# AI Platforms/Deployment A technical topic covering platforms and practices for deploying AI systems. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Deploying AI You Control Doesn't Need to be So Hard DevFeed: [Deploying AI You Control Doesn't Need to be So Hard]() Original publisher: [Read original article]() Author: Jeetu Patel Published: 2026-09-10T09:00:50Z Content type: news Language: en Sources: [Cisco Blogs]() Topics: [Artificial Intelligence](), [AI Platforms/Deployment](), [AI Factory](), [Nvidia](), [Critical Infrastructure](), [post-training](), [data](), [Nemotron](), [on-prem](), [Fine-tuning](), [Cloud](), [Benchmark]() Tags: [ai](), [ai-factory](), [ai-infrastructure](), [ai-strategy](), [cisco-cloud-control-framework](), [cisco-secure-ai-factory](), [cloud](), [critical-infrastructure](), [data](), [executive-platform](), [fine-tuning](), [infrastructure](), [model](), [models](), [nemotron](), [nvidia](), [on-prem](), [post-training]() ### AI overview Cisco announces a collaboration with Palantir to deliver Palantir's Ontology for Cybersecurity through Cisco's Secure AI Factory, using NVIDIA as a preferred full-stack foundation for Palantir's Sovereign AI OS. The article argues that enterprise AI decisions should balance intelligence, cost, and control, including custom evaluations, post-training with proprietary data, and deployment in the cloud, at the edge, or on-premises. ### Source excerpt Announcing a collaboration with Palantir to deliver Cisco's Secure AI Factory with NVIDIA as a preferred full-stack foundation for Palantir's Sovereign AI OS. ## How to secure edge AI in customer-owned environments DevFeed: [How to secure edge AI in customer-owned environments]() Original publisher: [Read original article]() Author: Shayak Lahiri Published: 2026-09-04T19:10:10Z Content type: article Language: en Sources: [Microsoft Security Blog]() Topics: [AI Platforms/Deployment](), [Machine Learning, Security Attacks](), [Inference](), [Application Security](), [cloud-infrastructure]() Tags: [ai](), [attacks](), [cloud](), [customer](), [deployment](), [edge](), [frontier-ai-models](), [hardware](), [how-to](), [inference](), [models](), [security]() ### AI overview The article explains how moving AI inference and assets into customer-owned edge environments changes the security trust model. It recommends attestation, provenance, action mediation, and releasing sensitive assets only to trusted environments. ### Source excerpt As AI moves into customer-owned environments, organizations need new ways to verify the systems, software, and AI assets they trust before releasing sensitive data, credentials, and models. The post How to secure edge AI in customer-owned environments appeared first on Microsoft Security Blog. ## Enterprise AI Agents: Common Roadblocks and How to Overcome Them DevFeed: [Enterprise AI Agents: Common Roadblocks and How to Overcome Them]() Original publisher: [Read original article]() Author: JEFF MILLS, CHIEF CUSTOMER OFFICER, AI SERVICES @ TOPTAL Published: 2026-09-01T07:00:00Z Content type: article Language: en Sources: [Toptal Blog]() Topics: [AI Agent](), [Artificial Intelligence](), [AI Platforms/Deployment]() Tags: [agentic](), [agents](), [ai](), [ai-agent](), [ai-agents](), [enterprise](), [operations](), [productivity](), [workflows]() ### AI overview This article examines why enterprises struggle to scale AI agents into daily operations and outlines the organizational readiness and workflow integration challenges behind that gap. ### Source excerpt AI agents promise autonomy at scale, but many organizations fail to deploy them in day-to-day operations. Drawing on decades of experience in business strategy and technology, two Toptal leaders explore what it takes to bring AI agents into real workflows. ## Machine vs. machine: The new reality of cybersecurity in ANZ DevFeed: [Machine vs. machine: The new reality of cybersecurity in ANZ]() Original publisher: [Read original article]() Author: Jeremy Pell Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [Cybersecurity](), [Frontier AI](), [Threat Research](), [threat detection](), [data-architecture](), [AI Platforms/Deployment](), [Security & Privacy]() Tags: [agentic-ai-cybersecurity-security-research](), [australia](), [compliance](), [cybersecurity](), [data-architecture](), [endpoint-security-siem-security](), [frontier-ai](), [policy](), [research](), [threat-detection]() ### AI overview Frontier AI is accelerating cyberattacks across Australia and New Zealand to machine speed, while defensive capabilities, policy, data visibility, and operational security are struggling to keep pace. Survey findings from more than 850 IT and