AI-Powered App Development
AI-Powered App & Software Development
Webyug Infonet LLP builds AI-powered web and mobile applications for businesses in the US, UK, Canada, EU, and Gulf countries. We integrate OpenAI (GPT-4o, Whisper, DALL-E), Gemini, Claude, and custom machine learning models directly into your products — delivering intelligent automation, smarter user experiences, and measurable business outcomes.
From AI chatbots and document processing pipelines to recommendation engines and predictive analytics dashboards, we architect AI solutions that are practical, scalable, and production-ready.
- OpenAI / GPT-4o Integration
- AI Chatbots & Virtual Assistants
- RAG & Knowledge Base Systems
- Document & Image Processing
- Recommendation Engines
- Predictive Analytics & ML Models
- Voice AI & Speech-to-Text
85+
Projects Delivered
15+
Countries Served
Since 2018
Established & Trusted
Free
Consultation
AI Chatbots & Intelligent Virtual Assistants
We build context-aware AI chatbots powered by GPT-4o, Claude, and Gemini that handle customer support, lead qualification, booking, and internal knowledge retrieval — reducing response times and support costs while improving satisfaction scores.
RAG Systems & Custom Knowledge Bases
Retrieval-Augmented Generation (RAG) lets your AI assistant answer questions using your own documents, PDFs, and databases — with accurate, cited responses. We build RAG pipelines using LangChain, vector databases (Pinecone, pgvector), and your preferred LLM.
Document & Image Processing Automation
Automate document-heavy workflows with AI. We build solutions that extract data from invoices, contracts, ID documents, and forms using OCR and LLM analysis — feeding structured data directly into your ERP, CRM, or custom backend.
Recommendation Engines & Personalisation
Increase engagement and revenue with AI-driven personalisation. We build recommendation engines for e-commerce (product suggestions), media (content feeds), and SaaS platforms — using collaborative filtering, content-based models, and hybrid approaches.
Predictive Analytics & Forecasting
Turn historical data into forward-looking intelligence. We develop demand forecasting, churn prediction, fraud detection, and customer lifetime value models using Python (scikit-learn, XGBoost, TensorFlow) and deploy them as APIs your apps can consume.
Voice AI & Speech-to-Text Applications
We integrate OpenAI Whisper, Google Speech-to-Text, and AWS Transcribe into web and mobile apps for voice commands, meeting transcription, real-time captions, and voice-driven search — making your product accessible and hands-free ready.
AI Integration into Existing Web & Mobile Apps
Already have a product? We add AI capabilities to your existing React, Laravel, Node.js, or Flutter application — whether that's an AI assistant, smart search, content generation, or automated classification — without disrupting what's already working.
Responsible AI — Secure, Explainable & Compliant
We build AI systems with data privacy and compliance at the core. All LLM integrations are architected to keep sensitive data within your infrastructure. We implement prompt injection protection, output filtering, and audit logging to meet GDPR and enterprise security requirements.
Our AI Development Process
We approach every AI project with a clear, outcome-first process — ensuring that the AI we build solves a real business problem and delivers measurable return on investment.
We begin with a discovery workshop to identify the highest-value AI use cases for your business, assess your data readiness, and define success metrics before any development begins.
We then build a proof-of-concept to validate the approach, iterate based on your feedback, and scale to production once accuracy and performance targets are met.
Every AI solution we deliver includes source code, documentation, model cards where applicable, and an ongoing support arrangement to handle model updates and API changes as AI providers evolve.
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Frequently Asked Questions
We integrate OpenAI (GPT-4o, Whisper, DALL-E), Google Gemini, Anthropic Claude, and open-source models. For custom ML, we use Python with scikit-learn, XGBoost, and TensorFlow. For RAG systems and knowledge bases, we use LangChain, Pinecone, and pgvector.
RAG (Retrieval-Augmented Generation) is an architecture that allows an AI assistant to answer questions using your own documents, databases, and proprietary knowledge — rather than only the LLM's training data. If you want an AI assistant that gives accurate, up-to-date answers specific to your business, a RAG system is the right approach.
We architect AI integrations so that sensitive customer data is never sent to third-party LLM APIs unless explicitly required. We use techniques such as data anonymisation, on-premise model deployment, and Azure OpenAI (which offers data residency and no training on your data) to meet GDPR and enterprise security requirements.
Yes. We specialise in augmenting existing React, Laravel, Node.js, and Flutter applications with AI capabilities — such as smart search, chatbots, content generation, classification, and document processing — without requiring a full rebuild.
Contact Us
- 704, Sun Gravitas, Opp. Ganesh Gruh Udhyod, Times of India Road, Near Shyamal Cross Road, Satellite-380015, Ahmedabad, Gujarat, India
- [email protected]
- (+91) 079 4921 4665