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The ability to split inference workloads between different environments is interesting indeed. #ai #inference #startups

Hybrid AI is the future. We're not just following the trend, we're leading it with NeuroSplit. NeuroSplit smartly chooses between cloud, on-device, or a combo of both – in REAL TIME. This not only gives you the best possible AI experience without sacrificing speed or quality

Looking for low latency in vision models? Skymel NeuroSplit has you covered! Achieve up to 60% cost reduction and 10X performance improvement with our Hybrid AI infrastructure. Optimize speed, cost, and privacy with dynamic local and cloud processing.

Curious about optimizing your AI spend? Our latest video compares two Small Language Model (SLM) deployments: 1️⃣ 100% cloud-based SLM ☁️ 2️⃣ Hybrid: 33% local device, 67% cloud 💻 + ☁️ Watch the performance. Compare the costs. The numbers speak for themselves. In just a few

Excited to showcase our startup at #PyTorchConference2024 #StartupShowcase! Please stop by our demo table to see AI orchestration innovation in action. Attending the flare party? Find us before or after – we'd love to chat! #AIStartup #PyTorch #MachineLearning

Building AI features in 2025: 10% coding 90% anxiety about what model drops tomorrow Soon™ 👀

2025: Where 'choosing the right model' is the wrong problem to solve. Jan 28

Why do today's AI decisions feel like tomorrow's regrets? Not for long. Jan 28 👀

The paradox of modern AI: It automates everything except its own deployment. Until today. Introducing the Orchestrator Agent - AI that deploys AI: - Real-time model selection - Automatic device/cloud decisions - Continuous optimization - Zero infrastructure management Results

Today, AI Starts Deploying Itself 🚀 For the first time ever, AI is orchestrating how AI runs. This changes everything. Introducing the Orchestrator Agent (OA) - an AI that lives on your users' devices and makes real-time decisions about: - Which models to use - Where to

AI is about to get personal. Really personal. Right now, AI feels powerful but generic—one model trying to serve millions of users. But imagine a future where AI is built just for YOU: It knows your preferences. It adapts to your context. It evolves with your needs. We're

Engineering hours spent on AI implementation at one client: Before Skymel: 436 hours After Skymel: 1.5 hours Same functionality. Better performance. 60% lower API costs. skymel.com

When model switching becomes a config change instead of a code change, fascinating things happen. Teams start experimenting more, comparing results, and becoming truly provider-agnostic. The psychological freedom is surprisingly powerful.

We've been thinking about AI integration all wrong. It's not about connecting to models—it's about expressing intent and letting an intelligent layer handle the rest.

The history of computing is defined by rising levels of abstraction. From machine code to assembly to high-level languages to frameworks. AI is following this same path, and the next logical step is abstracting away model-specific implementation details.

"AI agents aren't just chatbots with fancy prompts. They're systems that perceive, think, act, and learn on their own." What Are AI Agents, Really? No universally accepted definition exists, but there’s a common shape emerging. Most working definitions revolve around this loop:

Our founders Neetu and Sushant spoke with Pulse 2.0 about how Skymel got started -- from early work on hybrid inference (NeuroSplit) to our current focus on dynamic AI pipelines with the Orchestrator Agent. Full interview: pulse2.com/skymel-profile…