Benchling

Benchling is a purpose-built, cloud-native research platform used by academic labs, startups and large biopharma teams to digitize experiments and manage the full life cycle of biological entities. It combines a collaborative electronic lab notebook (ELN), a biologically aware registry for DNA/proteins/cell lines and other entities, inventory and sample lineage, sequence design and analysis tools, and configurable workflows. Customers use Benchling to capture richer experimental context, enforce consistency with templates and schemas, and build a single, searchable source of truth that supports reproducible science and regulated workflows. The platform is designed to be extended programmatically. Benchling’s Developer Platform exposes REST APIs, language SDKs (notably a Python SDK), example R helpers for dataset access, and an interactive API reference. Developers can build Benchling Apps to perform read/write operations, keep Benchling in sync with other systems, or represent lab instruments as apps that upload results. For event-driven workflows, Benchling supports “evented” apps that route events to your service via AWS EventBridge. Benchling Connect is provided for instrument connectivity and file processing inside the Notebook UI. For analytics, Benchling offers a Data Warehouse (SQL-accessible) so teams can connect BI tools or Jupyter notebooks and build dashboards and charts from the same data model. Common uses include: integrating instruments to automatically ingest assay outputs and attach them to notebook entries; bulk-loading or exporting large registries and assay datasets; building dashboards that surface project-level metrics and experiment outcomes; and automating request/approval workflows (for example, a Request + Slack notification walkthrough). Benchling supports molecular design tasks such as plasmid maps, primer design, sequence alignment and in-context virtual digests, and its registry enforces uniqueness and models parent/child lineage (eg, parent constructs and derived aliquots) so teams can trace provenance across cloning and production workflows. Benchling’s Bioprocess module extends these capabilities for process development with recipe design, batch execution, and ISA88-compatible recipe models to accelerate tech transfer and scale-up. Benchling is highly configurable and integrates with common lab and IT ecosystems. Out-of-the-box and partner integrations are available for instruments and third‑party software, while the Data Warehouse provides a SQL endpoint for BI tools. Developers can use the SDK and bulk endpoints to import and export data programmatically; pagination defaults (50 per page, max 100) and bulk create limits (most endpoints ~1,000 entities per request, with some endpoints up to 2,500) are documented to help design efficient calls. Benchling enforces rate, throughput and payload limits to protect tenant stability (for example, a tenant-wide API rate example cited is 60 requests per 30 seconds) and returns standard HTTP errors (including 413 for oversized payloads). Best practices include using bulk endpoints instead of per-entity loops, implementing exponential backoff on 429/5xx responses, and leveraging evented apps to reduce polling. Getting started requires tenant admin configuration to grant Developer Platform access and creating a personal API key to use the interactive reference. Benchling provides step-by-step guides and examples — Getting Started with Benchling Apps, SDK Quickstarts, uploading results via API, Jupyter + Warehouse examples, and instrument/file processing with Benchling Connect — plus release notes and SDK versioning details. Benchling also offers services, implementation support, and training to help teams configure schemas, migrate data, and validate workflows for regulated environments. The platform is trusted by hundreds of thousands of scientists and over a thousand biotech organizations, and is designed to scale as teams adopt automated instruments, build analytics pipelines, and move toward AI-enabled discovery.