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With our recent relationship with AWS we focus on markets where technology, innovation, and support in building Innovative Applications with AI & ML can unlock Long-Term Value and drive Economic Growth.
Build, Fine-Tune and Deploy your AI Models & Workspaces through Auto-Scaling Containers on AWS EC2 Instances. This ensures your data stays secure & private within your Private Cloud Containers.Start Building
Accelerate time-to-value of your generative AI-driven application using WorqHat AI's easy-to-use APIs right within your AWS Console & Accounts, without managing Infrastructure or Billing separately.Coming Soon
Enterprises get seamless access to our state-of-the-art models while choosing the Machines you want to deploy it on and streamling your VPC Procurement process all within your AWS Environment.Contact Us
WorqHat with AWS is enabling businesses across various sectors to launch AI-based products and services. By combining the superior, ready-to-use models of WorqHat AI with the robust infrastructure and specialized services of AWS, companies can safely utilize LLMs. This collaboration is set to redefine how we handle data, interact, and acquire knowledge.
With WorqHat's machine deployments on AWS, clients have the ability to operate in a safer and more confidential space for their model deployment and training. This guarantees that all client data remains secure and confined within their personal AWS VPCs. Users also have the flexibility to choose the machines they prefer for model deployment.
With AWS GPU Focused Machines, you have the freedom to select a setup that aligns with your requirements. You can choose from various configurations, each offering different levels of processing power that are cost-effective and capable of operating our highly optimized LLM Models, tailored to your needs.
What are the benefits for Companies
AWS helps us provide containerization options on Custom Machines Deployed to AWS. This means that whenever you create a Workspace, all your Databases, Training Datasets and Fine-Tuning Processes are contained within Dedicated, Private & Secure Environments.
You can choose between our Default Virtual Machines / Containers when creating a Workspace. However, depending on use cases, we also let enterprises choose Custom Machines to deploy to production and connect to other AWS Services using Internal IP Addresses.
Our Mission is to Come Together and build delightful tools and machine learning models to empower the next billion people to create amazing software for work, for life, and everything in between!Connect with Us