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Intelligo Tech Stack

AI-powered risk intelligence for due diligence and compliance

Technology, Information and Internet New York, NY 51–200 employees Founded 2014 Privately Held

Intelligo combines machine learning and human analysis to surface risk signals on people and companies. The stack (Python, scikit-learn, Pandas, TypeScript/Node.js front-end on AWS/GCP) reflects a data-heavy organization, and their active project list—data collection, API integration, human data entry workflows—reveals the core operational challenge: turning fragmented public sources into structured intelligence. Hiring is accelerating across engineering, data, and research, with senior-level roles suggesting they're scaling beyond initial product-market fit.

Tech Stack 14 technologies

Core StackAWS TypeScript Node.js React Angular Vue Python Docker Kubernetes scikit-learn Pandas GCP Azure SQL

What Intelligo Is Building

◆Challenges

Data collection
Complex data problems
Collecting data from public sources
Integrating with apis
Human data entry for sources

▲Active Projects

Data collection initiative
Robust data collection product
Api integration
Human data entry workflow

Hiring Activity

Accelerating5 roles · 3 in 30d

Department

Engineering

2

Data

1

Product

1

Research

1

Seniority

Mid

2

Senior

2

Lead

1

Notable leadership hires: Team Lead

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About Intelligo

Intelligo operates a risk intelligence platform for financial institutions, corporations, and investment firms conducting due diligence. The service bundles AI-driven analysis with human expert review to generate 360-degree profiles on subjects, covering pre-investment screening, M&A diligence, ongoing monitoring, and compliance use cases (AML, FCPA). Founded in 2014 and headquartered in New York, the company employs 51–200 people and is currently hiring across engineering, data, product, and research teams.

HeadquartersNew York, NY

Company Size51–200 employees

Founded2014

Hiring MarketsIsrael

Frequently Asked Questions

What tech stack does Intelligo use?

Python, scikit-learn, and Pandas for data processing; TypeScript and Node.js for backend; React, Angular, and Vue for front-end; AWS and GCP for infrastructure; Docker and Kubernetes for orchestration.