Kickstart Your AI Journey with Rimes’ Lakehouse Copilot

In today’s data-driven world, the sheer volume of data can be overwhelming. Data discovery and surfacing of metadata have become significant challenges in the marketplace. Understanding what data is available and how to use it is a big barrier to data democratisation and empowering the front-office to self-serve.

An AI copilot can be a game-changer in this scenario. It can connect to your enterprise data, metadata and knowledge bases, putting the data at your fingertips. However, many asset managers and asset owners face data quality and data management challenges when integrating AI into their workflows:

·       There is a skillset gap - AI talent is rare, and many firms lack people with the right skills.

·       Budgets are tight – firms do not have a lot of money to spend on experimentation with AI especially given a fast-moving landscape and uncertainty of the regulatory environment.

·       Data security is essential - no one wants a data leak.

This is where Rimes can help! Using our recently announced Lakehouse Copilot with “bring your own data” (BYOD), Rimes can bootstrap your AI journey without the need for specialist technical skills or tech spend. It’s all securely hosted in Microsoft Azure, ensuring that no data leaves your ring-fenced environment and none of your data is shared with third-parties or used to train models.

So, how does a Lakehouse Copilot BYOD use-case work?

1. Scoping - The Rimes AI Product team collaborates with your business stakeholders to find a useful use-case for a proof of concept (POC) and determine the appropriate stakeholders and project champions as well as success metrics.
2. Domain Expertise – You provide subject matter experts (SMEs) to help identify the relevant data and metadata and to collaborate with Rimes to understand the schemas for structured data or relevant datapoints to be extracted for unstructured data.
3. Data Provision – You provide the data, any relevant metadata and sample Q&A pairs of natural language queries and their expected responses.
4. Implementation – The Rimes AI Product team collaborates with the SMEs to train your Lakehouse Copilot to comprehend your data using prompt engineering, retrieval augmented generation and other AI patterns.
5. Validation - Working with the Rimes AI Product Team, the SMEs validate the responses to sample queries and iterate on the Copilot to refine the output.
6. Adoption: The Rimes AI Product Team helps client champions to gather feedback and drive adoption using data-driven metrics.

Ready to start your AI journey with Rimes’ Lakehouse Copilot? Book a demo with us today to learn more.