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NeoRecruit Tech Stack

AI-powered recruitment platform for skill verification and candidate screening

Information Technology & Services London 11–50 employees Privately Held

NeoRecruit builds an AI hiring engine focused on skill validation—sourcing, CV analysis, proctored interviews, and cheating detection. The tech stack reveals a data-science-heavy operation: Python, R, SAS, Stata, Databricks, and Azure Synapse sit alongside Power BI and Microsoft Fabric for analytics. Hiring is concentrated in data (3 roles) and research (2 roles) at mid-to-senior levels, with India as the primary hiring region—typical for ML-driven recruitment startups scaling research and data infrastructure.

Tech Stack 29 technologies

Core StackPower BI Power Apps Power Automate Azure Data Factory Databricks Power Query SAS Python AWS GitHub Actions Jenkins Apache Airflow AWS Glue AWS Lambda Terraform Docker Kubernetes Microsoft Fabric SQL Azure Synapse DAX R Stata CDISC Azure GCP AWS Step Functions JFrog Artifactory Bash

What NeoRecruit Is Building

◆Challenges

Complex supply chain problems
Supply chain analytics challenges

▲Active Projects

Self-service bi adoption

Hiring Activity

Decelerating5 roles · 1 in 30d

Department

Data

3

Research

2

Seniority

Mid

3

Senior

2

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About NeoRecruit

NeoRecruit operates an AI hiring platform designed to replace resume-based screening with skill-based assessment. The product combines AI-powered candidate sourcing, contextual CV analysis to move beyond keyword matching, deep interview simulations to test provable capabilities, and proctoring to prevent AI-aided cheating. The company has powered over 9,000 interviews and targets mid-market hiring teams seeking to reduce time-to-hire and false-positive candidate rejections. Based in London with 11–50 employees, the organization is privately held.

HeadquartersLondon

Company Size11–50 employees

Hiring MarketsIndia

Frequently Asked Questions

What tech stack does NeoRecruit use?

NeoRecruit operates on Python, R, SAS, and Stata for modeling; Databricks and Azure Synapse for data processing; Power BI, Microsoft Fabric, and Power Apps for analytics and user interfaces; and AWS, Azure, and GCP for cloud infrastructure, plus Kubernetes and Docker for containerization.