Hebbia Tech Stack

AI platform for financial analysis and investment research

Software Development New York, NY 51–200 employees Founded 2020 Privately Held

Hebbia operates an AI platform serving investment banks and large asset managers with document intelligence and agentic workflows. The tech stack spans cloud providers (AWS, Azure, GCP) with Spark, Airflow, and dbt for data pipelines, plus Snowflake for warehousing—a setup built for distributed processing and ML inference at scale. Current priorities are performance optimization, document indexing latency, and scaling ingestion to support rapid customer adoption, with engineering-led hiring (13 roles open) focused at senior and mid levels.

Tech Stack 26 technologies

Core StackAWS Python Apache Spark Hadoop Apache Airflow dbt Snowflake Adobe Premiere Pro After Effects Figma Okta Slack Adobe Illustrator Azure GCP SQL SharePoint Dropbox Google Workspace Linear OneLogin Gemini

What Hebbia Is Building

◆Challenges

Performance optimization at scale
Building agentic interfaces with enterprise control
Reducing indexing latency
Repetitive manual workflows
Manual drain of users' workflows
Optimizing uptime and reliability
Support hypergrowth trajectory
Improving data pipeline performance
Ensuring data security compliance
Scaling document ingestion

▲Active Projects

Scaling matrix platform
Distributed dag orchestrator for llm inference
Performance optimization for document indexing
Ci/cd systems
High-scale document build system
Universal indexing
Strategic growth initiatives post-sale
Deployment and early adoption
Commission bespoke ai use cases
Elastic data representation and metadata generation for private data retrieval

Hiring Activity

Steady30 roles · 9 in 30d

Department

Engineering

Sales

Design

Data

Marketing

Product

Finance

Seniority

Senior

Mid

Junior

Staff

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About Hebbia

Hebbia builds generative AI agents for institutional finance, enabling investment professionals to extract insights from filings, research, and internal documents with cited sources. The platform automates analyst workflows including document generation, research synthesis, and deal screening. Founded in 2020, the company operates from New York with 51–200 employees and serves investment banks alongside over 40% of the largest global asset managers by assets under management. Active development spans distributed orchestration, high-scale document processing, and agentic interfaces tailored to enterprise risk and compliance requirements.

HeadquartersNew York, NY

Company Size51–200 employees

Founded2020

Hiring MarketsUnited States, United Kingdom

Frequently Asked Questions

What tech stack does Hebbia use?

Hebbia uses AWS, Azure, and GCP for cloud infrastructure; Python and SQL for application logic; Spark, Hadoop, and Airflow for distributed data processing; dbt and Snowflake for data transformation and warehousing; and collaboration tools including Slack, Google Workspace, and Okta for identity management.

What is Hebbia working on?

Current projects include scaling matrix platforms, building distributed DAG orchestrators for LLM inference, optimizing document indexing performance, deploying CI/CD systems, and designing elastic data representation for private data retrieval to support high-scale financial workflows.