Cloudelligent

A security tool that flags everything isn't protecting you, it's training your team to ignore it. AWS just put a number on a problem most security teams already feel. Their new Deception Benchmark tests whether AI models can actually tell a real vulnerability apart from code that looks risky but isn't, across nearly 15,000 samples, 16 languages, and 70+ vulnerability categories. The result: under standard prompting, accuracy landed around the mid-50s, close to a coin flip. Not one of the 12 models tested kept both false positives and false negatives under 10%. That's the gap between an AI tool that looks impressive in a demo and one your team can actually trust to triage real findings. Trust in a security tool isn't something you get by turning it on, it's something you build by knowing exactly where it's reliable and where it isn't. This is the kind of evaluation we do before recommending any AI-assisted security tooling to a client, so false positives don't become the reason nobody looks at the real ones. Evaluating AI security tools for your team? Let's talk about what to test for: https://lnkd.in/g6vBYxYW #AWS #CloudSecurity #AIsecurity #Cloudelligent #AWSPartners

AI agents are moving from experimentation to real-world execution. That means security and governance need to evolve with them. A production-ready agent needs more than a capable model. It needs clear boundaries, controlled access, risk-based policies, monitoring, and human oversight where it matters. In our latest blog, we explore how Building Safer AI Agent Guardrails for Production on AWS can help organizations build autonomous systems that are safer, more controlled, and easier to govern. Read the full blog here: https://lnkd.in/gstpW-S4 #AIAgents #AIAgentSecurity #AIGovernance #AWS #GenerativeAI #AgenticAI #CloudSecurity

A mattress quiz can match you with the right product in minutes. What it can't do is answer your follow-up questions. That's the gap GoodBed set out to close. GoodBed runs the largest mattress review site on the web, matching millions of shoppers to their best-fit mattress every year. But once someone got a quiz result, the interaction stopped there, no way to ask why a mattress was recommended or how two options compared. Cloudelligent built a conversational layer on Amazon Bedrock that sits on top of GoodBed's existing recommendation engine: ✅ Connected product details, reviews, and editorial content scattered across Postgres, APIs, CMS, and S3 using retrieval-augmented generation and vector search. ✅ Grounded every chatbot answer in GoodBed's own Recommendation API, keeping responses accurate even when quiz answers were incomplete. ✅ Stood up a testing environment so GoodBed's team can refine the chatbot before launch, with room to add content and features later. The result: shoppers can now ask why a mattress was recommended, compare options side by side, and get pointed to GoodBed's resources, all inside one conversation instead of a static results page. Read the full case study here: https://lnkd.in/gzXRahg8 #GenerativeAI #AmazonBedrock #AWSPartners #APNProud #Cloudelligent #Chatbot #HomeFurnishings

The countdown is on! Cloudelligent is coming to the Los Angeles Small Business Expo 2026 in Pasadena, CA. Stop by and discover how we’re helping businesses put AWS, AI, and cloud technology to work. Here’s what you can explore with our team: Agentic BI for smarter, data-driven insights   Amazon Bedrock AgentCore for production-ready AI agents Amazon Connect for modern customer experiences Migration Quick Start to accelerate your move to AWS As an AI-native consulting firm and AWS AI Services Competency Partner, we’re ready to talk about what’s possible for your business. September 30, 2026 9:30 AM – 4:00 PM PST Pasadena Convention Center Come meet the Cloudelligent team and see what’s next for your business. RSVP: https://lnkd.in/gT4M45GW #SmallBusinessExpo #LosAngeles #Pasadena #Cloudelligent #AWS #AI #CloudComputing #SmallBusiness

Your AI agent may be ready for the prototype stage. But moving from prototype to production takes more than a working model. It requires the right foundation for security, scalability, governance, and visibility. With Amazon Bedrock AgentCore Activator, Cloudelligent helps you build and deploy production-ready AI agents in your AWS environment, with identity, guardrails, memory, APIs, and agent monitoring built into the journey. Go from prototype to production in weeks, not months, with a structured path designed to help you launch with confidence. Ready to take your AI agent to production? Schedule your free assessment today: https://lnkd.in/eNfy_TKX #AWS #AmazonBedrock #AgentCore #AIAgents #GenerativeAI #Cloudelligent #AWSPartner #AITransformation

Dumping your entire contract library into a chatbot and hoping for the best isn't an AI strategy. OpenAI's GPT-6 Astra just went generally available on Amazon Bedrock, and it's built for exactly that kind of heavy lifting: a 1 million token context window, deeper reasoning, and browser/computer use, so it can work through large codebases, long contracts, or full document sets in one pass. The bigger deal isn't the model itself, it's where it's running. On Bedrock, your inference data isn't used to train the model, and you get the same access controls and audit trail you already use across the rest of your AWS environment. More model choice is good. Knowing which model to point at which workload, with the right guardrails around it, is what actually determines whether your AI investment pays off. We help clients match the right foundation model to the job, inside an architecture that's secure and easy to govern from day one. Not sure which model fits your workload? Let's map it out: https://lnkd.in/grAPZVW7 #AWS #AmazonBedrock #GenAI #Cloudelligent #EnterpriseAI

Your AI agent just scanned your Redshift warehouse and flagged slow queries in minutes. Now imagine a hundred agents doing that across your entire company. Who's watching? AWS's new Agent Toolkit solves a real problem: it gives IAM the ability to tell a human's actions apart from an agent's, even under the same role. For one developer in one account, that's close to solved. For an enterprise running agents across dozens of accounts, it's where the real gaps start: ✅ IAM condition keys are local to one account. Nothing ties policy together across your AWS Organization. ✅ There's no company-wide kill switch. Stopping one agent in one account doesn't touch the other hundred it can reach. ✅ CloudTrail logs that a request happened, not which business process asked for it or who approved the agent's scope. Gartner expects 40% of enterprises to pull back autonomous agents by 2027 once gaps like these surface in production, and CSA already found 82% of enterprises have agents nobody can fully account for. Our latest blog breaks down exactly where the AWS Agent Toolkit stops and what an enterprise governance layer needs to pick up from there. Read the full breakdown: https://lnkd.in/gD9un7sD #AWS #AgenticAI #AIGovernance #Cloudelligent #AWSPartner #APNProud #CloudSecurity

Your GPU workloads shouldn’t have to wait. Or cost a fortune. There’s a faster way to explore what High Performance Computing (HPC) and GPU computing can look like on AWS. With Cloudelligent’s AWS HPC & GPU Activator, move from discovery to a live, cost-optimized environment in just 3 weeks. Think up to 90% lower compute costs, faster model loading, and a practical way to validate your workloads before scaling. Discover the offer on AWS Marketplace and see what your workloads can achieve: https://lnkd.in/dXF6hN4h #AWS #HPC #GPUComputing #AI #CloudOptimization #Cloudelligent

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AI agents can find a security vulnerability in your codebase faster than your team can log the ticket. Unfortunately, attackers are using the exact models to do the same thing. When autonomous models like Claude Mythos can map an entire attack path in minutes, traditional security response times fall behind. At that speed, minor oversight becomes critical exposure: ✔️ Overly broad permissions let compromised agents move sideways across systems. ✔️ Unsanitized inputs turn a single prompt into an open door to your infrastructure. ✔️ Stopping machine-speed threats requires defenses that operate at the same velocity. In our latest breakdown of AWS Continuum, we detail the layered control model, spanning identity, tooling, memory, runtime, and observability, designed to isolate and contain autonomous agents before an exploit occurs. Read the full architecture breakdown: https://lnkd.in/gMUCXfHz #AWS #AWSContinuum #AgenticAI #AISecurity #ClaudeMythos