Our Portfolio
Production-grade AI systems, Generative AI applications, distributed platforms, and enterprise integrations — shipped and running at scale.
AI-Powered Candidate Screening & Evaluation Platform
Designed and deployed a production-grade AI recruitment platform to automate high-volume candidate screening for enterprise hiring teams. The system uses transformer-based NLP pipelines for deep resume understanding, LLM-based contextual scoring and ranking, and a microservices backend built on FastAPI with horizontally scalable APIs. The platform integrates with existing ATS systems and surfaces structured insights to hiring managers, dramatically cutting time-to-shortlist.
Reduced manual screening effort by over 70% and significantly improved hiring accuracy at scale.
Enterprise Knowledge Copilot (RAG-based AI System)
Built a context-aware AI copilot that enables employees to query and interact with vast enterprise knowledge bases in natural language. The system uses a RAG architecture with vector embeddings and semantic search for precise retrieval, integrates natively with Confluence, ServiceNow, and internal documentation systems, and orchestrates responses via LangChain with FAISS and Pinecone for vector storage. Deployed on Kubernetes on AWS with robust access controls and audit logging.
Enabled real-time enterprise knowledge access for 1,000+ users, reducing support ticket volume and onboarding time.
Real-Time Voice-Based Conversational AI System
Developed a production-grade voice AI platform delivering natural, low-latency conversational experiences. The core pipeline connects Speech-to-Text, an LLM reasoning layer, and Text-to-Speech in a streaming fashion over WebRTC, minimising perceived latency. An event-driven backend using Kafka and AWS SQS handles session orchestration, context management, and failover. The architecture supports concurrent sessions at scale and is deployable across web, mobile, and embedded devices.
Delivered seamless real-time conversational experiences with sub-500ms end-to-end latency across concurrent sessions.
Large-Scale Image Comparison & Computer Vision Pipeline
Architected a distributed computer vision pipeline capable of processing millions of images for similarity comparison, deduplication, and visual search. The system employs CNN-based deep feature extraction and embedding generation, with GPU-optimised inference pipelines built on TensorFlow and PyTorch. Asynchronous job queues and auto-scaling workers on AWS handle burst workloads, while OpenCV powers pre-processing and post-processing stages. Results are indexed for fast approximate nearest-neighbour search.
Reduced image analysis time from hours to minutes at production volume, enabling real-time visual search capabilities.
Event-Driven Distributed Platform for Real-Time Systems
Designed and built a highly resilient, event-driven distributed platform to power real-time data processing for high-throughput business workloads. The platform uses a microservices architecture with Spring Boot and Node.js services communicating over Kafka topics and AWS SQS/SNS. Complex multi-step business workflows are orchestrated reliably using Temporal, with automatic retries, timeouts, and visibility into workflow state. The entire stack runs on Kubernetes with horizontal auto-scaling and blue-green deployment support.
Achieved reliable, low-latency processing of millions of real-time events per day with 99.9% uptime.
Intelligent Business Process Automation Platform
Designed and deployed a business process automation platform that replaced hundreds of hours of manual cross-department work each month. Using n8n as the core orchestration engine, the platform connects CRM, HRMS, finance, and communication tools through intelligent workflows triggered by business events. AI classification and extraction layers built on LLMs pre-process incoming data — emails, forms, documents — before routing them through the correct automation path. Custom webhook integrations, retry logic, and audit trails ensure reliability and compliance. The platform was deployed on a self-hosted Kubernetes cluster for full data sovereignty.
Eliminated over 300 hours of manual work per month across 4 departments, with zero data loss and full audit compliance.
Enterprise AI Integration & Digital Transformation Layer
Designed and delivered a transformation layer that brings modern AI capabilities into complex, legacy enterprise environments without disrupting existing systems. The solution integrates AI-powered automation into SAP S/4HANA and NetWeaver landscapes via secure OData and REST APIs, using SAP UI5/Fiori for the frontend experience. Deployed on OpenShift with AWS and Azure support, the platform enforces enterprise-grade security, SSO, and audit compliance throughout.
Accelerated AI adoption across enterprise teams without disrupting existing SAP workflows or compliance posture.