AI Development Plans

Our rapid prototyping cycle begins with requirement gathering through our secure portal. Within 72 hours, we deliver a working MVP using our proven tech stack. This includes basic functionality, API integrations, and a demonstration of core AI capabilities. The prototype serves as a foundation for further iterations.

We use state-of-the-art techniques like LoRA and QLoRA for efficient model adaptation. Our process includes data preparation, training pipeline setup, and comprehensive evaluation. We can fine-tune models on your domain-specific data while maintaining high performance and reasonable computing costs.

Our RAG (Retrieval-Augmented Generation) systems include document processing, embedding generation, vector store setup, and custom retrieval logic. We use tools like Azure AI Search and OpenAI embeddings to create efficient knowledge bases that can handle enterprise-scale data.

Yes, we offer comprehensive support including performance monitoring, model retraining, system updates, and technical troubleshooting. Our team is available to handle any issues and ensure your AI systems remain production-ready.

We implement robust safety measures including input validation, output filtering, and usage monitoring. Our systems are designed with ethical considerations in mind, including bias detection and mitigation strategies. We also provide documentation on responsible AI usage.

Yes, we specialize in enterprise integrations. Our solutions can connect with your existing databases, APIs, authentication systems, and cloud infrastructure. We ensure secure data handling and compliance with your organization's security requirements.

After the initial 72-hour prototype, we typically spend 2-4 weeks refining and scaling the solution based on feedback. Full production deployments, including testing and optimization, usually take 4-8 weeks depending on complexity and requirements.