Vercel's AI Gateway simplifies AI-in-production complexity

AI is moving faster than ever. But with speed comes chaos... runaway #GPU bills, shadow #AIprojects, and no clear #ROI. That’s the story we kept hearing from #CIOs and #CFOs. So we built Amberflo.ai AI Control Tower. A single pane of glass to govern #AI access, #meterToken & GPU #usage in real time, allocate costs, and enforce chargebacks. The result? 🔹 No more bill shocks 🔹 Clear accountability for every dollar 🔹 AI investments tied directly to business value This is how enterprises turn AI ambition into sustainable impact. #AWS #GOOGLE #AZURE #BILLSHOCK #FINOPS

Semantic Kernel, Agent Core, Vertex AI, Crew AI, Langraph... the Agentic AI landscape in 2025 feels like the wild west. 🤠 If you're trying to figure out how to build with agents or wondering what else is out there, my latest article is for you: The 2025 Agentic AI Maze: A Developer’s Guide to Choosing the Right Framework This isn't just a list of features. I cut through the hype to compare the big cloud platforms against the open-source heroes, so you can solve real production headaches such as: The Big Clouds: How Microsoft, AWS, and Google are solving enterprise security and scaling (and the vendor lock-in you accept). Open-Source Powerhouses: The flexibility of LangGraph, CrewAI, and AutoGen for rapid prototyping (and the production chaos you inherit). The Gold Standard: Why a hybrid approach is emerging as the winning strategy for enterprise-grade agents. Plus, there's a quick-reference cheat sheet at the end to solidify your choice. Stop spinning your wheels and start building smarter. Read the full developer's guide here 🔗 in the comments. What's the biggest production headache you've faced with AI agents so far? #AgenticAI #Frameworks #LLM #GenerativeAI #AIdevelopment #LangChain #SemanticKernel #Databricks #MLOps

𝐀𝐈 𝐝𝐨𝐞𝐬𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐛𝐞 𝐬𝐦𝐚𝐫𝐭, 𝐢𝐭 𝐧𝐞𝐞𝐝𝐬 𝐭𝐨 𝐛𝐞 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞. ⚡⁣ One of the biggest challenges with GenAI today isn’t the models themselves, but what happens when:⁣ o  A provider suddenly goes down⁣ o  Latency spikes during peak usage⁣ o  Costs spiral with every extra query⁣ ⁣ That’s where smart gateways come in. Think of them as the air traffic control for AI, automatically:⁣ ✅ Rerouting requests when a provider struggles⁣ ✅ Balancing quality vs. cost in real time⁣ ✅ Keeping systems running without teams firefighting at 2 AM⁣ ⁣ What’s exciting is how both enterprises and the open source ecosystem are tackling this:⁣ o  𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 like AWS Bedrock, Azure AI Studio, Google Vertex AI → managed resiliency & integrations⁣ o  𝐀𝐏𝐈 𝐠𝐚𝐭𝐞𝐰𝐚𝐲𝐬 (Kong, Tyk) + observability tools (Datadog, Prometheus, OpenTelemetry) → health checks, circuit breakers, real time insights⁣ o  𝐎𝐩𝐞𝐧 𝐬𝐨𝐮𝐫𝐜𝐞 𝐬𝐭𝐚𝐜𝐤𝐬 like LiteLLM, LangChain, BentoML → multi model orchestration with real flexibility⁣ ⁣ 👉 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: Resilience is becoming just as important as intelligence in GenAI.⁣ ⁣ Curious to know how are you (or your teams) approaching routing, failover, and cost optimization in your AI stack?⁣ ⁣ #GenAI #AIInfrastructure #AIGateways #AIOperations #MLOps #LangChain #AWS #AzureAI #VertexAI #OpenSourceAI⁣

Nuklai is joining forces with LinqAI to unite real-time, verifiable data with decentralized compute power to shape the next era of agentic AI. For AI to deliver real impact especially for enterprises, it needs more than models — it needs verifiable data and flexible compute power. Nexus brings the intelligence layer, enabling agents to reason with live, traceable data. LinqAI contributes LinqProtocol, a DePIN compute marketplace for running inference, simulations, and large-scale workloads—without relying on costly centralized cloud providers. Together, we’re laying the foundation for a future where AI infrastructure is scalable, open, and trustworthy, giving businesses and developers the tools they need to build confidently. #AI #Data #Compute #Infrastructure

🚀 Generative AI 2025: From Hype → Production ⚡ Enterprises are moving beyond chatbots. GenAI is now about scalable, governed, business-ready systems. 🔑 Key Shifts Happening Now 🤖 Agentic Workflows → AI agents executing end-to-end business processes 📚 RAG Pipelines → Reliable, domain-grounded responses 🛠️ Full-Stack AI Engineering → LangChain + FastAPI + JWT + CI/CD + Monitoring ☁️ Enterprise Deployment → AWS EC2/EKS, Docker, Kubernetes, NGINX 📈 Business ROI → Success = Tech depth + Domain impact ✨ My focus: bridging research & business impact by delivering secure, scalable, enterprise-grade GenAI platforms. 💡 The next leaders in AI will be those who can code, scale, and deliver value. #GenerativeAI #AIagents #RAG #LangChain #FastAPI #AWS #EnterpriseAI

