Leadership — Building Production AI Systems Since 2016
60
%Results improved compared to previous agencies.
10+ Years of Building Software That Works BytezTech was founded in 2016 with a simple belief: technology should solve real business problems, not create new ones. What started as a three-person development team has grown into a dedicated AI solutions company delivering computer vision, intelligent automation, and AI agent systems across 6 countries. Today, we are an NVIDIA Inception member, DPIIT Startup India recognized, and an n8n Community Creator — building GPU-accelerated AI products for manufacturing, hospitality, retail, and financial services.
Our Vision
To become the most trusted AI solutions company for mid-market businesses — the team that manufacturers, restaurants, and enterprises call when they need computer vision, automation, or AI agents that actually work in production. We don't chase trends. We build AI systems that run on factory floors, in restaurant kitchens, and inside warehouse operations — 24/7, without breaking. That's the standard we hold ourselves to.
Our Mission
Help businesses see what they're missing, automate what they're repeating, and grow what they're building — using computer vision, AI agents, and workflow automation deployed on enterprise-grade infrastructure. We serve clients from seed-stage startups to established companies across the UK, Singapore, UAE, Canada, and India. Every engagement starts with a real business problem and ends with a deployed, working system.
Our Values
Build to Deploy, Not to Demo - Every system we build is designed for production. We test under real conditions, deploy on real hardware, and support after launch. Demos are easy. Production is where trust is earned. We tell clients what's feasible, what's risky, and what will take longer than they expect. We'd rather lose a project by being honest than win one by overpromising. Right Tool for the Right Problem - Not every problem needs AI. Sometimes a simple n8n automation solves what a client thought needed machine learning.
Chintan Poriya
AI & COMPUTER VISION LEADER - CEO
Chintan brings over 11 years of proven experience in technology leadership, AI product development, and digital transformation. As the founder of BytezTech, he has built the company from a three-person team into a dedicated AI solutions company delivering GPU-accelerated computer vision, intelligent automation, and AI agent systems to clients across 6 countries. Under his leadership, BytezTech earned NVIDIA Inception membership — positioning the company alongside 19,000+ AI startups worldwide with access to enterprise-grade GPU infrastructure, TensorRT optimization, and NVIDIA Jetson edge deployment capabilities. Chintan also holds DPIIT Startup India recognition and is an official n8n Community Creator with published automation workflow templates. BytezTech's AI products today include the AI Vision Engine for real-time object detection and surveillance, an Intelligent Document Processing pipeline for insurance and fintech, and an AI Agent Platform powering WhatsApp commerce bots and voice assistants. These systems are deployed in production across manufacturing, hospitality, retail, and financial services industries in the UK, Singapore, UAE, Canada, and India. Chintan's approach is grounded in building AI that works in real business environments — not demos that look impressive but fail in production. With 150+ projects delivered and 44 verified Google reviews, his focus remains on measurable outcomes: reducing manual effort, increasing operational visibility, and deploying AI that runs 24/7 without human intervention. Areas of Expertise:
- Computer Vision & NVIDIA Edge AI Deployment
- AI Chatbots, Voice AI & Conversational Agents
- n8n Workflow Automation & AI Integration
- AI-Powered Mobile & Web Applications
Education:
- B.E (Computer Engg.)
130
PROJECT COMPLETED
Haresh Poriya
Chief Technology Officer & Co-Founder
Haresh is the technical backbone of BytezTech, leading the company's AI engineering, system architecture, and product development. With over 11 years of experience across full-stack development, cloud infrastructure, and machine learning systems, he ensures that every solution BytezTech delivers is production-grade, scalable, and built to run 24/7. As CTO, Haresh leads BytezTech's Python AI/ML team in building computer vision pipelines using YOLO v8 and NVIDIA CUDA, deploying AI models on edge devices (NVIDIA Jetson), and architecting intelligent automation workflows with n8n. His hands-on approach means he's involved in the technical design of every major project — from model training and optimization to API architecture and deployment. His current focus areas include advancing BytezTech's AI Vision Engine for real-time surveillance and quality inspection, building the company's Restaurant AI Monitor product, and integrating TensorRT model optimization for faster inference at the edge. Haresh's research-driven mindset ensures BytezTech stays ahead of emerging technologies while maintaining the reliability and performance that clients depend on. Areas of Expertise:
- AI/ML Model Development & Deployment
- Cloud Infrastructure & DevOps
- Technical Team Leadership
Education:
- B.E (Computer Engg.)
130
PROJECT COMPLETED
Our Philosophy — Build AI That Survives Monday Morning
Most AI demos work perfectly on a laptop. Then Monday morning happens — real lighting conditions, real camera angles, real users who don't follow instructions, and a production environment that has nothing in common with the test setup. That gap between demo and production is where most AI projects fail. It's also where BytezTech lives. Our philosophy is simple: we don't ship until it works in your environment, on your data, under your conditions. Every computer vision model we deploy is tested against the client's actual camera feeds. Every chatbot is stress-tested with real customer conversations. Every automation workflow runs through failure scenarios before it goes live.
This approach comes from experience, not theory. After 150+ deployments across manufacturing floors, restaurant kitchens, and e-commerce operations, we've learned that the hardest part of AI isn't building the model — it's making it reliable enough that the client forgets it's running. Three principles guide every project we take on: Test with real data, not sample data. A YOLO model trained on public datasets is a starting point. A YOLO model retrained on your factory's products, under your lighting, at your camera angles — that's a solution. Deploy where the data lives. We deploy on NVIDIA Jetson edge devices inside the client's facility. No video footage leaves the premises. No cloud dependency. No latency. The AI runs where the cameras are.
Measure outcomes, not accuracy percentages. We don't report "94.7% mAP" to clients. We report "your kitchen compliance improved from 71% to 97%" or "your customer response time dropped from 4 hours to 8 seconds." If the business metric doesn't move, the AI didn't work. This is what 10 years of building production software taught us — and it's what separates a working AI system from a science project.
