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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.

What is AgentBench?

AgentBench is a dedicated evaluation platform designed to assess the performance and capabilities of autonomous AI agents. It offers a comprehensive set of benchmarks that examine various aspects of an agent's behavior, such as problem-solving abilities, decision-making strategies, adaptability, and interaction with simulated environments. Through the evaluation of agents across a range of tasks and scenarios, AgentBench allows developers to identify both the strengths and weaknesses in their agents' performance, including skills in planning, reasoning, and adapting in response to feedback. This framework not only provides critical insights into an agent's capacity to tackle complex situations that mirror real-world challenges but also serves as a valuable resource for both academic research and practical uses. Moreover, AgentBench significantly contributes to the ongoing improvement of autonomous agents, ensuring that they meet high standards of reliability and efficiency before being widely implemented, which ultimately fosters the progress of AI technology. As a result, the use of AgentBench can lead to more robust and capable AI systems that are better equipped to handle intricate tasks in diverse environments.

Media

Media

Integrations Supported

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

Integrations Supported

API Availability

Has API

API Availability

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

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

AltaCoda

Date Founded

2025

Company Location

United States

Company Website

bench47.com

Company Facts

Organization Name

AgentBench

Company Location

China

Company Website

llmbench.ai/agent

Categories and Features

Categories and Features

LLM Evaluation

Not specified

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