To remain competitive in today's fast-paced market, you must make data-driven decisions while navigating three major challenges.
Talent
Building Generative AI platform requires a team of specialists, including data scientists, AI architects, machine learning engineers, DevOps engineers, and software engineers. These resources are both scarce and costly.
Time
Building a Generative AI platform from scratch can take 6-9 months. Delaying time to market and allowing competitors to capitalize on the evolving market.
Cost
Cost is a major obstacle for many organizations in adopting Generative AI. Implementing and optimizing Generative AI models requires significant financial investments.
CloudKitect solves this problem by empowering your existing development teams to provision an end-to-end Generative AI platform in under an hour using these 3 simple steps.
Learn
Review the documentation and watch instructional videos on setting up your workstation and using the SDK to write a few lines of code.
Launch
Deploy code into your private AWS account that automatically provisions the entire infrastructure, including vector databases, ingestion pipelines, QA and summarization APIS, and more.
Leverage
Upload your private data and begin interacting with your platform.
Why CloudKitect GenAI Platform
API First Design
Seamlessly integrate your existing platforms with our developer-friendly REST APIs.
Security and Compliance
We leverage our enhanced AWS services, which are pre-configured and hardened to meet various security and compliance standards such as PCI, HIPAA, NIST4, GDPR, MAS, and more.
SaaS Based Model
With our SaaS-based delivery model, there are no vendor lock-ins or long-term licensing commitments. It operates on a pay-as-you-go basis with minimal commitment.
Frequently Asked Questions
Everything you need to know about the product and billing.
Absolutely not. The platform is set up in your own AWS account, ensuring you retain full control and don’t have to share your private data with external entities.
Our AI platform currently supports four widely used LLM models. You can switch between models in real-time. We are adding support for latest models pretty much weekly.