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Case Studies

ALL CASE STUDIES

AI Agents

AI BRAIN

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

AI BRAIN

Financial Business Intelligence

Abacus helped the company improve employee productivity through chat-based solutions for financial and usability queries

Problem

The employees in the company struggled to access and get financial information from portfolio and transactional data

Solution

Abacus helped the company with a chat-based solution that differentiated usability queries from financial queries and provided query responses from Zendesk and Portfolio, transactional data, respectively

Results

Implemented the Abacus AI solution and achieved 95% accuracy in response rate

95% accuracy in query response

35% reduction in query resolution time

reduced operational expenses by 20%

AI AGENTS

Financial Analysis

The company leveraged Abacus.AI's AI Agents and GenAI solutions to answer complex financial queries

Problem

The company struggled to manage and provide efficient access to data and the ability to derive insights from the large and complex data that existed

Solution

Abacus.AI helped the company convert natural language queries to SQL queries to get accurate results with APIs as complex as that of with 30k endpoints

Results

The company used Abacus.AI's AI agents to work with their complex APIs

20% increase in operational efficiency

achieved 80% accuracy in data extraction

works with APIs with more than 30k endpoints

AI BRAIN

Customer Call Analysis

The company used Abacus.AI to identify key pieces of information from customer call transcripts and classify them

Problem

The company wanted to reduce costs by automating the categorization of calls based on the transcripts

Solution

Used Abacus.AI's named entity recognition model to automate this process

Results

Achieved 99% accuracy in classifying calls, saving multiple hours of human effort

classified call records into 15 classes

achieved an accuracy of 99%

aggregated over 100 datasets

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