14 Feb 2024
/
Fine-Tuning Large-Language Models
Automate Contract Classification with Large-Language Models (LLMs)
The challenge
Imagine a team, dedicated with the task of manually sorting through around 400 contracts every day, each needing to be categorized into more than a thousand specific categories. This process was not only time-consuming, but also prone to human error. That's where we came in.
Time Saved
350
Hours/ Month
Cost Saved
15.000€
/ Month
# Contracts
8.000
/ Month
The NeoTask Solution
We crafted an automated system that classifies the contracts into over a thousand activities. This approach involved fine-tuning Large Language Models on the client's contract data, ensuring a deep understanding of the nuances involved in each document. Recognizing the importance of reliability, we introduced a trust metric into the system. It allowed us to calibrate the model's predictions, giving our client a clear view of how certain the system was with each classification. This not only enhanced the accuracy but also offered our client a transparent insight into the system's performance.
Integration and Impact
Seamless AWS Integration: The solution was smoothly integrated into the client's existing AWS workflow, facilitating immediate adoption.
Annual Efficiency: Now processes approximately 90,000 contracts annually, saving over 4000 hours of manual work each year.
14 Feb 2024
/
Fine-Tuning Large-Language Models
Automate Contract Classification with Large-Language Models (LLMs)
The challenge
Imagine a team, dedicated with the task of manually sorting through around 400 contracts every day, each needing to be categorized into more than a thousand specific categories. This process was not only time-consuming, but also prone to human error. That's where we came in.
Time Saved
350
Hours/ Month
Cost Saved
15.000€
/ Month
# Contracts
8.000
/ Month
The NeoTask Solution
We crafted an automated system that classifies the contracts into over a thousand activities. This approach involved fine-tuning Large Language Models on the client's contract data, ensuring a deep understanding of the nuances involved in each document. Recognizing the importance of reliability, we introduced a trust metric into the system. It allowed us to calibrate the model's predictions, giving our client a clear view of how certain the system was with each classification. This not only enhanced the accuracy but also offered our client a transparent insight into the system's performance.
Integration and Impact
Seamless AWS Integration: The solution was smoothly integrated into the client's existing AWS workflow, facilitating immediate adoption.
Annual Efficiency: Now processes approximately 90,000 contracts annually, saving over 4000 hours of manual work each year.
14 Feb 2024
/
Fine-Tuning Large-Language Models
Automate Contract Classification with Large-Language Models (LLMs)
The challenge
Imagine a team, dedicated with the task of manually sorting through around 400 contracts every day, each needing to be categorized into more than a thousand specific categories. This process was not only time-consuming, but also prone to human error. That's where we came in.
Time Saved
350
Hours/ Month
Cost Saved
15.000€
/ Month
# Contracts
8.000
/ Month
The NeoTask Solution
We crafted an automated system that classifies the contracts into over a thousand activities. This approach involved fine-tuning Large Language Models on the client's contract data, ensuring a deep understanding of the nuances involved in each document. Recognizing the importance of reliability, we introduced a trust metric into the system. It allowed us to calibrate the model's predictions, giving our client a clear view of how certain the system was with each classification. This not only enhanced the accuracy but also offered our client a transparent insight into the system's performance.
Integration and Impact
Seamless AWS Integration: The solution was smoothly integrated into the client's existing AWS workflow, facilitating immediate adoption.
Annual Efficiency: Now processes approximately 90,000 contracts annually, saving over 4000 hours of manual work each year.
14 Feb 2024
/
Fine-Tuning Large-Language Models
Automate Contract Classification with Large-Language Models (LLMs)
The challenge
Imagine a team, dedicated with the task of manually sorting through around 400 contracts every day, each needing to be categorized into more than a thousand specific categories. This process was not only time-consuming, but also prone to human error. That's where we came in.
Time Saved
350
Hours/ Month
Cost Saved
15.000€
/ Month
# Contracts
8.000
/ Month
The NeoTask Solution
We crafted an automated system that classifies the contracts into over a thousand activities. This approach involved fine-tuning Large Language Models on the client's contract data, ensuring a deep understanding of the nuances involved in each document. Recognizing the importance of reliability, we introduced a trust metric into the system. It allowed us to calibrate the model's predictions, giving our client a clear view of how certain the system was with each classification. This not only enhanced the accuracy but also offered our client a transparent insight into the system's performance.
Integration and Impact
Seamless AWS Integration: The solution was smoothly integrated into the client's existing AWS workflow, facilitating immediate adoption.
Annual Efficiency: Now processes approximately 90,000 contracts annually, saving over 4000 hours of manual work each year.
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