Alembic Technologies Tech Stack

Causal AI platform for enterprise marketing attribution and revenue forecasting

Software Development San Francisco, California 51–200 employees Founded 2018 Privately Held

Alembic builds a Causal AI platform centered on deterministic marketing attribution and revenue forecasting, built on graph neural networks and Python/Node.js infrastructure. The engineering-heavy hiring profile (8 engineers across 16 open roles) paired with active projects spanning production causal systems, real-time analytics, ETL automation, and ML prototype productionization suggests they're scaling infrastructure to move measurement outputs from research into repeatable, low-latency enterprise workflows. Pain-point data confirms friction: integration friction, slow time-to-first-value, and the hard problem of transforming experimental algorithms into production systems are top internal challenges.

Tech Stack 55 technologies

Core StackPython Node.js JavaScript TypeScript React PostgreSQL Elasticsearch AWS Docker Kubernetes Terraform pandas Linux Apache NiFi Cursor GitHub Copilot Pandas NumPy GCP Azure CI/CD SQLAlchemy Pydantic Bash Poetry Linear Numba SciPy OpenAPI Sphinx+22 more

What Alembic Technologies Is Building

◆Challenges

Integration friction
Measurement challenges
Statistical rigor at enterprise scale
Marketing attribution challenges
Proving value of data cloud ai solutions
Manual integration work
Slow time-to-first-value
Inefficient product development lifecycle
Delayed product delivery
Transforming experimental ideas into production systems

▲Active Projects

Production systems for causal inference
Tools and libraries for advanced analytics
Real-time analytics
Ci/cd pipeline evolution
Field studies
Research implementations
Python sdk development
Etl/elt pipeline automation
Algorithms for marketing measurement
Ml prototype production

Hiring Activity

Steady15 roles · 5 in 30d

Department

Engineering

Data

Legal

Product

Research

Sales

Seniority

Senior

Mid

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About Alembic Technologies

Alembic develops a Causal AI platform that applies causal inference and graph neural-network analysis to enterprise marketing and advertising measurement. The product focuses initially on deterministic attribution and revenue forecasting across brand, performance, and omnichannel advertising budgets, with longer-term ambitions to extend causal analysis across broader enterprise workflows. Founded in 2018 and based in San Francisco, the company operates at 51–200 employees. The technical backbone spans Python, PostgreSQL, Elasticsearch, and cloud infrastructure (AWS, GCP, Azure) with deployment automation via Docker, Kubernetes, and Terraform. Core development is concentrated in the United States, with senior-level hiring velocity steady at five new roles posted in the last 30 days.

HeadquartersSan Francisco, California

Company Size51–200 employees

Founded2018

Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Alembic Technologies use?

Python, Node.js, JavaScript, TypeScript, React, PostgreSQL, Elasticsearch, AWS, GCP, and Azure. Infrastructure and DevOps uses Docker, Kubernetes, Terraform, and CI/CD pipelines. Data tooling includes pandas, NumPy, SciPy, SQLAlchemy, Pydantic, and Apache NiFi.

What is Alembic Technologies working on?

Production causal inference systems, real-time analytics, Python SDK development, ETL/ELT pipeline automation, CI/CD evolution, and algorithms for marketing measurement. Recent focus includes transitioning research implementations and ML prototypes into production systems.