Engineering & Advisory Capabilities
From concept to production, Afranet Ltd combines engineering discipline with practical AI implementation to build software that delivers measurable value.
AI Product Development
End-to-end design, training, fine-tuning, and deployment of specialized AI products tailored for business and human intent.
AI-Powered SaaS Platforms
Scalable multi-tenant SaaS applications featuring subscription management, secure usage quotas, and streaming LLM inferences.
Custom Web Application Development
Production-ready web applications built with modern frontend frameworks, strict TypeScript, responsive layouts, and WCAG AA accessibility.
Full-Stack Software Engineering
Complete system engineering spanning database schema design, RESTful/GraphQL APIs, backend services, and interactive user interfaces.
Large Language Model (LLM) Integration
Seamless integration of cutting-edge foundational models (GPT-4o, Claude 3.5, Gemini 1.5, Llama 3) via OpenRouter and direct provider APIs.
AI Workflow Automation
Automated business logic, intelligent document parsing, sentiment extraction, and autonomous multi-step execution workflows.
Business Process Automation
Streamlining manual administrative workflows, customer data sync, inventory tracking, and notifications.
API Design and Integration
Architecting secure, high-throughput REST and WebSocket APIs with strict validation, rate limiting, and OpenAPI/Swagger documentation.
Product Strategy and Technical Architecture
Transforming high-level business goals into rigorous technical blueprints, database schemas, and phased engineering roadmaps.
User Experience (UX) & Interface (UI) Design
Creating human-intentional UI systems with dark monochrome aesthetics, glassmorphism, responsive micro-animations, and accessible contrast.
Rapid MVP Development
Accelerated development lifecycle turning product concepts into production-grade functional MVPs within weeks.
AI Consulting and Technical Advisory
Strategic guidance for enterprises seeking to adopt AI, evaluate vendor platforms, safeguard privacy, and optimize LLM token costs.