cybersecurity professionals highlight gaps between regulatory intent and real-world protection, as well as the need for searchable, unified data architectures to support reliable AI-enabled defence. ### Source excerpt Frontier AI has accelerated cyber threats to machine speed, leaving many ANZ organisations vulnerable. Our latest research reveals how fragmented data and visibility gaps hinder defence and why a unified platform is essential to battle threats. ## Responsible AI adoption needs developer workflow design DevFeed: [Responsible AI adoption needs developer workflow design]() Original publisher: [Read original article]() Author: Dr. Gleb Tsipursky Published: 2026-08-24T14:00:00Z Content type: article Language: en Sources: [Stack Overflow Blog]() Topics: [responsible-ai](), [shadow AI](), [AI Strategy](), [AI Platforms/Deployment](), [Tooling](), [Stack Overflow](), [Microsoft]() Tags: [ai](), [ai-adoption](), [article](), [cc-by-sa](), [compliance](), [developer](), [devex](), [experimentation](), [microsoft](), [platforms](), [responsible-ai](), [se-stackoverflow](), [se-tech](), [shadow-ai](), [tools](), [workflow]() ### AI overview The article argues that responsible AI adoption depends on designing developer workflows, not merely publishing policies. It presents shadow AI as a signal that approved tools or processes are too slow, vague, or disconnected from engineering work, and recommends investigating workflow friction while providing monitored gateways and approved AI platforms that support visibility and experimentation. ### Source excerpt Organizations cannot solve shadow AI with a document employees read once. They need to make responsible use easier than improvised use. ## Five key recommendations for platform teams in 2026 DevFeed: [Five key recommendations for platform teams in 2026]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [AI Platforms/Deployment]() Tags: [2026](), [ai](), [complexity](), [engineering](), [leadership](), [organizational](), [platform-engineering](), [platforms]() ### AI overview The article presents five recommendations for platform teams in 2026, based on reported execution gaps in measuring success, developer adoption, proving return on investment, integrating AI, and managing multiple platforms. It emphasizes disciplined execution and treating platform engineering as a product with dedicated leadership. ### Source excerpt Five actionable recommendations for platform teams in 2026 to maximize ROI, drive adoption, integrate AI, and build effective, scalable platform strategies ## How to make the case for giving your AI Agent system access DevFeed: [How to make the case for giving your AI Agent system access]() Original publisher: [Read original article]() Author: Dawn Perrott Published: 2026-06-11T12:04:14Z Content type: tutorial Language: en Sources: [The Intercom Blog]() Topics: [AI Agent](), [Back end](), [knowledge-management](), [AI Platforms/Deployment]() Tags: [2026](), [agent](), [ai-agent](), [ai-agent-blueprint](), [ai-automation](), [backend](), [customer-service](), [deployment](), [how-to](), [integration](), [knowledge-management](), [management-tools]() ### AI overview The article explains why AI Agents need access to backend systems to move from answering customer questions to completing actions. It argues that connecting support agents to CRM, billing, and order-management systems can enable end-to-end resolution, and describes how Intercom's Procedures with system access handled complex workflows better than fixed, scripted Tasks in some cases. ### Source excerpt Without access to your backend systems, your AI Agent can answer questions, but it can't take action. A customer asks to change their payment plan, they get a clear explanation, but a support rep still has... ## Why AI Labs Still Need Consultants for Enterprise Deployment DevFeed: [Why AI Labs Still Need Consultants for Enterprise Deployment]() Original publisher: [Read original article]() Author: Prasad Rao Published: 2026-06-04T18:30:11Z Content type: opinion Language: en Sources: [Big Tech Careers]() Topics: [Artificial Intelligence](), [AI Platforms/Deployment](), [anthropic](), [OpenAI](), [Deployment]() Tags: [ai](), [anthropic](), [deployment](), [openai](), [relationships](), [strategy]() ### AI overview This opinion article argues that AI has not made consulting obsolete because consultants provide enterprise access, relationships, and organizational knowledge that models cannot distill. It presents OpenAI and Anthropic's partnerships with consulting and financial firms as evidence that AI labs need consultants to help move enterprise AI beyond demonstrations into production. ### Source excerpt The