All data on the Symbl.ai platform is encrypted and all connections are secured using 2048 bit AES encryption. Over the wire, data is encrypted using RSA 2048 bit keys. At rest, data is encrypted using AES-256. Please visit our security page to learn more.

We store transcripts, insights, and metadata about the conversation, which is persisted at Symbl.ai’s end. All data access is logged and audited regularly. Logs are maintained for a minimum of 3 months and encrypted at rest. By default, we do not store audio recordings. In cases where storing is required, audio recordings are securely stored and encrypted at rest using 2048 bit RSA. Please visit our security page to learn more.

Symbl.ai collects and processes only such Personal Data as is adequate, relevant, and limited in scope to the requirement and for a length of time that is necessary for the stated purposes of its use. Please visit our privacy policy to learn more.

Insights are generated with the help of various machine learning and deep learning models working together to draw inferences based on the context of the conversation. Our out of the box insights don’t generally need any upfront training data. You can create custom intents over our contextual understanding engine.

If your solution requires some other type of insight detection that does not fall under the out-of-the-box insights we provide, you might need to start with training data. However, our customers tell us the Symbl.ai contextual understanding engine generally provides better results than what they were able to generate with training data.

We are hosted in the public cloud and have the flexibility to scale as you grow.

If your requirements are not met by Symbl.ai’s Public Cloud, you can opt-in for our private cloud deployment option. Please contact us to discuss.

Symbl.ai’s async Audio & async Video APIs can detect and separate unique speakers in a single stream of audio & video data.

Symbl.ai provides developers reusable and customizable UI Components that can be widely divided into two types: Pre-built Summary UI and Symbl.ai React Elements.

Developers who want to start exploring Symbl.ai should review the Getting Started steps in our documentation, try our public collection in Postman, and sign up for the Symbl.ai platform (it’s free) which includes a simple UI developers and product builders can use to access an API playground, create custom trackers, view API logs, manage their usage & billing and more.

You can use our Text API for transcripts generated by your own ASR. We also work with a variety of ASR partners if you are looking for a customized solution.

Evaluating the results from various speech recognition vendors is a challenging task. To help make this process easier, we put together a utility, open-sourced on GitHub that will enable you to evaluate speech recognition vendors and results faster and goes beyond just Word Error Rate (WER) which you might see elsewhere. The utility automatically performs the pre-processing or normalization of the text to remove further manual efforts for the evaluation process.

Symbl.ai has best in class speech-to-text available across all channels. If a company claims a precise answer for out of the box speech recognition accuracy, here are a few considerations to keep in mind: 1. The way companies measure accuracy differs; 2. Custom models outperform standard, so the question to ask is what level of accuracy do we need to be successful; 3. The key differentiator when it comes to transcription is the presence of an intelligence layer. Symbl.ai provides a proven intelligence layer that transforms transcription into key insights and next best actions.

We charge based on the minutes processed through the Voice or Video API or the number of words processed via the text interface. See our pricing page for details.