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What is BenchSci?

Optimize the entire selection process for reagents and model systems to eliminate inefficiencies and reduce errors that can result in costly experimental setbacks. By condensing the decision-making timeframe from the usual 12 weeks to a mere 30 seconds, project timelines can be significantly shortened. This strategy not only minimizes direct expenses associated with consumables but also has the capacity to generate substantial annual savings. In addition, it supports the organizational mission by allowing scientists to reclaim precious research time. Experience concrete business benefits from AI through a solution that is both proven and ready for implementation. Over 41,200 scientists, representing 15 of the top 20 pharmaceutical companies and more than 4,450 academic institutions, rely on BenchSci’s AI-Assisted Antibody Selection to design more effective experiments while achieving significant reductions in hard costs. It’s crucial to recognize that antibodies account for only 40-50% of the reagent-related failures. Gain access to a wealth of experimental evidence, an extensive catalog of reagents and model systems, and independent validations, all within a single intuitive interface. Leverage real-world experimental data sourced from 11.2 million scientific publications, including those often not publicly available, for a comprehensive approach to research. This cutting-edge methodology equips researchers with the tools necessary to make swift and informed decisions, ultimately transforming the landscape of scientific experimentation. By streamlining processes and enhancing data accessibility, the opportunity for breakthroughs in research becomes significantly more attainable.

What is Bench47?

Bench47 equips teams and their AI-enhanced agents with a cohesive and intelligible memory alongside a diverse skill set. Important decisions, events, strategies, and discoveries are captured in a user-friendly Markdown format, facilitating easy review, modification, and export by team members. A range of MCP-compatible agents, such as Claude Code, Codex, and Cursor, can leverage the same knowledge repository and provide fresh perspectives. This platform allows teams to keep their skills current across multiple devices, link knowledge with code adjustments, and effortlessly transfer responsibilities between agents while maintaining context. Moreover, these agents can kickstart workflows for both development and production through notifications, webhooks, and pre-scheduled tasks. The adaptability of Bench47 permits it to function on selected machines, complying with access permissions defined by the team. It can also be deployed as a hosted solution, self-hosted on the client's own systems, or exclusively in the customer's cloud, thereby catering to a variety of organizational requirements. This robust flexibility positions Bench47 as an essential asset for boosting collaboration and productivity in AI-oriented initiatives, ultimately driving better outcomes in project execution.

Media

Media

Integrations Supported

Integrations Supported

Claude Code
Codex CLI
Gemini CLI
GitHub
Linear
Model Context Protocol (MCP)
Sentry

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$20/month
The Free plan is $0 for one person. Pro is $20/month and includes five seats. Team is $40/month for 10 seats, with each additional seat priced at $5/month, for teams of up to 100 people. Annual billing saves 20%; prices are in USD before tax. Enterprise, self-hosted, and dedicated deployments are quoted. Agent-provider usage is billed separately.
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

BenchSci

Date Founded

2015

Company Location

Canada

Company Website

www.benchsci.com

Company Facts

Organization Name

AltaCoda

Date Founded

2025

Company Location

United States

Company Website

bench47.com

Categories and Features

Categories and Features

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