Explore how we've helped startups and enterprises build scalable solutions that handle millions of users and transactions
DeFi Liquidity Protocol for Multi-Chain Trading
Built decentralized liquidity exchange with high throughput and multi-chain support
The Challenge
A fintech startup needed a decentralized liquidity exchange to compete with established DEXs. They required high transaction throughput, minimal gas costs, support for multiple blockchain networks, and real-time analytics—all while maintaining enterprise-grade reliability and security.
Our Solution
We architected and deployed a custom Automated Market Maker (AMM) protocol with gas-optimized Solidity smart contracts that reduced transaction costs by ~40% compared to standard implementations. Built cross-chain bridges using LayerZero protocol for seamless multi-chain liquidity pools. Developed a real-time analytics dashboard with The Graph for on-chain data indexing and WebSocket connections for live trade updates. Implemented comprehensive security auditing and emergency pause mechanisms.
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Start a Conversation→Multi-Sensor Fusion for Autonomous Trucking
Real-time perception system for highway autonomous trucks
The Challenge
An autonomous trucking startup needed a perception system for highway autopilot capable of detecting vehicles, lane markers, and road hazards at highway speeds (65+ mph) in real-time. Their previous vendor's solution had high false positive rates causing unnecessary braking events, and struggled with nighttime and adverse weather detection. The system needed to run on edge hardware in trucks without cloud dependency.
Our Solution
Built a custom sensor fusion pipeline combining camera, radar, and GPS data using PyTorch. Developed attention-based CNN architecture optimized for highway scenarios with temporal tracking for vehicle trajectory prediction. Implemented aggressive model quantization and TensorRT optimization to run on embedded NVIDIA Jetson AGX units. Created synthetic training data pipeline using CARLA simulator for rare edge cases. Deployed robust sensor calibration system accounting for vibration and temperature variations in truck cabins.
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Start a Conversation→Custom Multi-Modal AI Assistant for Enterprise
Fine-tuned LLM with custom multimodal architecture for domain-specific tasks
The Challenge
A large enterprise needed an AI assistant to help employees process internal documents, analyze images from field operations, and transcribe voice notes—all while maintaining data privacy and compliance. Their existing solution using GPT-4 API was costing $35K/month, and the generic model struggled with company-specific terminology and processes, achieving only 68% accuracy on domain-specific queries.
Our Solution
We fine-tuned LLaMA 2 70B on 500K internal documents and communication logs, reducing hallucinations significantly. Built a multimodal architecture that processes text (documents, emails), images (diagrams, photos), and voice (meeting notes). Implemented RAG using Pinecone vector database for real-time retrieval of relevant company knowledge. Deployed on their private Kubernetes cluster with FastAPI backend and Redis caching. Added chat history, conversation branching, and export features. Integrated with their SSO and role-based access control.
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Start a Conversation→Patient Portal Transforms Dental Practice Operations
Patient portal with online booking and automated reminders
The Challenge
A multi-location dental practice in Michigan was experiencing approximately 28-32% patient no-show rates, leading to significant revenue loss and scheduling inefficiencies. Their reception staff was overwhelmed with phone bookings, spending 12-18 hours weekly just on appointment scheduling. Patients complained about long wait times on phone and inability to book after hours. The practice needed a modern solution to improve patient experience and operational efficiency.
Our Solution
We developed a comprehensive patient portal with responsive web and mobile interfaces. Implemented real-time appointment scheduling with calendar availability sync across all locations. Built automated reminder system using Twilio for SMS and SendGrid for emails, sent at 48-hour and 24-hour intervals. Created secure patient messaging for non-urgent inquiries. Integrated Stripe for online payment processing and insurance verification. Connected with their existing Practice Management System via HL7 FHIR API for seamless data synchronization. Added patient forms, medical history, and document upload features.
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Start a Conversation→E-Commerce Platform Drives $580K in Annual Online Sales
Custom e-commerce platform with real-time inventory sync
The Challenge
A boutique retail store in Michigan with 15 years of brick-and-mortar experience had zero online presence, missing out on the growing e-commerce market. They were processing phone orders manually via Excel spreadsheets, leading to frequent inventory mismatches and overselling. Their competitors with online stores were capturing market share, especially during evening hours and weekends when the physical store was closed.
Our Solution
We built a custom Next.js e-commerce platform with server-side rendering for SEO optimization. Implemented real-time inventory synchronization between the online store and their Square POS system using webhooks. Created a mobile-first responsive design with product filtering, search, and recommendations. Integrated Stripe for payment processing and Shippo for multi-carrier shipping. Built an admin dashboard with analytics, order management, and customer insights. Added email marketing integration with Mailchimp for abandoned cart recovery and promotional campaigns. Implemented product reviews and wishlist features.
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Start a Conversation→Real-Time Fraud Detection for Fintech Platform
ML-powered fraud detection system processing millions of transactions
The Challenge
A fast-growing fintech platform processing $2M+ daily transactions was losing ~$120K monthly to fraudulent activities. Their rule-based fraud detection had 40% false positive rate, blocking legitimate users and causing customer churn. They needed a real-time ML solution that could adapt to evolving fraud patterns while minimizing false positives.