Agentic AI - From Research into Reality Over the last year, the conversation about AI has shifted. It’s no longer only about building smarter models, it’s about creating systems that can act on behalf of people in real-world workflows. This is what Agentic AI represents. At AWS, the recent release of Amazon Bedrock Agentcore is an important step in this direction. It gives organisations the ability to build AI agents that can reason, plan, and take action across different systems while staying within secure guardrails. With OpenAI models now available on Bedrock too, customers have even more choice in how they design these intelligent workflows. The promise is clear. Less manual orchestration, faster decision making, and new ways of automating business processes that were once too complex for traditional approaches. The challenge is equally clear. Agentic AI must be designed responsibly, with strong governance, explainability, and security at its core. We are only at the beginning, but it feels like a turning point. How do you see Agentic AI changing the way we design and run cloud architectures? #AgenticAI #ArtificialIntelligence #AWS #AmazonBedrock #CloudArchitecture #AIInnovation #GenerativeAI #CloudComputing

🚀 The Rise & Fall of ML Inference Platforms 💡 From 2020 to 2022, every startup wanted to be the "AWS for AI inference." ⚡ VC money flowed, GPUs were bought, and promises of seamless model serving filled the air. But by 2025, most of these platforms vanished, pivoted, or got acquired for pennies. 🤯 Why? ✨ Key Shifts: 🏢 Hyperscalers (AWS, GCP, Azure) steamrolled with managed inference 🛠️ Open Source (vLLM, TGI, TensorRT, Ray Serve) became the default 🔄 Full-stack AI platforms (Databricks, Hugging Face) absorbed inference into bigger ecosystems ⚙️ LLMOps got easier with quantization, LoRA, and better GPU scheduling 🤖 The AI Agent revolution shifted value to orchestration, reasoning, and multi-modal workflows 💸 High infra costs + price-sensitive customers = tough unit economics 🔥 The Lesson: Infrastructure value is temporary. Ecosystem value is durable. 👉 The future lies in: 🧠 Agent orchestration platforms 🎥 Multi-modal AI stacks 📱 Edge AI optimization 🗄️ AI-native databases 📌 If you’re building in AI infra today, don’t just solve the tech problem—build for the ecosystem. That’s where lasting value lives. 💬 What do you think is the next AI infra wave to get commoditized? https://lnkd.in/gt9FJHfB #AI #MachineLearning #Inference #MLOps #Agents #Infrastructure #OpenSource #FutureOfAI

The pace of development for AI agents is accelerating, with more cloud providers offering support for agentic workflows. A noteworthy recent release is the open-source Amazon Web Services (AWS) Strands Agents SDK. Strands is an open-source SDK that lets developers build and run AI agents with very little code. It's not just a new experimental tool. AWS has been using it for a couple months now. The combination of simplicity and being battle-tested makes it an incredibly compelling option for anyone looking to build agent-based applications. If you haven't and you're interested in applications using Agentic AI, check it out: https://lnkd.in/emF7svcy #AWS #OpenSource #SDK #ArtificialIntelligence #AgenticAI #AI

💬 "Edge AI excels in dynamic environments, and Blaize’s flexible graph streaming processor delivers local, scene-aware processing that reduces latency and energy use, enabling smarter, faster real-time responses for security, automotive, and low-power applications,” Val Cook, Chief Software Architect at Blaize. 🌐 Explore how adaptable systems, data flow architectures, and hybrid edge-centralized AI solutions are revolutionizing real-time AI applications. Val Cook highlights that innovation and rethinking the foundation of AI hardware and software are essential for shaping the next generation of intelligent systems. 🔗 Listen to the Podcast on The AI Forecast: Rebuilding AI from the Ground Up with Val Cook – https://lnkd.in/gfJYTf9m #AI #AIInfrastructure #BZAI #Blaize #EdgeComputing #TechInnovation #TheAIForecast

🚀 AWS Launches AgentCore to Lead the Agentic AI Era At the AWS Summit in New York, Amazon unveiled Amazon Bedrock AgentCore—a powerful platform for building secure, enterprise-scale autonomous AI agents. Features include: 🧠 Secure web access 🧠 Memory management 🧠 Contextual reasoning 🧠 Model Context Protocol (MCP) 🧠 Agent-to-Agent (A2A) interactions Backed by a US $100M investment and a new AI agents marketplace, AgentCore positions AWS as a central hub for trusted agentic AI development. At Transform LogiQ, we’re helping organisations explore how agentic AI can drive real-world efficiencies. #TransformLogiq #AWSAgentCore #AgenticAI #AILeadership #EnterpriseAI #DigitalTransformation #aws #aidevelopment #digitaltransformation