Software • AI • Cloud • Blockchain

PhotonStar Studio

Engineering the
Digital Future

PhotonStar helps teams ship production‑grade web apps, mobile apps, AI‑powered systems and blockchain platforms faster. Every product is built for reliability, observability and scale from the first sprint.

Explore Solutions View Case Studies
PhotonStar in numbers

Intelligent digital ecosystems built with modern tech stacks

PhotonStar is a product‑first team of engineers, designers and data scientists building dependable systems using cutting-edge technologies. We leverage React, Angular, Vue.js, Next.js for web, Flutter, React Native, Kotlin for mobile, and Python, Node.js, .NET Core for backend development.

Our AI/ML expertise spans TensorFlow, PyTorch, YOLOv8, OpenCV for computer vision, LangChain, LlamaIndex for RAG systems, and Scikit-learn, Keras for machine learning. We specialize in automobile detection systems, facial recognition, predictive analytics, and NLP-based intelligent agents.

From smart‑city platforms to enterprise dashboards, we design every solution to be secure, observable and cloud‑native using AWS, Azure, Google Cloud, Docker, Kubernetes – so you can iterate confidently long after launch.

  • AI/ML Projects: RAG systems, vehicle detection (YOLO), facial recognition, predictive models
  • Modern Tech Stack: MERN, MEAN, Django, FastAPI, GraphQL, PostgreSQL, MongoDB
  • Cloud & DevOps: CI/CD pipelines, Terraform, Jenkins, GitHub Actions, serverless architectures

35+

Production launches

Web, mobile and AI deployments running in production for clients worldwide using modern frameworks.

25+

AI/ML projects

Computer‑vision, NLP, RAG systems, and forecasting models actively serving business decisions.

99.9%

Target uptime

Architected with redundancy, monitoring and alerting by default using modern cloud practices.

50+

Tech Stack Tools

Expertise across modern frameworks, AI/ML libraries, cloud platforms and DevOps tools.

Our Expertise

Architecting digital products that last

PhotonStar combines product thinking, strong engineering and modern cloud practices to ship software that users trust and teams can evolve.

What PhotonStar builds
Web apps & dashboards Android & iOS products AI & ML Solutions Vehicle Detection Systems RAG & Chatbot Systems Blockchain & Web3 dApps Cloud CI/CD & DevOps CRM & internal tools

Web Platforms

Responsive portals, admin panels and SaaS web apps with secure APIs, robust auth using React, Angular, Vue.js, Next.js, Django, FastAPI.

Mobile Ecosystems

High‑performance Android and iOS apps built with Flutter, React Native, Kotlin, Swift supporting offline‑first flows and real‑time sync.

AI & Computer Vision

Vehicle detection, facial recognition and prediction pipelines using YOLO, OpenCV, TensorFlow, PyTorch and modern MLOps practices.

RAG & NLP Systems

Intelligent chatbots, document Q&A systems and knowledge bases using LangChain, LlamaIndex, GPT-4, BERT for context-aware AI applications.

Blockchain & Web3

Smart contracts, token flows and private chains using Solidity, Ethereum, Polygon, Hyperledger with audit trails and system integration.

Cloud & DevOps

AWS, Azure, GCP architectures with Kubernetes, Docker, Terraform, Jenkins, GitHub Actions enabling frequent, low‑risk releases.

Delivery Playbook

How projects move from idea to impact

A clear four‑step flow keeps complex initiatives predictable and gives stakeholders visibility at every milestone.

Concept to production in weeks. Each phase is built to uncover risks early, validate assumptions and ship usable software on a regular cadence.

Discovery & UX flows

We align on goals, map key user journeys and select the right stack across web, mobile, AI and cloud for your domain.

Build, integrate, iterate

Cross‑functional squads ship features in short sprints with weekly demos, feedback loops and transparent progress tracking.

Cloud deployment & MLOps

Infrastructure‑as‑code, CI/CD pipelines and model serving pipelines ensure reliable deployments and safe rollbacks.