Our Solution
Designed and deployed a real-time fraud detection system using gradient boosting models (XGBoost) with feature engineering pipeline processing 200+ signals including transaction patterns, device fingerprinting, and behavioral biometrics. Built streaming architecture with Kafka and Redis for sub-100ms inference. Implemented online learning pipeline to continuously update models based on fraud analyst feedback. Created explainability dashboard showing why transactions were flagged.
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Start a Conversation→AI-Powered Supply Chain Optimization
Predictive analytics for inventory and logistics optimization
The Challenge
A manufacturing company with 15 distribution centers was struggling with inventory management—experiencing both stockouts (losing sales) and overstock (tying up $3M in excess inventory). Their legacy system used fixed reorder points that couldn't adapt to seasonal demand, promotions, or supply chain disruptions. Manual inventory decisions by regional managers led to inconsistent results.
Our Solution
Built ML-based demand forecasting system using time series models (Prophet, LSTM) that predicts demand at SKU-warehouse level considering seasonality, promotions, weather, and economic indicators. Developed optimization engine using linear programming to calculate optimal reorder points and quantities. Created real-time dashboard showing inventory levels, predicted stockouts, and recommended actions. Integrated with their ERP system for automated purchase order generation.
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Start a Conversation→High-Performance NFT Marketplace on Polygon
Gas-optimized NFT marketplace with lazy minting
The Challenge
A digital art platform wanted to launch an NFT marketplace but Ethereum gas fees ($50-200 per mint) made it economically unfeasible for artists selling lower-priced artwork. They needed a solution that was affordable, fast, and still had good liquidity. Previous developer built a prototype that took 45 seconds to load listings and had no mobile optimization.
Our Solution
Architected NFT marketplace on Polygon with ERC-721A gas-optimized smart contracts reducing batch mint costs by 60%. Implemented lazy minting allowing artists to create NFTs without upfront gas costs—minting happens on first purchase. Built IPFS integration for decentralized metadata storage. Developed high-performance frontend with Next.js, implementing virtual scrolling for collections with 10K+ items. Added advanced search, filtering, and recommendation engine. Integrated MetaMask, WalletConnect, and credit card payments via Crossmint.
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Start a Conversation→AI-Powered Medical Imaging Analysis
Deep learning model for radiology image analysis
The Challenge
A radiology group in Michigan was facing a backlog of 2-3 days for CT and MRI scan analysis, with radiologists spending 15-20 minutes per scan. They needed an AI system to pre-screen scans, flag abnormalities, and prioritize urgent cases. The solution had to integrate with their existing PACS system and meet HIPAA compliance requirements.
Our Solution
Developed custom deep learning models using PyTorch for detecting abnormalities in CT and MRI scans. Built preprocessing pipeline to handle DICOM images and normalize across different scanner types. Implemented attention-based neural network architecture highlighting regions of interest for radiologists. Created secure API integration with their PACS system. Deployed on HIPAA-compliant AWS infrastructure with encrypted data storage. Built radiologist review interface showing AI confidence scores and highlighted regions.
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Start a Conversation→Multilingual AI Customer Service Chatbot
LLM-powered chatbot handling 10K+ monthly conversations
The Challenge
An e-commerce company with 50K monthly visitors was spending $25K/month on customer service agents handling repetitive questions about orders, shipping, returns, and product specifications. Their human agents were overwhelmed during peak hours (evenings and weekends), leading to 2-4 hour response times and frustrated customers.
Our Solution
Built custom LLM-powered chatbot using fine-tuned GPT-3.5 on their product catalog, FAQ database, and 2 years of customer service transcripts. Integrated with their Shopify store for real-time order status lookup. Implemented semantic search over product specifications and return policies. Added multilingual support (English, Spanish, French). Created escalation logic to route complex issues to human agents with full conversation context. Built analytics dashboard tracking resolution rates, customer satisfaction, and cost savings.
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Start a Conversation→Real-Time Social Media Intelligence Platform
Multi-source data aggregation and sentiment analysis
The Challenge
A PR agency managing 40+ clients needed to monitor brand mentions across Twitter, Reddit, news sites, and blogs in real-time. They were manually checking multiple platforms daily, missing time-sensitive crises, and struggling to quantify sentiment for client reports. They needed automated monitoring, sentiment analysis, and instant alerts for negative mentions.
Our Solution
Built real-time data aggregation pipeline using streaming APIs from Twitter, Reddit, and RSS feeds from 500+ news sources. Implemented NLP sentiment analysis using fine-tuned BERT models to classify mentions as positive, negative, or neutral. Created keyword and entity extraction to identify trending topics and influencers. Built automated alert system sending Slack/email notifications for negative sentiment spikes. Developed analytics dashboard with sentiment trends, competitor comparisons, and exportable reports. Implemented data warehouse for historical analysis.
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