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BioRender Tech Stack

Web-based platform for scientific illustration and research communication

Software Development Toronto, Ontario 201–500 employees Founded 2017 Privately Held
biorender.com LinkedIn

BioRender is a design tool purpose-built for scientists to create publication-ready figures and diagrams. The stack reveals a modern, JavaScript-heavy web application (React, Node.js, Express, Vercel) backed by Python and ML infrastructure (PyTorch, TensorFlow), paired with a heavy sales and marketing apparatus (Salesforce, HubSpot, Marketo, Outreach). Hiring is heavily weighted toward sales and marketing roles over engineering—48 open positions with 31 posted in the last 30 days, but only 4 engineering spots—suggesting the company is in a sales-led scaling phase focused on enterprise expansion and go-to-market maturity rather than platform innovation.

Tech Stack 37 technologies

Core StackSlack React Node.js Express.js AWS Python PyTorch TensorFlow Figma Adobe Creative Cloud Cursor MongoDB Datadog Terraform Marketo HubSpot Salesforce Zapier Vercel Google Ads SAS Canva NetSuite Customer.io Looker GraphPad Prism JMP Stata Outreach Webflow+7 more

What BioRender Is Building

◆Challenges

  • Scaling highly interactive web application
  • Complex technical sales environments
  • Increasing sales productivity
  • Automating manual steps
  • Validating analysis correctness
  • Ensuring statistical workflows meet standards
  • Improving marketing roi
  • Optimizing lead generation
  • Scaling revenue engine
  • Refining input/output accuracy

▲Active Projects

  • Strategic account expansion plans
  • Drive attendance at biorender field events
  • Scaling highly interactive web application
  • Launch new enterprise features
  • Sales enablement strategy
  • Enterprise messaging and positioning
  • Sales strategy improvement
  • Pipeline council
  • Educational tutorials for researchers
  • Leadership meetings

Hiring Activity

Accelerating50 roles · 30 in 30d

Department

Sales
13
Marketing
12
Product
8
Engineering
4
Design
3
Executive
2
HR
2
Legal
2

Seniority

Senior
19
Mid
9
Manager
7
Lead
6
Junior
5
Director
2
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About BioRender

BioRender provides a SaaS platform for scientists to design, annotate, and share research visualizations. The product targets academic researchers, biotech professionals, and pharma teams who need to communicate complex scientific concepts visually. Founded in 2017 and backed by Y Combinator, the company operates from Toronto with a 201–500-person team. The platform is built on React and Node.js on AWS infrastructure, with Python and ML components likely supporting automated figure generation or validation. BioRender distributes through both self-serve and enterprise channels, reflected in active projects around strategic account expansion, enterprise feature launches, and educational onboarding for researchers.

HeadquartersToronto, Ontario
Company Size201–500 employees
Founded2017
Hiring MarketsUnited States, Canada, Ireland

Frequently Asked Questions

What tech stack does BioRender use?

BioRender runs React and Node.js on AWS, with Python, PyTorch, and TensorFlow powering backend logic. The platform is deployed on Vercel, uses MongoDB for storage, Datadog for monitoring, and Terraform for infrastructure-as-code. Sales and marketing stack: Salesforce, HubSpot, Marketo, Outreach, and NetSuite.

What is BioRender working on?

Current projects include scaling the web application for higher traffic and interactivity, launching new enterprise features, expanding into large strategic accounts, improving sales enablement, and developing educational content for researchers. The company is also working on enterprise messaging and pipeline development.

How this profile is built

BioRender's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.