role of consultants in the AI era ## OpenAI launches DeployCo to help businesses build around intelligence DevFeed: [OpenAI launches DeployCo to help businesses build around intelligence]() Original publisher: [Read original article]() Published: 2026-05-11T06:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [AI Platforms/Deployment](), [enterprise deployment](), [Frontier AI](), [Artificial Intelligence]() Tags: [acquisition](), [ai-adoption](), [applied-ai](), [company](), [deployment](), [enterprise-deployment](), [frontier-ai](), [industry](), [openai](), [partners]() ### AI overview OpenAI announces the OpenAI Deployment Company, a new organization intended to help businesses build and deploy reliable AI systems. It will embed Forward Deployed Engineers with organizations, redesign workflows and infrastructure, and support AI adoption. The company will launch following OpenAI's planned acquisition of Tomoro, bringing approximately 150 deployment specialists, and will begin with more than $4 billion in investment. ### Source excerpt OpenAI launches DeployCo, a new enterprise deployment company built to help organizations bring frontier AI into production and turn it into measurable business impact. ## How Replicate Handles Billing: A Complete Breakdown DevFeed: [How Replicate Handles Billing: A Complete Breakdown]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-04-09T00:00:00Z Content type: article Language: en Sources: [Dodo Payments Blog]() Topics: [AI Platforms/Deployment](), [AI Infrastructure](), [GPU](), [Multi-GPU](), [llama](), [stable-diffusion](), [Whisper]() Tags: [ai](), [ai-infrastructure](), [ai-platform](), [analysis](), [billing](), [compute](), [gpu](), [infrastructure](), [llama](), [models](), [multi-gpu](), [stable-diffusion](), [usage-based-billing](), [whisper]() ### AI overview The article analyzes Replicate's usage-based billing model, which charges for compute time by hardware type rather than by subscription, model, or token package. It explains hardware-tier pricing, multi-GPU committed-spend requirements, and model-agnostic billing, and discusses how to implement similar per-second billing for an AI platform. ### Source excerpt A detailed analysis of Replicate's pure usage-based billing model - per-second compute pricing across hardware tiers, cold start costs, and how to build the same pay-per-second infrastructure billing for your own AI platform. ## BBVA and OpenAI collaborate to transform global banking DevFeed: [BBVA and OpenAI collaborate to transform global banking]() Original publisher: [Read original article]() Published: 2025-12-12T00:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [OpenAI](), [AI Strategy](), [Generative AI](), [AI Platforms/Deployment](), [Security](), [software-development]() Tags: [ai](), [banking](), [chatgpt](), [deployment](), [enterprise](), [financial-services](), [generative-ai](), [global-affairs](), [openai](), [privacy]() ### AI overview BBVA and OpenAI are expanding a multi-year AI transformation program that will roll out ChatGPT Enterprise to all 120,000 BBVA employees across 25 countries. The collaboration will develop AI solutions for customer interactions, risk analysis, internal processes, employee productivity, and a more personalized banking experience, with security, privacy, training, and adoption controls for the regulated financial-services environment. ### Source excerpt BBVA is expanding its work with OpenAI through a multi-year AI transformation program, rolling out ChatGPT Enterprise to all 120,000 employees. Together, the companies will develop AI solutions that enhance customer interactions, streamline operations, and help build an AI-native banking experience. ## BNY builds "AI for everyone, everywhere" with OpenAI DevFeed: [BNY builds "AI for everyone, everywhere" with OpenAI]() Original publisher: [Read original article]() Published: 2025-12-12T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [AI Strategy](), [ai-governance](), [Generative AI](), [AI Platforms/Deployment]() Tags: [agents](), [ai](), [ai-adoption](), [ai-agents](), [ai-governance](), [efficiency](), [enterprise](), [generative-ai](), [openai](), [platform](), [responsible-ai]() ### AI overview BNY is expanding enterprise-wide generative AI adoption with OpenAI through Eliza, an internal AI deployment and education platform. More than 20,000 employees are building AI agents across over 125 live use cases, while governance and responsible AI practices support safe experimentation and scale. ### Source excerpt BNY uses OpenAI to expand AI adoption enterprise-wide through Eliza, where 20,000+ employees build AI agents that improve efficiency and client outcomes.