Project Showcase
Real-world AI implementations delivered by our expert network.
27 projects found
AI-Powered First-Line Support Agent (RAG)
AI Engineer
The project involved developing an intelligent automation system to handle Tier-1 customer inquiries for a microsite building platform. By leveraging advanced Retrieval-Augmented Generation (RAG), the system analyzes a knowledge base of over 280 articles to provide instant and accurate responses. The solution was designed to solve scalability challenges by automating repetitive, low-complexity questions that previously overwhelmed the human support team.
AI Agents Management & Orchestration Control Plane
AI Engineer
Developed a centralized, production-grade management platform (Control Plane) for the lifecycle management of specialized AI agents. The system provides a unified web interface for defining agent personas, deploying them across diverse environments, and monitoring their performance and token consumption in real-time.
AI-Powered Multi-Modal City Guide
AI Lead Engineer
Architected and launched a mobile-first, multi-modal AI travel companion that generates dynamic, location-aware storytelling. The platform utilizes generative AI to create historical narratives for points of interest, translates content in real-time, and synthesizes high-quality audio guides for a hands-free user experience.
Multi-Agent Personal Assistant & Time Organizer
AI Engineer
The project involved building a sophisticated personal productivity automation system based on a Multi-Agent Architecture to streamline tasks and professional collaboration. The system integrates with Google Workspace, Jira, Zoom, and Confluence to provide unified task management, automated scheduling, and intelligent email triage. By using a Supervisor Agent to orchestrate specialized sub-agents, the platform autonomously handles complex workflows like research and meeting coordination while maintaining human-in-the-loop security.
AI-Powered Creative Automation System
Lead AI Engineer / Architect
Creative teams lose days on manual marketing asset production, with inconsistent brand use, multi-platform resizing, and weak product-identity control. The system automates the pipeline from brief to delivery: it uses Computer Vision for design analysis, automated prompt engineering, fine-tuned generative models, smart one-to-many resizing (Saliency Maps), and ControlNet for product fidelity, with automated brand and compliance checks—cutting production from days to minutes while keeping full brand consistency.
Interrogation Transcription System for Law Enforcement
Voice AI Engineer
Automated real-time transcription of interviews to generate official protocols in a secure environment. On-premise (air-gapped) deployment ensuring maximum security and data privacy. Core Model: Python, OpenAI Whisper, Pyannote, Docker, on-premise deployment Orchestration: Custom system for real-time processing (voice detection + chunking + transcription). Supports up to 10 simultaneous sessions. Fine-tuning Pipeline: Created a pipeline for periodic model updates using client-provided datasets (edited transcripts). Focused on adapting to (local dialect) and low-quality audio. Metrics: Used WER (Word Error Rate) and CER (Character Error Rate) to validate model performance. Deployment: On-premise (Air-gapped). All components are deployed locally to ensure maximum security and data privacy.
Financial Voice Agent for Call Center
Voice AI Engineer
Voice agent integration for a financial services company with a focus on mobile stability. Focus: Integrated AI agents with telephony infrastructure. Solved architectural challenges regarding vendor integrations. Performance: Focused on maintaining high communication quality over mobile networks.
RAG for Medical equipment marketplace
AI Engineer
Knowledge base system for medical device documentation with semantic search capabilities. Pipeline: Web scraping of manufacturer manuals for specified medical devices → chunking → indexing with metadata → storage in vector database. Core Functionality: On query, retrieves relevant documentation and specifications for a given medical device.
Deepfake Voice Detection System
AI Solutions Architect
Telecom providers and financial institutions needed a solution to detect synthetic speech and protect against voice fraud in call centers. We built a real-time deepfake detection system for streaming audio using speaker recognition, diarization, ASR, Deep Fake detector model.
Fruit Counting System for Agricultural Robotics
Computer Vision Engineer
Farmers and agri-tech companies required automated fruit yield estimation to plan harvest and optimize logistics. Designed a robotic vision system to count oranges on trees using 3D cameras, depth sensors, and GPS.
AI Audio Summarization & Call Analysis
AI Voice Engineer
Call center teams and financial services wanted faster review of long customer calls for compliance and support optimization. Built an AI-powered system for speech-to-text transcription, speaker separation, and intelligent summarization of conversations.
Generative AI Video Platform (Lipsync & Video Generation)
Senior Deep Learning Research Engineer
Development of a large-scale generative AI video platform serving high-volume content creation, architecting image-to-video and video-to-video systems from scratch.
