The no-code data automation platform teaching operations and finance teams to automate the work software forgot.
San Francisco · Founder & CEO Alex Yaseen · Backed by OpenView, Matrix & Thrive Capital
Every operations team has a person who owns The Spreadsheet - the one that reconciles invoices, routes orders, or matches inventory across a dozen mismatched files each week. Parabola is built for that person. The San Francisco company makes a no-code platform where operators describe a messy, recurring data process and get back a working, documented workflow that runs on a schedule.
Founder and CEO Alex Yaseen studied finance at USC and worked at Deloitte before starting the company. In consulting he watched large enterprises run mission-critical processes on manual spreadsheet work, and set out to build a tool that let the people closest to the work automate it - without waiting on an engineer. Parabola publicly launched its browser-based drag-and-drop tool in 2017 and, by its own reporting, took roughly five years to find durable product-market fit before revenue accelerated.
The pitch it settled on is unusually specific: automate the "un-automatable." Where task-based tools connect apps and analytics suites demand data-savvy users, Parabola goes after the raw mess - PDFs, email attachments, and inconsistent spreadsheets - and turns it into structured, usable data.
Figures reported by Parabola; funding per public announcements (June 2023).
Parabola's users sit in operations, finance, supply chain, and logistics - most often at fast-moving ecommerce, retail, CPG, and freight companies. Named customers include Brooklinen, On, WHOOP, SKIMS, KIND, Fabletics, Caraway, Rhone, Tecovas, Ruggable, Faherty, Uber Freight, Lyft, Mercury, and Deel, alongside logistics platform Flexport.
These are teams drowning in recurring, deadline-driven data chores: month-end close, invoice audits, inventory reconciliation, and order routing.
The platform extracts structured data from unstructured inputs like PDFs, emails, and inconsistent spreadsheets; categorizes and classifies records; and standardizes messy values such as company names, addresses, and date formats.
Supply chain and logistics leaders use it to automate inventory management, order routing, and vendor data processing, while finance teams use it to compress reconciliation and reporting work that used to run late into the night.
My team can now see a problem and fix it themselves. Watching them take ownership of work that used to wait on someone else is exhilarating.- Marie Fodness, AVP Global Operations, WHOOP
A browser-based, no-code canvas where users combine drag-and-drop building blocks to pull data from 1,000+ sources, clean and transform it, and run the flow on a schedule.
AI-powered steps that read unstructured PDFs and emails, extract structured fields, classify records, and standardize inconsistent values across files.
An AI agent builder: describe what you want to automate in plain language, and Prowork asks follow-up questions to build transparent, auditable agents for logistics, supply chain, and finance.
Parabola looks a lot like Alteryx on capability, but is fully cloud-based and far faster to learn - if you understand spreadsheets, you can build a flow in an afternoon. And unlike many AI agents, its steps are designed to be visible and inspectable, which matters when finance and supply chain teams need an audit trail.
| Parabola | Task tools (Zapier) | Analytics suites (Alteryx) | |
|---|---|---|---|
| Core focus | Data transformation & workflows | App-to-app tasks | Advanced data analytics |
| Who builds it | Non-technical operators | Non-technical users | Data-savvy analysts |
| Setup | Fully cloud, minutes to value | Cloud | Heavier install |
| Handles messy PDFs/email | Yes, with AI blocks | Limited | Possible, complex |
| Auditable steps | Yes, by design | Partial | Yes |
Other alternatives referenced publicly: Make, Workato, Tray.io, Alloy Automation, n8n.
Parabola runs on a B2B SaaS subscription model. Notably, it does not charge per "task" the way many automation tools do; instead it limits the number of flows and steps per plan. Public pricing has ranged from an entry-level Solo tier around $80/month up to team and enterprise plans for larger operations and finance organizations.
The company has raised roughly $34 million in total. Its $24M Series B, announced June 2023, was led by OpenView with participation from Matrix, Thrive Capital, and Flexport - plus an operator-heavy roster of angels.
Revenue is estimated by third parties at roughly $6.5M annually and is not confirmed by the company.
Investors also include the founders/CEOs of Mercury, Lattice, Webflow, Linear, Harry's, Warby Parker and Allbirds.
Alex Yaseen starts the company to help non-technical teams automate manual data processes.
Parabola ships its browser-based, drag-and-drop workflow tool for collaborative data automation.
New AI capabilities extract, classify, and standardize data from unstructured inputs.
OpenView leads a round to expand the product and double down on ecommerce, retail, CPG, and logistics.
A natural-language AI agent builder aimed at logistics, supply chain, and finance teams.
Parabola is a no-code data automation platform that lets operations and finance teams build workflows - or AI agents - that pull data from PDFs, emails, spreadsheets, and APIs, clean and transform it, and run automatically on a schedule.
Parabola (legally Parabola Labs, Inc.) was founded by Alex Yaseen, its CEO. The company publicly launched its workflow tool in 2017.
Parabola has raised roughly $34 million in total, including a $24 million Series B led by OpenView in June 2023 with participation from Matrix, Thrive Capital, and Flexport.
Operations, finance, supply chain, and logistics teams at ecommerce, retail, CPG, and freight companies - including Brooklinen, On, WHOOP, SKIMS, Flexport, and Lyft.
Unlike Zapier's task-based app connections, Parabola focuses on transforming and cleaning data across whole workflows. Compared with Alteryx, it offers similar data-transformation power but is fully cloud-based and far faster to learn.