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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

AIMS, or Asset Information Management System, stands out as the leading CMMS solution favored by healthcare professionals globally. Developed with input from 30 healthcare experts across 14 hospitals in Michigan, AIMS has been supporting both multi-facility healthcare organizations and standalone hospitals since its inception in 1984. This scalable, web-based software offers a range of essential components, optional features, and interfacing capabilities designed to address both current and future operational requirements. Users can conveniently manage all facets of their maintenance operations remotely, with internet access available at any time. AIMS is not only straightforward to learn and utilize, but it is also sufficiently robust to handle the intricate demands of extensive multi-facility networks. Whether you prefer a solution hosted on your own server or one of Phoenix's Cloud Solutions, AIMS is adaptable to fulfill your specific requirements. Overall, AIMS combines versatility and user-friendliness, making it an ideal choice for healthcare facilities striving for efficient asset management.

Description

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

CoLab
Codestral Mamba
CrewAI
Cynerio
Databricks
Guardrails AI
JavaScript
JupyterLab
LangChain
Le Chat
LlamaIndex
Mathstral
Ministral 3B
Ministral 8B
Mistral 7B
Mistral AI
Mixtral 8x7B
OpenAI
OpenTelemetry
Pixtral Large

Integrations

CoLab
Codestral Mamba
CrewAI
Cynerio
Databricks
Guardrails AI
JavaScript
JupyterLab
LangChain
Le Chat
LlamaIndex
Mathstral
Ministral 3B
Ministral 8B
Mistral 7B
Mistral AI
Mixtral 8x7B
OpenAI
OpenTelemetry
Pixtral Large

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Phoenix Data Systems

Founded

1984

Country

United States

Website

www.goaims.com

Vendor Details

Company Name

Arize AI

Country

United States

Website

docs.arize.com/phoenix

Product Features

Medical Inventory

Barcode Scanning
Expiration Date Management
Purchasing
Reorder Management
Supply Management
Usage Tracking
Vendor Management

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