Teleskope – a cybersecurity startup – recently announced it launched a data protection platform that automates data security, privacy, and compliance at scale, helping organizations comply with regulations like GDPR and CCPA, and reduce the manual and operation burden on security, data, and engineering teams. And the company raised $2.2 million in pre-seed funding led by Lerer Hippeau.
Different from other Data Security Posture Management (DSPM) approaches that result in alert fatigue due to valuable time wasted on false positives, Teleskope utilizes artificial intelligence (AI) – specifically Large Language Models (LLM) – to provide actionable insights with greater accuracy. And the company’s data protection software integrates with existing workflows and developer pipelines, allowing engineers to automate security at the source.
By minimizing false positives and providing context around the data, Teleskope helps organizations focus on genuine vulnerabilities – streamlining their security and privacy operations while significantly reducing risk – particularly important at a time when data breaches and privacy incidents are increasing along with fines for improper data handling.
Launched by two former Airbnb security engineers, Elizabeth Nammour and Julie Trias, Teleskope brings a combination of expertise and fresh perspective to the issue of data security. Before starting Teleskope, the co-founders wrestled with the problem of constant manual assessments and reviews that become obsolete as soon as they’re completed. They recognized the need to replace point-in-time spreadsheets and ad hoc scripts with automation that provides a real-time and always up-to-date data security and privacy posture.
Teleskope’s advanced contextual analysis goes beyond traditional data classification for discerning whether data like an address is actually considered Personally Identifiable Information (PII) when associated with a customer’s home address, or when that address is associated with a public landmark or business address and does not have PII implications. And Teleskope utilizes state-of-the-art large language models, which are continuously fine-tuned and optimized for speed and cost, to identify the data subject associated with the data like a customer, employee, or differentiate between customer types, such as doctors and patients.
The company brought together a team of industry experts as advisors, including Doug Dooley, chief operating officer of the application security company Data Theorem, Abby Kearns, former chief technology officer of Puppet, Sathia Narayanan Mahadevan, head of privacy and assurance at Reddit and Nancy Wang, director of engineering for data protection and security at Amazon Web Services.
Teleskope can monitor cloud data stores and third-party vendors within minutes, providing a comprehensive inventory of assets, including hidden ones, and identifying their security and compliance risks. Its advanced classification engine, powered by a large language model and rules engine, can adapt to each unique data store – identifying sensitive data and providing actionable context on who the data is about. And the Teleskope AI model is trained to learn each unique customer implementation to increase its accuracy further.
The company supports structured and unstructured data stores across popular cloud platforms like AWS, GCP, and Snowflake, as well as third-party SaaS, identifying over 100 data types, including personal, payment, healthcare, and sensitive data. Teleskope can automatically enforce compliance requirements or remediate security vulnerabilities directly at the source or enables developers to implement any custom security or privacy protocols through open APIs. And Teleskope can scale to petabytes of data with predictable cost-effective pricing.
KEY QUOTES:
“With the increasing use of generative AI causing even more data leaks, privacy is becoming even more of a concern. And we know from our work at Airbnb that data classification products don’t work the way they should – too many false-positives, a lack of contextual understanding, and an inability to scale and integrate causes alert fatigue and puts critical data at risk. “Now more than ever, privacy and security concerns are escalating due to the widespread use of generative AI. Teleskope helps customers automate security and privacy saving them valuable time, while simultaneously reducing risk. From detection to remediation, Teleskope can be easily integrated in developer pipelines to help prevent and resolve data security vulnerabilities.”
— Elizabeth Nammour, co-founder and CEO of Teleskope
“The cyber field needs more diversity of thought, as well as leaders building with hands-on experience as engineers and operators. Teleskope’s founders’ extensive experience as security-focused software engineers, including for the military, brings fresh perspective, as they’ve lived through the pain points they’re solving. Plus, their developer-centric approach and strategic use of AI for best-in-class contextual classification position them to build the industry-leading platform to protect and secure customer information.”
— Graham Brown, managing partner at Lerer Hippeau
“What sets Teleskope apart as a data security and protection solution is their unique ability to detect and remediate security vulnerabilities before they enter production, by enforcing protection policies at every stage of the software development lifecycle (SDLC). Teleskope enables engineers to take on a much bigger role when it comes to protecting sensitive business and customer data.”
— Nancy Wang, director of engineering for data protection and security at Amazon Web Services
“Teleskope has been a game-changer for us in streamlining our compliance and security processes. We’ve found Teleskope to be incredibly accurate in classifying data, and it has helped us uncover customer PII and sensitive information that was previously overlooked through manual labeling. By integrating Teleskope’s findings into our existing workflows through APIs, our engineers were able to automate compliance tasks, saving them valuable hours of operational overhead, and allowing them to focus on their core responsibilities. As an early-stage company with a complex on-the-ground business, this is invaluable to us in the time of limited capital and resources.”
— Nick Cobb, former Uber (senior infrastructure manager) and now vice president of engineering and product at Kyte, a service for cars delivered on demand