Image Generation Service based
Computer Vision Researcher
Built a scalable production image generation service based on Stable Diffusion capable of handling user-level traffic.
AI-Based Fitness Technique Correction App
Computer Vision Engineer
Developed a real-time fitness application that analyzes exercise technique using a camera. Users select an exercise, position the camera, and receive feedback on movement correctness.
Real-Time Football Match Perception System
Computer Vision Engineer
Led the end-to-end development of a real-time computer vision system for football match analytics, combining OCR, object detection, tracking, classification, and classical CV techniques into a unified production pipeline.
Smart Parking Detection System
Computer Vision Engineer
Designed a system that detects available parking spaces from live camera feeds.
AI-Driven Campaign Optimization Platform
Lead Data Scientist / ML Engineer
A telecom company had large volumes of messaging and campaign data but no practical way to use it for targeting or personalization. The goal was to build production ML systems that could directly improve campaign performance.
Live Streaming Reinforcement Learning Recommendation System
Lead AI Engineer / Architect
A consumer-facing live streaming platform needed to improve real-time content recommendations under strict latency constraints. Traditional offline-trained models were slow to adapt to user behavior and changing content dynamics. The goal was to design a system that could learn continuously from live user interactions.
Quantitative Research Infrastructure Optimization
Data / Platform Architect
A crypto investment fund needed to run large-scale backtests over long historical time ranges. An initial cloud-first design using managed services proved too expensive once realistic workloads were tested.
URLs Scraping Pipeline
Data Engineer / Backend Engineer
Built an end-to-end URL scraping high-throughput platform to continuously discover, schedule, and scrape web pages at scale. The pipeline coordinates scraping demand, executes distributed scraping jobs, and emits structured outputs for downstream processing and monitoring.
Kubernetes Autoscaling & Capacity Optimization
Cloud / Platform Engineer (AWS EKS / Karpenter)
Built and maintained AWS EKS node provisioning with Karpenter by defining scalable, workload-aware node pools to automatically right-size capacity and improve cluster elasticity for data/compute services.
Databricks Lakehouse Ingestion & Medallion Architecture
Data Engineer
Built and operated a Databricks Lakehouse ingestion and transformation framework on Delta Lake, implementing a Medallion Architecture (Bronze/Silver/Gold) to move data from raw landing through curated layers into analytics-ready datasets for reporting and KPI consumption.
High-Load Enterprise Ingestion & Inference Platform
AI Lead Engineer
Led the architecture and development of a scalable, multi-tenant RAG (Retrieval-Augmented Generation) platform designed to ingest and index massive volumes of heterogeneous enterprise data. The system enables automated monitoring of client-defined storage, transforming unstructured data into a queryable knowledge base powered by a variety of Large Language Models.
No-Code Knowledge Ingestion & Semantic Search
AI Engineer
Engineered a lightweight, no-code RAG solution to bridge the gap between static cloud storage and interactive AI. The system monitors Google Drive directories, automatically ingesting newly uploaded documents of various formats into a vector database to enable natural language querying.
AI-Powered Natural Language Interface for DevOps Monitoring
AI Engineer
Telecom providers and financial institutions needed a solution to detect synthetic speech and protect against voice fraud in call centers. We built a real-time deepfake detection system for streaming audio using speaker recognition, diarization, ASR, Deep Fake detector model. Management needs monitoring data for decisions but has no SQL skills, so they depend on DevOps for every request and wait 1–2 hours while engineers spend 20–30% of their time on routine data pulls. An AI assistant in Slack lets users ask questions in plain English, turns them into read-only database queries with full audit trails, and escalates when unsure—cutting DevOps time on data requests by 60–80% and giving near-instant, self-service access to system performance, costs, and errors.
AI-Powered Credit Card Competitive Intelligence System
AI Engineer
Financial institutions were manually monitoring 500+ pages across 15+ comparison sites every day, and traditional scrapers kept breaking whenever site layouts changed. The solution is a self-healing AI platform that uses semantic HTML analysis (81.82% accuracy), adaptive parsing (98% success rate), and automated analytics to collect and analyze competitive data, adapt to site changes in hours, and turn raw data into trend analysis and strategic recommendations.
OCR & Document translation pipeline
AI Engineer
Automated document processing system for extracting structured data from diverse file formats and translating into target languages. Input: PDF, images, DOCX, TXT and other file formats. Core Pipeline: File ingestion → OCR extraction (Qwen2.5-VL) → structured JSON output for rendering → translation to target language (Gemma 3).
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