Benchling

Benchling

Cloud-based platform for life sciences R&D

Overview

Benchling provides a cloud-based platform for life sciences research and development. It offers tools like an electronic lab notebook (ELN), molecular biology tools, and sample tracking to help scientists design experiments, record results, and analyze data, all in one system available by subscription. The platform works by grouping these tools into modules that researchers access over the internet; teams can collaborate, manage experimental workflows, and integrate data across projects. Benchling differs from many competitors by focusing specifically on life sciences R&D with an integrated, sector-tailored set of tools and enterprise options, rather than generic software. Its goal is to speed up biotech and pharmaceutical research, improve data management, and help researchers move ideas from concept to experiments to new therapies faster.

YC Company

About Benchling

Simplify's Rating
Why Benchling is rated
B
Rated A on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & Analytics

Enterprise Software

Biotechnology

Company Size

501-1,000

Company Stage

Series F

Total Funding

$411.1M

Headquarters

San Francisco, California

Founded

2012

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Simplify's Take

What believers are saying

  • May 2026 launches with Twist, Adaptyv, and Ginkgo deepen Benchling’s execution moat.
  • January 2026 Lilly TuneLab partnership gives customers access to proprietary models and federated learning.
  • AI Connectors and Baseten inference make Benchling the default layer for biotech AI workflows.

What critics are saying

  • Benchling’s headcount fell 18.2% from 2023 to March 2026, signaling operating pressure.
  • Point solutions from Twill, Dotmatics, and ELN incumbents can undercut Benchling’s platform expansion.
  • If biotech spending contracts again, enterprises delay renewals and Benchling’s growth narrative weakens.

What makes Benchling unique

  • Benchling unifies R&D records, AI models, and wet-lab execution in one workflow.
  • Model Hub, launched May 2026, embeds predictive models directly into scientific records.
  • Benchling Automation connects 200-plus instruments hardware-agnostically, avoiding vendor lock-in across labs.

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Funding

Total Funding

$411.1M

Above

Industry Average

Funded Over

8 Rounds

Series F funding comparison data is currently unavailable. We're working to provide this information soon!
Series F Funding Comparison
Coming Soon

Benefits

Four months of fully paid parental leave

401(k) plan

Remote working stipend

Yearly company-wide retreat

Monthly gym and wellness stipend

Commuter benefits

100% premiums covered for health, dental, and vision

Weekly company social events

Flexible PTO and company-wide winter holiday shutdown

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
Briya
Jul 29th, 2026
Briya named a finalist in the 2026 Fierce AI Innovation Awards.

Briya named a finalist in the 2026 Fierce AI Innovation Awards. The 2026 Fierce AI Innovation Awards have named Briya a finalist in the AI Innovation in Data Interoperability category. The Fierce AI Innovation Awards recognize organizations that move beyond simple AI pilots and deliver measurable results. A panel of industry leaders and expert judges evaluates each entry. They consider five criteria: innovation, impact, execution, scalability, and industry relevance. This recognition highlights Briya AIRE, a clinical-grade AI research environment. AIRE helps researchers turn questions into research-ready evidence using natural language. Briya joins Benchling AI, IMO Health, and Innovaccer as a finalist in the category. Fierce Life Sciences presents the awards as part of Questex's healthcare and life sciences portfolio. Fierce Life Sciences also publishes Fierce Biotech, Fierce Pharma, and Fierce Healthcare. Through these publications, events, and awards, Fierce provides news and analysis for healthcare, biotechnology, and pharmaceutical professionals. Why is healthcare data hard to use for research? Healthcare data is fragmented across EHRs, clinical research systems, public datasets, enterprise platforms, and unstructured medical documents. It is one of the world's most valuable resources for advancing medical research, yet much of it sits in systems that were never designed to work together. Data interoperability involves more than moving information between systems. Researchers must also connect, harmonize, and understand the data. Moreover, they need to trace each result back to its source and prepare the data for scientifically valid analysis. Before researchers can generate real-world evidence or build patient cohorts, they often spend months locating data, navigating privacy requirements, harmonizing different formats, defining study populations, and preparing information for analysis. These barriers make research slower, more expensive, and less accessible to smaller organizations. How does Briya AIRE make healthcare data research-ready? Briya AIRE was built to address these challenges. AIRE enables researchers to move from a question to research-ready evidence using natural language. Its suite of epidemiologist-designed AI agents helps researchers define study populations, explore and analyze healthcare data, build patient cohorts and comparison groups, and create transparent, reproducible reports. AIRE provides a federated research layer across complex healthcare data, meaning analysis runs where the data lives rather than requiring patient records to be moved or centralized. That layer spans structured records as well as the valuable information found in physician notes, pathology reports, and other clinical free text. Every study population and analysis remains transparent and inspectable, allowing researchers to understand how results were generated and reproduce their work. By connecting fragmented data and automating the most time-consuming stages of research, AIRE enables scientists and healthcare professionals to move through the research lifecycle with greater speed and confidence, from epidemiological studies to clinical trial feasibility assessments. For individual researchers and students, Briya also offers a free version of AIRE with access to public health datasets such as the Behavioral Risk Factor Surveillance System (BRFSS). These datasets have long been available online, but downloading them, querying them, and harmonizing fields that change from year to year can take a researcher weeks. In AIRE, the same work can be done in minutes using just natural language.

