Prophecy, the low-code data transformation platform, announced two new product offerings: Prophecy Generative AI Platform and Prophecy Data Copilot.
The new Prophecy Generative AI Platform provides a simple way for organizations to power generative AI applications using privately-owned, enterprise data.This new offering leverages Prophecy’s flagship product, the low-code data transformation platform.
In addition, Prophecy is also announcing the launch of the Prophecy Data Copilot, an AI assistant that automatically creates data pipelines based on natural language prompts, and improves pipeline quality with greater test coverage.
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“We are seeing tremendous results from building applications that combine enterprise data with off-the-shelf LLM models. Our belief is that for the vast majority of enterprise use cases, the era of hiring machine learning engineers who train proprietary models, or specialized LLMs is over,” shared Prophecy Co-Founder and CEO, Raj Bains. “Now all you will need is a private knowledge warehouse that provides private context along with questions and the LLMs give very relevant answers. With Prophecy’s new platform release, a data or application engineer can build an application like a support-bot on private data in a week”.
Generative AI technology is becoming mainstream, with nearly all businesses looking to adopt and implement this technology into their existing workflows.But today’s generative AI applications are trained against public data, limiting their usefulness when it comes to answering questions that are specific to an organization. The Prophecy Generative AI Platform democratizes AI for technical and non-technical teams by:
- Putting the power of generative AI against enterprise data in the hands of every user in every organization
- Speeding up the development of generative AI applications against enterprise data
- Supporting nearly unlimited use cases by leveraging the full breadth of enterprise data
“We see generative AI based copilots making low-code the default way to build applications and data pipelines in enterprises,” shared Prophecy Co-Founder, Maciej Szpakowski. “We already see a 30-40% productivity boost from low-code adoption in our customer base, that coupled with another 30-40% from copilots will make starting with code financially untenable for the majority of enterprise use cases. The future of enterprise development is definitely copilot powered low-code, and we’re excited to see our customers get this boost as they adopt Prophecy Data Copilot.”
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Prophecy Data Copilot assists and automates numerous data-related tasks. Data Copilot:
- Democratizes the creation and delivery of data products. Data products are underpinned by data transformations. With Copilot, users can describe transformations using natural language. Copilot then converts these natural language prompts into Prophecy visual components and transformation logic, along with corresponding code.
- Improves efficiency and quality of pipeline creation. Copilot suggests data tests, enabling greater test coverage and increasing confidence in data. Copilot also suggests what transformations to use next, minimizing errors when joining, filtering, and aggregating data.
- Prevents data misuse. Copilot automatically generates descriptions for data pipelines and datasets. This includes, for example, an explanation of how a column was computed.
“Generative AI and LLMs have become mainstream practically overnight and the hype is warranted,” shared SanjMo Principal, Sanjeev Mohan.“However, today’s applications, such as ChatGPT, artificially constrain the usefulness to data that is available in the public domain.The next frontier is applying this power technology to privately-held, enterprise data, something I didn’t think would happen till years from now. These new solutions from Prophecy will enable teams to use their data to move the needle in significant ways.”
With the launch and platform updates, Prophecy further democratizes data transformation, boosting productivity and empowering non-technical users to access and leverage data in their everyday workflows.
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