Panos.AI is meant to become the world's 1st digital advisor to immediately help companies and their employees with automating business processes more efficiently, because it already knows processes and solutions – thanks to the integrated artificial intelligence!
During the hackathon, we wanted to tackle the challenge of providing first strategic insights to companies for kickstarting automation initiatives based on publicly available data. We wanted to prove, that it is technically possible using NLP to recommend potential and quantified candidates for automation using job postings in English language with salary information, which typically also include listings of manual tasks. The output is an overview of ranked departments within companies which have been classified based on the job postings according to their automation potential quantified by employee cost per year to show potential savings as well as benchmarking. This would allow customers to quickly decide in which departments they should look first to improve efficiencies/cost for meeting company goals/competitive situation.
This prototype classifies text between two classes using embeddings: 1-Automation unlikely / 2- Automation likely
The Cohere API & SDK allows us to test different pre-trained models from different transformers without minimal changes to our code. Our dataset contains 4345 job postings classified via rule-based logic & expert review. But we will use just 500 for the prototype.
Steps:
Classifying business automation needs from publicly available data is unheard of, until now, companies have primarily access to generic content on where automation potential could reside. This is typically followed by lengthy consulting, workshop and software implementation activities limited to certain departments missing the overall picture for informed strategic decisions.
Statistics show that therefore 40-70% of transformation projects are not as successful as initially planned or even fail completely.
Customers in general:
Customer Size segments, by priority:
Typical customers, by priority:
Typical contact person for customers:
Special customer segments by industry, which e.g., have an increased need for automation & require an industry solution:
Specific customer segments by rollout, languages/regions/country by priority (example):
Partners in general: