Using GenAI with DataPAI's data integration capabilities breaks down data silos, boosts efficiency, cuts costs, increases revenue, and empowers users with actionable insights.
AI readiness starts with sound data strategy. phData can ensure your organization is ready to make the most of your data and help create a roadmap for a successful AI adoption within 4-8 weeks.
DatapAI's ML Engineers can help design, build, and manage your AI & MLOps platform on top of Snowflake and the Modern Data Stack.
Our teams of data scientists, ML engineers, data engineers, and analytics consultants have the breadth of experience necessary to advance AI initiatives at any point on the AI readiness journey.
This demo showcases an IT Chat Assistant powered by LLMs and RAG. DataAI offer end-2-end data pipelines to ingest 300+ difference source connections and transform data into different cloud distinations, data warehouses like Snowflake, BigQuery Redshift, or Sqllite3 and DuckDB. When a user asks a question from any of these distinations, the AI utilizes an API that inputs the question along with information from the dataPAI data models. The DataPAI platform provides OpenAI with details about specific fields in the data and their meanings. This approach to prompt engineering helps guide OpenAI to identify which fields are relevant to the user's question.
Generative AI capabilities automate or streamline content authorship and tailor messaging for individuals or curated audiences.
LLMs excel at extracting insights from unstructured data. We've worked with our clients to build intelligent processing pipelines for documents, automating manual tasks, and yielding substantial operational savings.
LLMs are incredibly powerful at making decisions based on historical patterns and other relevant data.
Context-aware chatbots are revolutionizing the way organizations support their teams and disseminate information.
Generative AI is extremely powerful for automating time-consuming workflows.