Kernshell delivers enterprise AI across six practice areas: Generative AI (custom LLMs, RAG systems, AI copilots on Azure OpenAI and AWS Bedrock), Conversational AI (chatbots, voice AI, virtual assistants), Core Machine Learning (predictive analytics, computer vision, classification), MLOps and AI Operations (automated pipelines, model monitoring, drift detection), AI Data and Governance (GDPR/HIPAA frameworks, explainable AI), […]

Kernshell builds and deploys AI on Microsoft Azure (Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning), Amazon Web Services (SageMaker, AWS Bedrock, Comprehend), and Google Cloud (Vertex AI, AutoML). LLMs used include GPT-4o, Anthropic Claude 3.5, Meta LLaMA 3, and Google Gemini 1.5 — selected based on client data residency, performance, and cost requirements.

Kernshell serves manufacturing (predictive maintenance, ETQ Reliance AI integration, computer vision quality inspection — clients Jabil, Hitachi Energy), healthcare (ScreenX Health AI patient screening, HIPAA-compliant AI, EHR integration), legal (LexOps AI contract review), financial services (fraud detection, risk modeling), retail (demand forecasting, recommendation engines), and logistics.

Kernshell uses a Proof-of-Concept methodology — validating the AI approach on real company data in 3–6 weeks before committing to full production development. Full production AI applications typically take 8–16 weeks covering use case definition, model selection, development, integration, testing, and deployment with monitoring infrastructure.

Yes. Kernshell has developed LexOps AI (Generative AI contract review platform built on Azure OpenAI) and ScreenX Health (HIPAA-compliant AI patient screening platform built on AWS Bedrock and Anthropic Claude). Both are available as enterprise software licenses with full implementation, customisation, and managed support services.