Managing product claims across markets and languages is time-consuming and complex.
Unilever needed a faster, more scalable way to extract, translate, and optimise claims for product display pages.
Neem identified an opportunity to transform this process using AI claims automation, reducing manual effort while improving efficiency and accuracy.
Overview:
Unilever’s existing process for optimising PDPs required manually extracting product claims from multiple markets and languages, translating them, and entering them into spreadsheets.
Neem identified an opportunity to streamline this workflow using AI claims automation, enabling faster extraction, translation, and structuring of product claims.
This approach significantly improved efficiency while maintaining accuracy and flexibility for manual review.
Client Snapshot
- Client: Unilever
- Industry: Retail CPG and dComm
- Type: AI-driven automation and web application development
- Challenge: Use AI to automate an existing process for increased efficiency
Services delivered
- Web Application
- Tech services
Neem delivered an automated process to streamline efficiency and cut down on laborious man hours when extracting product claims to optimise product display pages.
"An absolute game changer of a quote goes here over a few lines... probably three for best"
The Challenge: Extracting from Unstructured Text across Multiple Languages
The existing process relied heavily on manual effort and was not suited to scale. Extracting product claims across markets required navigating unstructured data, multiple languages, and contextual variations.
1. Multilingual Complexity: Claims needed to be identified across multiple languages and formats.
2. Contextual Variability: Similar claims were expressed differently, making standardisation difficult.
3. Manual Translation and Entry: The process required manual translation, validation, and data entry.
4. Automation Limitations: Traditional automation could not handle the variability and context required.
The Core Challenge
Develop a scalable AI claims automation solution capable of extracting, translating, and structuring product claims with high accuracy.
The Neem Approach:
Neem implemented a structured approach to design and deploy an AI claims automation solution.
1. Proof of Concept (POC):
Neem proactively developed a working POC to demonstrate the potential of AI claims automation before formal engagement.
2. Configurable Rules Engine:
A configurable framework was built to allow users to define parameters for claim extraction and optimisation.
This enabled flexibility while maintaining control over outputs.
3. Context-Aware AI Integration:
Neem integrated OpenAI capabilities to enable context-aware processing of multilingual product claims.
This allowed the system to identify variations in meaning rather than relying on exact keyword matches.
4. Prototype Development:
A working prototype was developed and presented to the client.
This demonstrated how AI claims automation could be applied at scale to improve efficiency.
1. Proof of Concept (POC):
Neem proactively developed a working POC to demonstrate the potential of AI claims automation before formal engagement.
2. Configurable Rules Engine:
A configurable framework was built to allow users to define parameters for claim extraction and optimisation.
This enabled flexibility while maintaining control over outputs.
3. Context-Aware AI Integration:
Neem integrated OpenAI capabilities to enable context-aware processing of multilingual product claims.
This allowed the system to identify variations in meaning rather than relying on exact keyword matches.
4. Prototype Development:
A working prototype was developed and presented to the client.
This demonstrated how AI claims automation could be applied at scale to improve efficiency.
Key Capabilities
To deliver this AI claims automation solution, Neem provided:
Web application with OpenAI integration: Delivered a fully embedded application with automated claim extraction and processing.
Configurable Rules Engine: Enabled customisation of search parameters and refinement of outputs.
CSV Import/Export Functionality: Allowed easy integration and data sharing across systems.
High Accuracy Performance (80–90%): Delivered reliable results while allowing for manual validation.
Impact & Outcomes: High Accuracy Efficiency
The AI claims automation solution transformed a manual, time-intensive process into a scalable workflow.
Significant Time Savings: Reduced hours of manual effort and ongoing operational costs.
Improved Efficiency: Enabled faster extraction and processing of product claims.
Scalable Automation: Allowed the process to be applied across multiple markets and languages.
Sustained Client Value: Unilever renewed support following successful delivery.
Looking to implement AI claims automation in your business?
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Speak to our development team today.
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