When Julie Trias and Elizabeth Nammour worked together at Airbnb on the company’s data team, they had to manage data spread across various sources, and this increasing proliferation led to challenges in ensuring data security. The founders’ own frustration with the multitude of existing data protection options motivated them to start a company and create the automated data protection tool they wanted.
On Tuesday, this startup, Teleskope, announced a $5 million seed investment.
“We tested many different tools to help us understand, protect, delete and redact data on Airbnb, but what we realized was that there was no tool that could help developers to do it automatically,” Trias told TechCrunch.
That’s not to say there weren’t solutions, but those that did exist, like data classification tools, generated many false positives and had scaling issues. “There were no tools that could help you move from detection to actual remediation, meaning deleting the data, isolating the data, or taking any sort of action on the data.” The solution developed by Teleskope allows customers to connect to their various data sources, identify sensitive data in various data stores in an automated manner and isolate or delete them if necessary.
They currently have a few different use cases: “We now sell primarily to data teams, not just product developers, but data governance engineers, who want to clean up their entire datasets in their data warehouse, or who want to clean a dataset before using it for training models, or they have multiple datasets and need to remove a particular user’s data for compliance purposes,” a she declared.
The solution relies on what Trias calls “a model pipeline” with different models coming into play depending on the type of data. “For example, we trained a very efficient model to classify natural language data, such as conversational file types. We have trained a model that works very well with structured tabular format types. We trained a model that can classify sensitive data into a code base file or log file,” she said.
Trias says that despite having the experience and pedigree to build a product like this, they weren’t well versed in the world of venture capital and how to pitch their project when they started the company – and the teams Female founders face a greater challenge with investors in general. “I think the hardest part was that when we started making venture capital calls, we didn’t know how to do it. We didn’t even know what a design partner was. We were pre-produced, first of all, and we didn’t know all the VC lingo. So we were completely unprepared when we took our first meetings with venture capital firms,” she said.
They refined their pitch over time and were able to find investors who understood them and their vision. The seed funding was led by Primary Venture Partners with participation from Lerer Hippeau and Plug and Play Ventures as well as Essence VC, which led the company’s pre-seed round.
techcrunch
