To recap: On-Premise: your data center, Confidential Computing infrastructure with GPUs required. On-Device: your hardware, fully offline, built for edge. VPC (AWS/GCP): all models and ElevenAgents, your cloud boundary, data stays in your environment. Cloud API: all models
ENTERPRISE AI
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On-Premise and On-Device AI Access Launches Mid-2026
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On-Premise and On-Device are in early access, with initial releases expected in the first half of 2026. VPC deployments are available now. Join the waitlist:
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VPC AI Model Deployments on AWS SageMaker and GCP
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For organizations that need their data to remain inside their own cloud environment, we offer VPC deployments on AWS SageMaker and GCP Vertex. Our models run in your cloud account and we cannot access your data or logs. This is best suited to organizations with data residency
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ElevenLabs Cloud API: Fast Production Deployment with Multiple Voice Models
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For everyone else, our cloud API is the fastest path to production. You get access to all our models and voices, and automatic scaling – managed entirely by ElevenLabs. We support data residency in the US, EU and India; Zero Retention Mode for enhanced privacy; and all of the
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On-Premise GPU Computing for Government and Secure Organizations
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On-Premise runs on your own servers, in your own data center, on Confidential Computing infrastructure with GPUs. This is best suited to government agencies and organizations that cannot procure cloud infrastructure in their required region.
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ElevenLabs Expands Deployment Options On-Premise and On-Device
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ElevenLabs can now be deployed on-premise and on-device. This expands our deployment options beyond cloud and VPC, to cover the full range of enterprise environments.
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Anthropic’s Daily Marketing Strategy with Claude Cowork Launch
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Anthropic is really using this as a marketing strategy to keep the conversation going every single day, with a daily update. I'd be happy if they continued like this! Claude (@claudeai) Claude Cowork is now generally available to all paid plans. For Enterprise, we are adding role-based access controls, group spend limits, usage analytics, and expanded OpenTelemetry to give admins what they need to deploy it across the org. — https://nitter.net/claudeai/status/2042273755485888810#m
→ View original post on X — @kimmonismus, 2026-04-09 16:38 UTC
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Max Agency Podcast: Building Production AI Agents with Hex
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🎙️Introducing Max Agency
— Harrison Chase (@hwchase17) 9 avril 2026
Max Agency is a new podcast where we go deep on how the best agents are actually being built: architecture decisions, tradeoffs, evals, and everything in between. Each episode, I sit down with engineering leaders who are doing this work in production.… pic.twitter.com/yqBsBcGQOR🎙️Introducing Max Agency Max Agency is a new podcast where we go deep on how the best agents are actually being built: architecture decisions, tradeoffs, evals, and everything in between. Each episode, I sit down with engineering leaders who are doing this work in production. Our first episode features Izzy Miller (@isidoremiller), AI Engineer at Hex (@_hex_tech). Hex has been shipping data agents since before most teams were even thinking about them, starting with single-cell text-to-SQL and graduating to a full Notebook agent that can work autonomously for 20 minutes on a complex analysis. Izzy has a lot of perspective on what it actually takes to get agents working well in production, and what breaks along the way. A few takeaways from our conversation: – Keep your eval sets small enough to hold in your head: Izzy runs 30-50 handcrafted "traps" with multiple repetitions, rather than hundreds of variants. If you can't explain why your agent fails each one, your eval set is too big – Day zero performance is almost irrelevant: The more interesting question is how the agent compounds. Izzy is building a 90-day simulation where the warehouse evolves and the agent has to accumulate understanding – You can catch agent errors without seeing the raw outputs: By running an LLM-as-a-judge over production usage and clustering the results, you can surface places where something likely went wrong, without needing to read individual conversations Watch the full episode on: – Youtube: piped.video/watch?v=Xyh1Eqcj… – Apple Podcasts: podcasts.apple.com/us/podcas… – Spotify: open.spotify.com/episode/1BJ…
→ View original post on X — @langchain, 2026-04-09 16:32 UTC
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Cloud cost optimization aligning consumption with enterprise value
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Cloud cost optimization isn’t about cutting spend—it’s about aligning consumption with value. https://
tinyurl.com/5y2ct8tk via @LinkedIn #ArtificialIntelligence #MachineLearning #GenerativeAI #EnterpriseAI #CloudComputing #DataPlatforms #CIO #CTO #ChiefDataOfficer #ExecutiveLeadership -
User manages and evaluates infrastructure with long-term agents
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I LOVE IT I basically manage and evaluate all my infra using long-term agents at this point