Real Projects. Real Impact.
A closer look at the products we've architected, built, and shipped — and the problems they solved.
DevMinds Learning
AI Adaptive Learning Platform
The Challenge
Special-needs children require personalized learning paths that adapt in real time — something off-the-shelf LMS platforms can't deliver. The client needed a system that could assess ability, adjust difficulty, and serve content from multiple AI providers without latency bottlenecks.
Our Solution
We architected a multi-AI system integrating Claude, Gemini, and OpenAI behind a unified orchestration layer. An adaptive difficulty engine adjusts across 4 proficiency levels in real time based on learner performance. BullMQ-powered job queues handle 1,000+ module processing tasks daily with fault tolerance.
Key Results
- Multi-AI architecture with seamless provider failover
- Adaptive difficulty engine across 4 proficiency levels
- 1,000+ modules processed daily via BullMQ pipelines
- Personalized learning paths for special-needs children
Feel Your Best
Full-Stack Wellness Platform
The Challenge
A wellness company needed a unified platform spanning a patient-facing app, provider dashboard, admin portal, and marketing site — all sharing a single codebase. The existing setup was fragmented, slow, and had no role-based access control.
Our Solution
We built a 78,000+ LOC monorepo serving all 4 applications with shared business logic. A 4-tier RBAC system handles patients, providers, admins, and super-admins. Real-time booking, Razorpay payment integration, and push notifications were built from scratch.
Key Results
- 78,000+ LOC monorepo serving 4 applications
- 4-tier RBAC with granular permission control
- Razorpay payments with 99.9% transaction success rate
- 40% faster API response times after optimization
Copper
AI-Powered Online Proctoring
The Challenge
Online exams were being compromised at scale. The client needed a proctoring solution that could detect cheating in real time across 1,000+ concurrent sessions — without requiring manual human reviewers for every flag.
Our Solution
We built a real-time proctoring engine combining facial recognition with behavioral analytics. The system monitors 50+ data points per session — gaze tracking, tab switches, audio anomalies, and multi-angle video feeds — and flags suspicious behavior automatically.
Key Results
- Real-time facial recognition + behavioral analytics
- Automated flagging across 50+ data points per session
- 1,000+ concurrent users with multi-angle video feeds
- 80% reduction in manual review time
Veda
AI Recruitment Agent
The Challenge
A growing company was spending 60+ hours per week on manual resume screening, interview scheduling, and candidate communication. They needed an AI system that could handle the top of the hiring funnel autonomously.
Our Solution
We designed a multi-agent architecture with 12+ specialized LLM sub-agents — each handling a discrete hiring task: resume parsing, skill extraction, fit scoring, interview scheduling, and candidate communication. The system integrates directly with Calendar, Slack, and email.
Key Results
- 12+ specialized LLM sub-agents working in concert
- Automated screening with intelligent fit scores
- Calendar + Slack + email integration
- 80% reduction in manual hiring workload
Insta Insights
Instagram Reels Analysis
The Challenge
Content creators and brands had no way to deeply analyze what makes a Reel perform well. Surface-level metrics like views and likes don't explain why content resonates — or how to replicate success.
Our Solution
We built an analysis engine combining GPT-4 with custom ML models to break down Reels across engagement patterns, hook effectiveness, pacing, and audience retention signals. The system processes 25+ reels per session and generates new scripts in the creator's own tone and style.
Key Results
- GPT-4 + custom ML for multi-dimensional content analysis
- 25+ reels analyzed per session at 95%+ accuracy
- Script generation matching the creator's voice and tone
- Deep engagement insights beyond surface-level metrics
Smart LMS
Enterprise Learning System
The Challenge
An existing LMS built for 4,000 students was buckling under growth. Page loads exceeded 8 seconds, the real-time collaboration features were broken, and the platform couldn't handle concurrent usage beyond a few hundred sessions.
Our Solution
We re-architected the entire platform for horizontal scalability — introducing Redis-backed caching, database query optimization, and a CDN strategy. Real-time collaboration was rebuilt on WebSockets, and push notifications were unified across web, iOS, and Android.
Key Results
- Scaled from 4,000 to 50,000+ concurrent students
- Rich text editor with real-time collaboration
- Unified push notifications across all platforms
- 12x scale increase with zero downtime
AI Counsellor
AI-Powered Counselling System
The Challenge
Counselling services were entirely dependent on human availability, creating long wait times and high operational costs. The organisation needed a way to handle routine counselling sessions at scale without sacrificing the quality of interaction.
Our Solution
We built an AI counselling system powered by GPT-4 with real-time speech recognition via Azure Cognitive Services. A Retrieval-Augmented Generation (RAG) pipeline using Pinecone and OpenAI embeddings ensures contextually precise responses. WebSocket-based streaming delivers sub-second response times, and an admin dashboard provides session analytics and template management.
Key Results
- 70% reduction in human counsellor workload
- 77% cost reduction in counselling operations
- Sub-second response times via WebSocket streaming
- RAG pipeline with Pinecone for contextual precision
Blended Learning
AI Lecture Engine
The Challenge
An educational institution needed to deliver lectures at scale but was bottlenecked by instructor availability. Creating video content manually was slow, expensive, and couldn't keep pace with a growing student base of 10,000+.
Our Solution
We designed an end-to-end automated lecture generation pipeline. Whisper handles text-to-speech, OpenAI LLMs generate lecture content, RVC clones instructor voices, and SADTalker animates avatar presentations. Reveal.js automates slide generation with dynamic styling. The entire pipeline runs on AWS for scalable delivery.
Key Results
- 80% reduction in dependency on human instructors
- Scalable lecture delivery to 10,000+ students
- End-to-end pipeline: Whisper, LLM, RVC, SADTalker
- Automated presentations with dynamic styling via Reveal.js
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