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What is Symbl?

Symbl is an API platform aimed at enabling developers and companies to effortlessly integrate conversational intelligence into a variety of communication channels. Our comprehensive set of APIs utilizes advanced machine learning algorithms that can analyze any form of conversation data to derive meaningful insights contextually, encompassing several domains and platforms including voice, email, chat, and social media, all without the need for initial training data, wake words, or specialized classifiers. By democratizing access to conversational technology, Symbl facilitates large-scale collaboration, empowering organizations to implement our targeted workplace productivity API, which assists brands in optimizing crucial workflows for knowledge workers while enhancing customer interactions. Whether you are a seasoned developer or a novice looking to harness employee collaboration within your business, our API provides customizable options designed to address your unique use cases, ensuring it effectively satisfies your requirements. In addition, Symbl is dedicated to transforming the dynamics of team communication and collaboration by offering cutting-edge tools that enable businesses to thrive in a rapidly evolving landscape. Ultimately, our goal is to support organizations in unlocking their full potential through improved interaction and engagement strategies.

What is Speech2Structure?

During patient care, it has been observed that physicians often spend approximately two-thirds of their time on documentation rather than on conducting examinations or engaging in meaningful conversations with patients. To address this issue and allow doctors to focus more on patient interactions, Averbis is creating Speech2Structure, a cutting-edge software solution that captures documentation in real-time using voice input while organizing it instantly. This innovative system is skilled at recognizing and addressing various linguistic subtleties, such as negations and diverse diagnostic categories, as it processes the incoming information. Furthermore, it efficiently converts pathological laboratory results and microbiological findings into applicable diagnoses, thereby simplifying the documentation workflow. In addition, the medications mentioned during patient consultations can provide valuable insights into possible diagnoses, which enhances the overall clinical understanding. Ultimately, by reducing the documentation burden, this tool aims to improve the quality of patient care delivered by physicians.

Media

Media

Integrations Supported

AWS Marketplace
Confluence
Gmail
Google Calendar
Google Docs
HubSpot CRM
HubSpot Customer Platform
Jira
Microsoft Outlook
Salesforce
Slack
Trello
Twilio Flex
Unremot

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Symbl.ai

Date Founded

2018

Company Location

United States

Company Website

symbl.ai

Company Facts

Organization Name

Averbis

Date Founded

2007

Company Location

Germany

Company Website

averbis.com/health-discovery/speech2structure/

Categories and Features

AI Voice Agents

Not specified

Conversational AI

Code-free Development
For Developers
Intent Recognition
Multi-Languages
Reusable Components
Speech Recognition

Speech Recognition

Automatic Transcription
Multi-Languages
Speech-to-Text Analysis
Voice Recognition

Categories and Features

Conversational AI

Sentiment Analysis

Data Extraction

Not specified

Decision Support

Not specified

Deep Learning

Not specified

Medical Transcription

Not specified

Speech Analytics

Automatic Transcription
Sentiment Analysis

Speech Recognition

Audio Capture
Automatic Transcription
Speech-to-Text Analysis

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