ALL CASE STUDIES
AI Agent
Anomaly Detection
ChatLLM
Forecasting and Planning
Personalization AI
Predictive Modeling
FORECASTING AND PLANNING
A popular tools company selling product on multiple platforms including Amazon and Home Depot
The company used Abacus.AI to optimize inventory to ensure high availability of stock while limiting excess inventory
Problem
The company wanted to optimally manage inventory
Solution
The company used Abacus.AI Demand forecasting model to predict the inventory requirement for various SKUs
Results
Resulted in predictions that are 72% more accurate than what the company achieved using its models
Forecasted on ~5,000 SKUs
Decreased the forecasted percentage error by 42%
Forecasted for 1 month to 12 month timeframes
PERSONALIZATION AI
Very large retail company
The company used Abacus.AI to generate cart recommendations using Abacus.AI’s vector store
Problem
The company wanted to recommend items to users based on what’s already in their cart in real time
Solution
Abacus.AI vector store was used to generate recommendations
Results
Generated recommendations under 20ms latency
Under 20ms latency
Scales up to 10,000+ Queries/Second
Handles millions of requests/day
FORECASTING AND PLANNING
Consumer Retail & Manufacturing Company
The company used Abacus.AI to enhance inventory management and demand forecasting, reducing errors
Problem
The company wanted to forecast demand across 5000 SKUS to optimally manage inventory but had difficulty building accurate models
Solution
Used Demand Forecasting solution to predict the demand for each SKU
Results
Improved their models and predicting the demand more accurately
Built models were 72% more accurate than existing models
Decreased forecasting error by 42%
Predicted demands from 1-12 months in the future
PERSONALIZATION AI
Multinational Consumer Products Company
The company used Abacus.AI to increase e-commerce revenue by personalizing user experiences on their website
Problem
The company wanted to personalize the user experience on their website to increase revenue but many visitors had limited shopping histories
Solution
Used Personalized recommendation solution to build a streaming recommendation model
Results
Provided recommendations for all visitors, even those with limited histories
Increased overall orders by 10%
Over 10M page views
10K orders per day
CHATLLM
Household Consumer Goods Organization
The company used Abacus.AI to streamline customer service operations by automating the analysis of call transcripts
Problem
The company was spending too much time and money manually categorizing call transcripts to improve customer service
Solution
Used Text Classification and Extraction solution to build a model that could analyze the call transcripts
Results
Increased workplace efficiency, nearly eliminating manual reviews
Automated transcript reviews with 99% accuracy
Aggregated data from 100+ datasets
Classified transcripts into 15 classes
PERSONALIZATION AI
Multinational Home Improvement Retail Company
The company used Abacus.AI to boost online sales and reduce product returns by integrating advanced real-time recommendation models
Problem
The company needed to increase conversion rates of online sales while also decreasing returns to boost revenue
Solution
Leveraged Recommendation solution for real-time recommendations and plug-and-play PyTorch & TensorFlow models
Results
Deployed real-time recommendation models that were moved into production and integrated with their website
6 different real-time models deployed
Sale conversion rates increased by 3%
Returns decreased by 10%
FORECASTING AND PLANNING
Consumer Retail & Manufacturing Company
The company used Abacus.AI to improve the accuracy of demand forecasts, streamlining operations and reducing monthly expenditures
Problem
The company wanted to improve forecast accuracy for 1m SKUs over a period of six months
Solution
Used Demand Forecasting Solution to predict demand for each SKU
Results
Improved their models and predicting the demand more accurately
Built and deployed a model within 2 weeks
Spends $15k less per month on AI
Increased accuracy by over 25% across all categories
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