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What is UnitusTI Therapy Intelligence?

UnitusTI provides an extensive array of functionalities, comprising tailor-made data collection methods, integrated billing solutions, instant charting and reporting for billing and insurance needs, staff management features, scheduling options, program implementation support, and optional integrated curricula, all offered at competitive rates. The Aquarium Digital Iconic Music Example further enriches the experience by allowing users to engage with the interface through interactive touch icons accompanied by music, which promotes active involvement with vibrant visuals such as fish and seaweed. In addition, ASCEND© (Advanced Systematic Curriculum for Early Neural Development) is a carefully crafted tool for BCBA professionals that encompasses a diverse set of skills crucial for effectively aiding children on the Autism Spectrum. This resource proves particularly advantageous for busy ABA practitioners who appreciate ready-to-use program templates but still wish to implement their chosen data collection techniques. By delivering these valuable resources and tools, UnitusTI not only streamlines effective treatment methodologies but also significantly boosts the overall productivity of ABA practices, ensuring that professionals can focus more on their clients. The combination of these elements positions UnitusTI as a leader in enhancing both client care and operational efficiency in the field.

What is Aquarium?

Aquarium's cutting-edge embedding technology adeptly identifies critical performance issues in your model while linking you to the necessary data for resolution. By leveraging neural network embeddings, you can reap the rewards of advanced analytics without the headaches of infrastructure management or troubleshooting embedding models. This platform allows you to seamlessly uncover the most urgent patterns of failure within your datasets. Furthermore, it offers insights into the nuanced long tail of edge cases, helping you determine which challenges to prioritize first. You can sift through large volumes of unlabeled data to identify atypical scenarios with ease. The incorporation of few-shot learning technology enables the swift initiation of new classes with minimal examples. The larger your dataset grows, the more substantial the value we can deliver. Aquarium is crafted to effectively scale with datasets comprising hundreds of millions of data points. Moreover, we provide dedicated solutions engineering resources, routine customer success meetings, and comprehensive user training to help our clients fully leverage our offerings. For organizations with privacy concerns, we also feature an anonymous mode, ensuring that you can utilize Aquarium without compromising sensitive information, thereby placing a strong emphasis on security. In conclusion, with Aquarium, you can significantly boost your model's performance while safeguarding the integrity of your data, ultimately fostering a more efficient and secure analytical environment.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

$100 per month

Pricing Information

$1,250 per month
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Mundo Pato

Date Founded

2010

Company Location

United States

Company Website

www.mundopato.com

Company Facts

Organization Name

Aquarium

Company Website

www.aquariumlearning.com

Categories and Features

Occupational Therapy

Assessment Management
Care Plan Management
Patient Records
Patient Registration
Patient Scheduling
Practice Management
Progress Tracking

Categories and Features

AI Observability

Not specified

Embedding Models

Not specified

Machine Learning

Not specified

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