Tech in Asia
Jun 19th, 2026
AI inference startup Baseten nears $1.5b round.

AI inference startup Baseten nears $1.5b round. Baseten is reportedly close to raising US$1.5 billion in a split-priced round, with some investors buying in at a US$13 billion valuation and others at US$11 billion. Baseten, a US-based AI inference startup, announced a US$300 million series E at a US$5 billion valuation in January 2026, about nine months after a US$150 million series D. The company says it helps businesses run models for AI inference across managed cloud, self-hosted, and hybrid deployments. Baseten has publicly cited users including Cursor, Mercor, Clay, OpenEvidence, Lovable, and Abridge. Baseten also recently partnered with Benchling on inference tools for biotech customers. Stay updated on the go with our mobile app. Get latest insights with smoother, more personalized experience through TIA mobile app. How would you feel if you could no longer use Tech in Asia? Share, tag us, and land on our Wall of!

PR Newswire
May 28th, 2026
Benchling launches hardware-agnostic automation to connect lab instruments with AI workflows

Benchling has launched Benchling Automation, a hardware-agnostic system connecting lab instruments, automation systems and scientific records. The platform eliminates the need for bespoke integrations by working with existing instruments and integrating with any ELN/LIMS platform. Launch partners include HighRes, Automata, Ginkgo Bioworks, Celltrio, Opentrons and Hamilton. The system automatically dispatches experiments to instruments and returns analysed results directly into scientists' notebooks, pulling data from over 200 instruments. Teams can build and modify workflows without custom code, write Python for advanced analysis, and maintain full traceability from raw data to results. Benchling Automation consolidates Benchling Connect and Benchling Advanced Analytics under one expanded offering. The platform is available now and serves over 1,300 companies including Merck, Moderna and Sanofi.

PR Newswire
May 20th, 2026
Benchling partners with Baseten to bring on-demand GPU capacity for biotech AI models

Benchling and Baseten have announced Benchling Inference, providing biotech companies with on-demand GPU capacity to train and run scientific models without managing infrastructure. The service comes preloaded with leading scientific models and integrations for drug discovery workflows. Built on the Baseten Inference Stack, the platform addresses the bursty nature of drug discovery work, where teams need to run thousands of predictions quickly before extended quiet periods. It offers cold starts in 5-10 seconds and spans 15+ cloud providers. The service allows scientists to deploy third-party or internal models from a unified environment. For organisations with data sovereignty requirements, it can run in Baseten Cloud, customer virtual private clouds, or hybrid configurations. Benchling has raised $585 million to date and serves over 1,300 companies including Merck, Moderna and Sanofi.

PR Newswire
May 13th, 2026
Benchling launches Model Hub to integrate AI models directly into R&D workflows

Benchling has launched Model Hub, a platform feature allowing scientists to run AI models directly within their R&D workflow without requiring engineering infrastructure. The tool is now available to all Benchling customers. Model Hub enables scientists to select inputs from their Benchling registry, choose from curated models, and run predictions individually or in batches whilst maintaining full audit trails. The platform launches with open-source models including AlphaFold, Chai-1, and Protenix, with proprietary partnerships including Boltz PBC. Key features include batch predictions across candidate libraries, centralized prediction tracking, multiple sequence alignment support, and upgraded GPU infrastructure enabling four times more structure predictions. Scientists can access results as structured data connected to their experimental records, eliminating the months of engineering work previously required to run AI models.

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