Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

Write a Review

Description

AgentBench serves as a comprehensive evaluation framework tailored to measure the effectiveness and performance of autonomous AI agents. It features a uniform set of benchmarks designed to assess various dimensions of an agent's behavior, including their proficiency in task-solving, decision-making, adaptability, and interactions with simulated environments. By conducting evaluations on tasks spanning multiple domains, AgentBench aids developers in pinpointing both the strengths and limitations in the agents' performance, particularly regarding their planning, reasoning, and capacity to learn from feedback. This framework provides valuable insights into an agent's capability to navigate intricate scenarios that mirror real-world challenges, making it beneficial for both academic research and practical applications. Ultimately, AgentBench plays a crucial role in facilitating the ongoing enhancement of autonomous agents, ensuring they achieve the required standards of reliability and efficiency prior to their deployment in broader contexts. This iterative assessment process not only fosters innovation but also builds trust in the performance of these autonomous systems.

Description

Bench47 empowers teams and their AI-driven agents with a unified, clear memory and skill set. Key decisions, incidents, strategies, and discoveries are documented in an easy-to-read Markdown format, allowing for inspection, editing, and exportation by users. Various MCP-compatible agents, including Claude Code, Codex, and Cursor, can share the same knowledge base and contribute new insights. This system enables teams to maintain up-to-date skills across different machines, connect knowledge with code modifications, and seamlessly transfer tasks between agents while retaining context. Additionally, agents can initiate workflows for both development and production through alerts, webhooks, and scheduled tasks. The flexibility of Bench47 allows it to operate on chosen machines, adhering to the access levels established by the team. Furthermore, it can be utilized as a hosted service, self-hosted within the client's infrastructure, or deployed exclusively in the customer's cloud environment, ensuring adaptability to various organizational needs. This versatility makes Bench47 an invaluable tool for enhancing collaboration and efficiency in AI-driven projects.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code No 
Codex CLI No 
Gemini CLI No 
GitHub No 
Linear No 
Model Context Protocol (MCP) No 
Sentry No 

Integrations

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

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$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 Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

AgentBench

Country

China

Website

llmbench.ai/agent

Vendor Details

Company Name

AltaCoda

Founded

2025

Country

United States

Website

bench47.com

Product Features

Alternatives

GLM-4.7 Reviews

GLM-4.7

Z.ai

Alternatives

Factory Reviews

Factory

Factory.ai
BenchLLM Reviews

BenchLLM

5.0 out of 5 stars
Antigravity CLI Reviews

Antigravity CLI

Google
5.0 out of 5 stars