Tessian is a London based company which has raised 13 million dollars to build a product which solves the problem of enterprise email security using machine learning. The round was led by Balderton capital and Accel partners. Previous investors Amadeus Capital Partners, Crane, LocalGlobe, Winton Ventures and Walking Ventures also participated.
The company was formerly known as CheckRecipient before it rebranded to Tessian. Company plans to use the newly raised funds to ramp up its marketing and sales efforts and also to invest in product development.
The company aims to solve a simple yet really big problem of sending emails to the wrong recipients which causes data loss and might even lead to sensitive information falling in wrong hands causing lot of security headaches for the IT and security teams.
According to the company, UK's information commissioner's office receives more security incident reports about misaddressed emails than any other type of security issue which makes it a big enough problem to attack and with the new privacy rules coming over all across the world this might even lead to large fines and penalties for companies.
“With the recent report from the ICO that misaddressed emails are now the number one data security incident reported to them and GDPR now in full swing, companies should make addressing this risk a top security priority,” said Tessian CEO and co-founder Tim Sadler in a statement. “It’s human nature to fear scary things like hackers or malware, but we often don’t think twice about the dangers behind something as familiar and ingrained as sending an email. In reality that’s where an overwhelming threat lies.”
The company has built a machine intelligence technology which analyses corporate email network to find common patterns and detect any anomalies which might occur and if it detects something unusual in an email which someone is trying to send then it will put up a red flag for user to check the contents of the email before sending it.
It offers four different product solutions for email security using machine learning :
1. Custom email filters which allows customers to implement customised client security requirements on email.
2. Misaddressed emails which prevents highly sensitive emails from being accidentally sent to the wrong people.
3. Data loss prevention which prevents sensitive emails to be sent to unauthorised or personal accounts causing data loss to the company.
4. Ethical walls and Insider List compliance which allows companies to build ethical walls and project boundaries between groups of email users.