By Daniel LaBianca
About 50 hours of endless verifications and costly judgment calls later, these are the hard-earned lessons you need to know before handing your enterprise development project over to AI.
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Kevin Feasel explains how developers can move beyond flashy AI demos and add practical, production-ready capabilities such as classification, semantic search, RAG and function calling to existing .NET applications.
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By Pure AI Editors
The MCPA credential is designed to validate developers’ ability to build and deploy Model Context Protocol integrations as MCP adoption expands across enterprise AI systems.
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By Pure AI Editors
AI³ combines AI deployment, governance, cybersecurity and ongoing operations for financial services and health care organizations working with multiple model providers.
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By Pure AI Editors
New Active Intelligence features translate documents across more than 130 languages and generate summaries inside Venue while retaining permissions, approvals, and audit controls.
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By Pure AI Editors
Intelligent RCM uses AI workers to review claims, prepare appeals, and identify underpayments while keeping specialists responsible for final decisions and submissions.
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By Pure AI Editors
Lumi combines dealership inventory, manufacturer and government data with LLMs and web tools to answer vehicle questions and route prospective buyers into existing CRM workflows.
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By Pure AI Editors
New agents can execute multistep onboarding, compliance, and document-management processes while using existing permissions, approval gates, and audit trails.
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By Pure AI Editors
Compass combines private-company data, financial modelling, and transaction support to help financial advisors manage clients’ pre-IPO equity through a single AI interface.
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