Services

AI and ML

Industries

Human Resources

Product

AI technology company based in Silicon Valley. Leading investors such as Google, Randstad Innovation Fund, Bain Capital Ventures, and Cervin Ventures back it. The company addresses the traditional inefficiencies of lost applicants due to poor candidate experience, the high cost of recruiting due to overburdening hiring teams with menial tasks, and lack of visibility and control for HR leadership.

Business needs

  • Build a user communication system in natural language for interacting with applicants.
  • Utilize Natural Language Processing (NLP), Natural Language Generation (NLG), and Natural Language
  • Understanding (NLU) for effective real-time communication during the recruiting process.
  • Implement new modules in AI to expand system functionality and capabilities.
  • Develop an ontology for a preliminary interview, including a question-answer format and appointment slot scheduling, streamlining the interview process.

Suggested solutions from svitla

  • Used Python and advanced ML libraries to develop sophisticated AI models.
  • Implemented advanced methods in linear regression and TF-IDF for pattern matching, along with string similarity algorithms.
  • Built a comprehensive regression testing framework in Python to validate AI models.
  • Developed an effective unit testing system, ensuring robustness and reliability in software development.
  • Leveraged AWS and Azure cloud platforms for scalable and efficient computing resources.
  • Implemented Docker containers within a microservice architecture for streamlined application deployment and management.
  • Integrated RabbitMQ as a message broker to manage and route messages between different services.

Technologies

Programming language & frameworks: Python (Spacy, Pandas, Scikit-learn, Jumspell)

Cloud: AWS, Azure

Container: Docker container, Microservice architecture

Database: MySQL, Redis

Message-broke: RabbitMQ

Value delivered

  • Extended an AI system to handle pre-interview and appointment management
  • Implemented processing user communications in natural language on chat.
  • Improved the maintenance system, ensuring reliability and smoother operation.

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