Observability & evolution

Dashboards, logging and alerting plus a 3–12 month roadmap keep your product improving after launch, not just running.

What a typical engagement looks like
  • MVP window: usually 8–12 weeks from signed brief to first users.
  • Team: product lead, tech lead, 2–4 engineers and a designer.
  • Security: single‑sign‑on, audit logs and granular permissions by design.
  • Post‑launch: feature sprints, A/B tests and reliability improvements based on real usage.
React.js Angular Vue.js Next.js Python Node.js TensorFlow PyTorch YOLOv8 OpenCV LangChain LlamaIndex Flutter React Native AWS Azure GCP Docker Kubernetes MongoDB PostgreSQL FastAPI Solidity GraphQL React.js Angular Vue.js Next.js Python Node.js TensorFlow PyTorch YOLOv8 OpenCV LangChain LlamaIndex Flutter React Native AWS Azure GCP Docker Kubernetes MongoDB PostgreSQL FastAPI Solidity GraphQL
Selected Work

Case studies from the field

A snapshot of how PhotonStar technology performs in real‑world environments with demanding constraints.

photon_vision_sys.exe
> Initializing YOLO v8 model... OK
> Loading weights... OK
> Stream connected: CAM_04
> Object detected: [Sedan] (98.2%)
REC ●
Smart Cities

AI-Powered Traffic Intelligence Platform

A city‑wide computer‑vision system using YOLOv8 & OpenCV that ingests 500+ live camera feeds to detect vehicles, flag violations and optimize signal timing.

Built on a hybrid cloud‑edge architecture using AWS IoT, Docker, Kubernetes, the platform helps operators respond faster to congestion and incidents while providing real-time analytics that guide long‑term infrastructure planning.

Computer vision (YOLOv8) Real‑time analytics Cloud + Edge Computing
Plan a similar rollout
RAG-based Knowledge System

Intelligent document Q&A chatbot using LangChain, GPT-4, Pinecone for context-aware responses with citation sources and real-time updates.

AI/NLP • RAG System
Healthcare Triage Assistant

Decision‑support tool combining clinical rules with ML recommendations using TensorFlow, BERT and audit‑ready traceability.

Responsible AI • ML
Real-time Fraud Detection

Streaming risk engine processing thousands of transactions using Python, Kafka, Redis with explainable ML signals for compliance teams.

FinTech • Real-time ML

Upcoming Projects & Articles

Explore our latest R&D initiatives and technical insights.

Vehicle Detection
Vehicle Detection

Traffic Management System with the use of machine learning to manage the traffic and vehicle detection program to identify correct vehicle and manage the traffic signals and routes

Machine Learning
Smart City Traffic Analytics
Smart City Traffic Analytics

A real-time analytics dashboard designed to monitor city-wide traffic congestion, public transport movement, and emergency response routes using live sensor data and interactive maps.

IoT • Smart City
AI-Powered Health Monitoring
AI-Powered Health Monitoring

An intelligent healthcare assistant that analyzes wearable device data to detect early health anomalies and provide preliminary diagnostic insights for medical professionals.

HealthTech • AI
Blockchain-Based Document Verification
Blockchain-Based Document Verification

A research-driven project exploring decentralized identity and document verification using blockchain to prevent fraud and ensure secure data authenticity.

Blockchain • R&D
AI Chatbot for Customer Support
AI Chatbot for Customer Support

Developing a scalable AI chatbot capable of handling multilingual customer queries, automating ticket resolution, and improving customer response times.

AI • SaaS
Logistics Fleet Tracking Platform
Logistics Fleet Tracking Platform

A centralized fleet management system providing real-time GPS tracking, predictive maintenance alerts, and route optimization for logistics companies.

Logistics • IoT

Join the PhotonStar Team

We are always looking for passionate developers, designers, and innovators. Ready to build the future? Apply now to become part of our journey.

Let's talk about your next release

Share a bit about your challenge and the impact you are aiming for. A PhotonStar product specialist will respond within one business day.

Prefer chat? Tap the WhatsApp button to start a conversation instantly.