We implement GPT-4, Claude, and other leading models with custom API endpoints. For a legal tech client, we built a contract analysis tool that processes 25,000+ documents/month with 98% accuracy, reducing review time from 40 hours to 2.5 hours per contract using optimized API calls.
Our team handles full fine-tuning of OpenAI models using client-specific datasets. A healthcare client achieved 94% accuracy in medical imaging analysis after we trained a vision model on 85,000+ labeled radiology images, implementing transfer learning techniques to reduce training time by 60%.
We create AI systems that combine multiple models for complex workflows. For a logistics client, we built a system combining GPT-4 for route planning and Whisper for voice-to-text warehouse instructions, integrating with their WMS through 14 custom API endpoints.
All implementations include GDPR, HIPAA, and SOC2 compliance. We developed an encrypted data pipeline for a financial services client that handles $3B in transactions/year, using tokenization to reduce PII exposure by 89% while maintaining OpenAI API functionality.
Our cost management systems reduce API expenses by 30-70% through token budgeting and request prioritization. For an e-commerce client, we implemented a tiered processing system that shifted 40% of non-urgent tasks to off-peak hours, saving $12,500/month in API costs.
We build low-latency systems handling 10,000+ concurrent requests. For a live captioning service, we developed a WebRTC-based solution using Node.js that maintains sub-300ms latency across 12 OpenAI API endpoints, even with 80% CPU utilization.
Our systems include automated retraining pipelines. For a customer support chatbot, we implemented a feedback loop that collects 8,000+ user interactions/day, triggering model retraining every 72 hours to maintain 91%+ response relevance.
We connect OpenAI APIs to legacy infrastructure. For a manufacturing client, we bridged a 1992-era MES system with GPT-4 for predictive maintenance, handling 500+ API calls/minute through custom Java middleware while maintaining 99.99% uptime.
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Our retention rate went from 55% to 77%. Teacher retention has been 100% for three years. I don't know if we'd exist the way we do now without FreedomDev.
Integrated with our [Real-Time Fleet Management Platform](/case-studies/great-lakes-fleet) case study, we implemented a system using GPT-4 to analyze 15,000+ sensor data points/hour. The AI reduced unplanned downtime by 34% through early detection of engine failures, processing data from 480+ vehicles in real-time.
For a QuickBooks integration project ([QuickBooks Bi-Directional Sync](/case-studies/lakeshore-quickbooks)), we developed an AI that auto-categorizes 2,500+ transactions/day with 97% accuracy. The system reduces manual bookkeeping by 70% using OpenAI's text classification models.
Built an AI triage system for urgent care clinics that processes 5,000+ patient interactions/day. The model achieved 92% accuracy in identifying critical symptoms through fine-tuned GPT-4 models trained on 800,000+ medical records, with HIPAA-compliant data handling.
Created an AI assistant for law firms that extracts key clauses from 1,200+ contracts/month. The system reduced contract review time by 65% while improving clause identification accuracy from 72% to 98% through custom model training.
Developed an AI that generates product descriptions and generates images for 800+ SKUs/month. The system increased conversion rates by 22% using DALL·E for image generation and GPT-4 for SEO-optimized text.
Built multilingual chatbots for global retailers handling 500,000+ interactions/month. The AI reduced support costs by 40% while maintaining 85%+ customer satisfaction scores through continuous learning from agent interactions.
Implemented a computer vision solution for automotive parts inspection using OpenAI's vision models. The system detected 97.3% of defects at 850 parts/minute, reducing manual inspection costs by $225K/year.
Created AI tutors for K-12 schools that generate personalized learning plans for 15,000+ students. The system uses GPT-4 to create adaptive quizzes and explanations, improving test scores by 18% in pilot programs.