Artificial intelligence company Shaip has launched a new Generative AI Platform aimed at addressing key challenges in AI development. The platform offers end-to-end support for Large Language Model (LLM) creation, focusing on data quality, model performance, system scalability, and regulatory compliance.
We are thrilled to announce the launch of our state-of-the-art Generative AI Platform! ☀ https://t.co/RFTmfFFW5r#AI #generativeai #innovations #TechNews #Shaip #AIplatforms #artificialintelligence
— Shaip (@weareshAIp) July 25, 2024
The Shaip Generative AI Platform provides tools for multiple stages of AI development:
- Data Generation: Offers ethically sourced data for training and testing, with support for synthetic dataset creation and API/SDK integration for custom data.
- Experimentation: Allows users to manage prompts and compare models from providers like OpenAI, Google, Anthropic, and Cohere, as well as open-source options.
- Evaluation: Includes over 50 automated metrics for assessing model performance, such as hallucination, relevancy, and toxicity. Custom evaluations and integration with open-source tools are also supported.
- Observability: Provides real-time monitoring and analytics for tracking AI system performance, costs, and usage in production environments.
Vatsal Ghiya, CEO of Shaip, stated, “Our Generative AI Platform is designed to address ethical concerns in AI by providing tools to ensure that training data is ethically collected, models respond reliably and ethically, and systems comply with regulatory standards.” He added, “By providing a comprehensive suite of tools and services, we’re empowering organizations to create AI systems that are not only powerful but also ethical and safe.”
The platform supports various use cases, including Q&A pair generation and text summarization. It offers both cloud and on-premise deployment options and combines automation with human oversight.
As generative AI continues to evolve rapidly, platforms like Shaip’s aim to provide developers and organizations with tools to navigate the complex landscape of AI development and deployment. The focus on ethical considerations and regulatory compliance reflects growing industry concerns about the responsible use of AI technologies.