Using Argonaut, you can self-host your LLMs on Kubernetes environments in AWS and GCP without having to worry about privacy, scalability issues, and the infrastructure grunt work. Join our waitlist.
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Deploying LLMs using Argonaut with ease
Join the waitlist to be the first to know when its out
1. Give permissions to your cloud
Connect your AWS/GCP account to Argonaut. Using a service account key, we securely manage your resources and environments.
2. Create a kubernetes cluster with GPUs
Create GPU-enabled Kubernetes clusters with UI or using raw yaml values.
3. Pick model to deploy from Huggingface or Replicate
Pick your model from Huggingface or Replicate and deploy. Fully customizable infra and deployments.
💽 Self-host vector databases
Self-host vector databases like Weaviate and Chroma. Enjoy benefits of reduced latency and increased control over data security and privacy.
📊 Autoscaling with KEDA
Argonaut handles the autoscaling for your apps with KEDA with complete flexibility of scaling strategy customizable to the requirements of each workload.
📓 Your choice of tools
Bring your tools of choice to your cloud environment. Easily host Jupyter Notebooks, Airflow, dbt and more.
⏩ Kubernetes clusters with GPU support
Deploy and manage dedicated GPUs in your clusters via AWS and GCP in one click.
Access controls and collaboration 🤝
Improve your team’s collaboration and pace of shipping by providing self-serve capabilities. Set up multiple workspaces to manage controls
Integrate with vector databases
Self host chroma, weaviate in minutes or use the hosted versions
Autoscale your apps
Customizable austoscaling strategies that work out of the box
Choose your tools
Integrate with tools like airflow, dbt, and others, easily
GPU nodes in k8s
Speed up your training with dedicated GPUs
Instead of constantly thinking about infrastructure, CI/CD processes, and hiring a DevOps engineer for these, we only spend time developing our applications. Argonaut has increased our productivity and made us much faster. Because DevOps is overhead.