\.com/Vedant2802

[View the original profile](https://tal.club/meet/akshat-vedant-1)

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