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Case Studies

ALL CASE STUDIES

Generative AI

Optimization

Structured ML

STRUCTURED ML

Complex Classifier

The company leveraged Abacus.AI to automate classifying small and medium-sized businesses (SMBs) into appropriate Standard Industrial Classification (SIC) codes

Problem

Manual assignment of SIC codes for SMBs was time-consuming and error-prone, creating bottlenecks in the lending process and requiring significant human resources

Solution

Implemented Abacus.AI's integrated solution combining ChatLLM, GenAI, and ML capabilities to automatically determine accurate SIC codes based on business information from various sources

Results

Achieved industry-leading accuracy in SIC code mapping while significantly reducing processing time

reduced manual processing time by 80%

achieved over 85% accuracy in SIC code classification

supports batch processing capabilities

STRUCTURED ML

Predictive Models In Sales And Marketing

The company used Abacus.AI to score and prioritize leads to efficiently allocate its sales and marketing resources

Problem

The company wanted to optimize marketing and sales resources by prioritizing the leads to target

Solution

Trained and deployed an Abacus.AI lead scoring model that helps the company determine the top leads to target

Results

Lead scoring helped the company optimize its sales & marketing resources and achieve higher growth

7X improvement in conversions

trained on ~10M leads

handled 2Bn+ events

STRUCTURED ML

Anomaly Detection

The company used Abacus.AI to build an anomaly model to detect quality of service issues

Problem

Reduce churn by proactively reaching out to customers experiencing quality of service issues

Solution

Used Abacus.AI anomaly detection model to identify abnormalities in user session data

Results

Identified 12 types of service issues that could cause a customer to churn using three different methods

processed user session data from 2.5M customers in real-time

calibrated on 2+ TB of data and over 1Bn events

identified 12 types of service issues

STRUCTURED ML

Smart Solar Panel Placement With Computer Vision

Solar Quote utilised Abacus.AI's computer vision capabilities to automate the detection of home roofs, angles, and obstructions, streamlining the solar panel placement process

Problem

The manual process of assessing home roofs for solar panel placement was time-consuming, prone to errors, and required significant human effort, leading to inefficiencies in project timelines

Solution

Implemented Abacus.AI's computer vision solution to analyse visual data of home roofs, automatically detecting roof angles, obstructions, and other relevant features to optimise solar panel placement

Results

The process of roof assessment and solar panel placement planning was significantly streamlined, improving operational efficiency

reduced roof assessment time by 60%

5X improvement in operational efficiency

enhanced project completion timelines by 40%

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