AI platform that auto-documents workflows and identifies process improvements
Scribe automates process documentation and discovery at scale—Python + Django + PostgreSQL backend, React + Next.js frontend, with PyTorch and JAX for ML inference. The tech stack reflects a data-heavy platform: Snowflake, dbt, Dagster, and Airflow power workflow mining and analytics. Hiring leans heavily toward sales (10 open roles) and enterprise motion (strategic account plans, contract playbooks, large-deal cycle optimization), while the data-infrastructure projects (large-scale ingestion, query optimization) suggest Scribe is wrestling with the performance costs of processing workflows across millions of users.
Notable leadership hires: Head of Legal
Scribe is a workflow AI platform that automatically generates step-by-step process documentation from user actions, then surfaces improvement opportunities by analyzing those workflows at scale. The product is built for mid-market and enterprise organizations seeking to standardize work, onboard faster, and reduce errors. The company operates from San Francisco with a 51–200 person team, hiring actively in the United States and Serbia. Core capabilities include automated guide capture (Scribe Capture) and workflow optimization (Scribe Optimize), marketed around documentation speed gains and error reduction.
Backend: Python, Django, PostgreSQL, Redis, Celery on AWS. Frontend: React, Next.js, TypeScript, Tailwind CSS. ML: PyTorch, JAX. Data: Snowflake, dbt, Dagster, Airflow, Metaplane. QA: Playwright.
San Francisco, CA. The company was founded in 2019 and remains privately held with 51–200 employees.
Other companies in the same industry, closest in size