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Description

Enhance machine learning model performance by capturing real-time training metrics and issuing alerts for any detected anomalies. To minimize both time and expenses associated with the training of ML models, the training processes can be automatically halted upon reaching the desired accuracy. Furthermore, continuous monitoring and profiling of system resource usage can trigger alerts when bottlenecks arise, leading to better resource management. The Amazon SageMaker Debugger significantly cuts down troubleshooting time during training, reducing it from days to mere minutes by automatically identifying and notifying users about common training issues, such as excessively large or small gradient values. Users can access alerts through Amazon SageMaker Studio or set them up via Amazon CloudWatch. Moreover, the SageMaker Debugger SDK further enhances model monitoring by allowing for the automatic detection of novel categories of model-specific errors, including issues related to data sampling, hyperparameter settings, and out-of-range values. This comprehensive approach not only streamlines the training process but also ensures that models are optimized for efficiency and accuracy.

Description

Runheed is an error-tracking platform designed for developers utilizing AI coding agents in the creation and upkeep of production applications. It offers SDKs for Node.js/TypeScript and Python that log exceptions, which Runheed organizes by fingerprint, providing detailed insights such as stack traces, breadcrumbs, request information, environment specifics, release data, and optional context from the agent session. With the remote Model Context Protocol (MCP) server, compatible agents can effectively search through error groups, analyze comprehensive context and trends, assess project health, and document fixes for errors. If an error that has been resolved appears again, it reopens along with its previous resolution note for reference. Setup frameworks are available for popular applications like Express, Next.js, Fastify, FastAPI, Django, and Flask, while an HTTP endpoint is available for error reports from other programming languages. Users receive email alerts whenever new types of errors are identified. The Solo plan is priced at $29 per workspace each month and comes with a trial period of 7 days, allowing users to explore its features before committing. This makes Runheed an appealing choice for developers looking to streamline their error management process.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

No images available

Integrations

AWS Lambda Yes 
Amazon CloudWatch Yes 
Amazon SageMaker Yes 
Amazon SageMaker Studio Yes 
Amazon SageMaker Unified Studio Yes 
Change Healthcare Data & Analytics Yes 
Claude No 
Claude Code No 
Claude Desktop No 
Cline No 
Codex CLI No 
Cursor No 
Keras Yes 
MXNet Yes 
Model Context Protocol (MCP) No 
PyTorch Yes 
TensorFlow Yes 
Visual Studio Code No 
Zed No 

Integrations

AWS Lambda No 
Amazon CloudWatch No 
Amazon SageMaker No 
Amazon SageMaker Studio No 
Amazon SageMaker Unified Studio No 
Change Healthcare Data & Analytics No 
Claude Yes 
Claude Code Yes 
Claude Desktop Yes 
Cline Yes 
Codex CLI Yes 
Cursor Yes 
Keras No 
MXNet No 
Model Context Protocol (MCP) Yes 
PyTorch No 
TensorFlow No 
Visual Studio Code Yes 
Zed Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$29/month
Solo is $29 per workspace per month, or $290 annually, and includes 50,000 events per month, 3 projects, and 30-day history. Pro is $79/month or $790/year; Scale is $199/month or $1,990/year. All plans include the MCP server and unlimited agent keys; events above the monthly limit are rejected rather than billed. The 7-day trial requires a payment card; the first charge is due at the end of the trial unless canceled before then.
Free Trial Yes 
Free Version No 

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 No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/debugger/

Vendor Details

Company Name

Great Work LLC

Founded

2025

Country

United States

Website

runheed.com

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Alternatives

No Alternatives