Voice Analytics

The Cloud9 workflow collects, structures and delivers metadata for firms to accurately capture voice information to provide a robust view of market intelligence for the front office.

Benefits of the C9 Trader Platform

Standardized Structure and Delivery
All the data around the call and transcription of trader voice conversations are structured and delivered, real-time, in a standard .json format, allowing firms a comprehensive view for the purposes of compliance, surveillance and analysis.
Unique Speaker Identification
For the first time, customers of Cloud9 can discern conversations on a user-by-user basis, for both the near and far end counterparties.
More Data About Your Calls
The Cloud9 platform is purpose built to capture more information than ever about a conversation and deliver that real-time and store for historical analytics.
Deploy On Premises
Deployment capabilities on the cloud or in-house so sensitive and proprietary information does not leave the premises.

Enhance Your Big Data Experience with
Cloud9 Data Collection and Delivery

Realtime Event Notification

Firms can write to an API that will start to send relevant call information at the initiation of a voice conversation. This real-time stream of information can not only be sent to relevant middle and back office repositories but also used as a trigger to release relevant information back to a user’s desktop.

Sales Efficacy and Predictive Analytics

Structured metadata can be quickly queried for reports on sales efficacy, trade reconstruction and combined with other unique data sets for revenue generating predictive analytics.

Biometric Identification

Utilizes voice recognition technology to authenticate users before and during calls conducted on the platform.


Cloud9’s built-in recording, secure storage options, and enhanced transcription services allow firms to be fully compliant with all retention, recording, and surveillance requirements of MiFID II. We also exceed the requirements of other major regulatory initiatives like Dodd-Frank.

Hover over a user to identify which customers they interact with. Join that with trade information to correlate sales conversations with actual notional trades.

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