Case Study - Automating Product Research Work with AI Agents
WrangleWorks, a platform that automates data work using AI, approached Seeai with a vision to bring the capabilities of Large Language Models (LLMs) to their AI-powered platform.
- Client
- WrangleWorks
- Year
- Service
- LLM-powered AI agent development
Our client
WrangleWorks, a platform that automates data work using AI, approached Seeai with a vision to bring the capabilities of Large Language Models (LLMs) to their AI-powered platform. Their WranglesXL Ad-in eliminates 80% of product data work for distributors. With ChatGPT, WrangleWorks saw the potential of utilising LLMs for data wrangling and needed a team of experts to conduct research and development.
Our challenge
Distributors often have product content files that can contain up to thousands of rows of unvalidated product data. The manual process of searching information of each product on the internet through many websites is time-consuming and prone to errors, resulting in days or even weeks of manual data work for dedicated team members. Data wrangling, which involves cleaning, standardising, and enriching raw data, is a significant bottleneck in the process.
Our approach
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Industry knowledge: Seeai spent time expanding their knowledge of the industrial distribution and manufacturing industries to understand the data and identify the exact pain points where automation can benefit users.
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Targeted task selection: Instead of full development from the start, Seeai worked together with teams at WrangleWorks to identify a specific task that could only be solved with LLMs and had the largest impact if solved, allowing for quick iteration and understanding of the project.
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System design: To minimise the indeterministic nature of LLMs, Seeai built a system around LLMs rather than using LLMs as the system itself, using conventional solutions wherever possible for complete control over the output.
The results: Seeai developed an LLM-powered AI agent to automate the product research work, integrating it with WrangleWorks' existing Python-based package for creating data transformation "recipes."
The AI agent not only searches for products but also other information such as companies, broadening its scope as the project matured.
Key outcomes
Reduced manual work: The AI Agent automated the tedious process of searching for individual product information.
Seamless integration: The AI Agent was successfully integrated into WrangleWorks existing platform, accessible to customers using their Microsoft Excel WranglesXL Add-In.
Extendability: The use case of the AI Agent is not limited to product search, creating more opportunities for the product.
Seeai's expertise in LLMs and software engineering, combined with their targeted approach and industry knowledge, enabled WrangleWorks to become a pioneer in successfully creating an AI agent to automate data wrangling tasks.
What we did
- LLM
- Custom Integration
- R&D
- Python