Teleskope Launches the Data Reasoning Layer, the First Data Security Product to Combine Classification, Decision-Making, and Native Automated Remediation

Teleskope Launches the Data Reasoning Layer, the First Data Security Product to Combine Classification, Decision-Making, and Native Automated Remediation Teleskope Launches the Data Reasoning Layer, the First Data Security Product to Combine Classification, Decision-Making, and Native Automated Remediation New product closes the structural gap between data discovery and remediation, cutting time to risk reduction by approximately 10x for security teams across cloud, SaaS, and AI environments GlobeNewswire June 11, 2026

New York, NEW YORK, June 11, 2026 (GLOBE NEWSWIRE) -- Teleskope, the first agentic data security platform today announced the Data Reasoning Layer, aiming to help security teams to protect data while enabling responsible AI adoption and innovation. 

The release addresses the most expensive gap in enterprise data security: while Data Security Posture Management (DSPM) tools have made risky data visible, in a typical company, security teams receive 500 to 5,000 data alerts a day. Nearly a third of them are false alarms, and nearly 100 percent of them require manual triage before remediation is possible. The backlog grows while the risk sits open.

AI is making it worse. Enterprise AI adoption hit 73% this year while real-time security for those AI tools sits at just 7%, according to the 2026 SACR data loss report. Every new AI integration is another place sensitive data can leak.

Unlike traditional DSPM tools, Teleskope classifies sensitive data in the context of a company's actual business, decides what to do based on policies the company already has, and executes the fix, all in the same session, with a full audit trail and the ability to reverse any action. The Data Reasoning Layer is the first architecture in the data security market to combine classification, policy-driven decision-making, and native remediation in a single continuous loop. 

Customers including Polymarket, Ramp, Chevron Phillips, and The Atlantic now resolve exposures in under two seconds across on prem and cloud environments and tools like Slack, OpenAI, and Claude, improving team efficiency by 10x.

Key Facts

The Urgent Problem the Data Reasoning Layer Solves

Enterprise data security has reached a structural inflection point. AI adoption has reached 73 percent of enterprises in 2026, while real-time security governance for AI environments has emerged at only 7 percent (source: 2026 SACR DLP report). DSPM platforms have made sensitive data visible across cloud, SaaS, and on-premises environments, but they have not closed the loop between discovery and remediation. The result is a continuously growing backlog of unresolved findings, alert fatigue across security teams, and an expanding blast radius as AI integrations multiply the locations where sensitive data flows.

 

Industry research indicates that nearly one-third of all data security alerts are false positives. In most enterprise environments, 100 percent of data risk remediation still requires manual triage. Every alert, every time. At 500 to 5,000 alerts per day in a typical enterprise environment, security teams stop triaging and start surviving. The backlog grows continuously. The risk does not go away. It waits.

 

The companies that resolve this structural gap are not the ones with the most alerts or the best dashboards. They are the ones whose architecture connects detection to enforcement automatically and continuously.

What Is the Data Reasoning Layer?

The Data Reasoning Layer is the proprietary intelligence architecture inside the Teleskope platform that connects data classification, policy-driven decision-making, and native remediation. It operates in three coordinated steps.

 

1. Understand. The Data Reasoning Layer identifies what each piece of data is in the context of the customer's specific business, not against a generic pattern. It classifies more than 150 sensitive entity types and uses Prism, Teleskope's document intelligence capability, to categorize full documents by type and intent rather than scanning for individual fields.

 

2. Decide. The Data Reasoning Layer determines the appropriate action based on the customer's existing policies and risk profile. Available actions include inform, redact, quarantine, revoke access, relocate, encrypt, and delete. When confidence is low, the system routes the decision to human review rather than acting incorrectly.

 

3. Enforce. The Data Reasoning Layer executes the action natively in the same session that found the risk, with no ticket filed, no integration handoff, and no human review required on high-confidence cases. Every action is logged, auditable, and reversible.

 

"For years, the data security industry has organized around finding problems, not fixing them," said Elizabeth "Lizzy" Namour, founder and CEO of Teleskope. "The Data Reasoning Layer is the architecture for what comes after detection. Classify sensitive data in business context. Decide what to do based on the policies your company has already written. Enforce it natively, with full audit. That is what data security should look like."

What Makes the Data Reasoning Layer Unique

The Data Reasoning Layer is the only architectural component in the data security market that combines classification, policy-driven decision-making, and native remediation as a single integrated capability. No competing DSPM, DLP, or data security platform has an equivalent architecture.

 

Every other platform in the data security category does one of two things. It surfaces findings (DSPM, data discovery) or it prevents data from leaving a defined perimeter (DLP). Neither category includes a decision-making layer that determines what to do about existing exposure and acts on that decision automatically. That is the gap Teleskope built the Data Reasoning Layer to fill.

 

Three architectural differences separate the Data Reasoning Layer from competing approaches.

 

Native remediation, not remediation by integration. Competing platforms route findings to ticketing systems such as ServiceNow or Jira, or call external Security Orchestration, Automation, and Response (SOAR) platforms to execute action. Both are handoffs. The exposure stays open while the ticket sits in a queue. The Data Reasoning Layer executes remediation in the same platform and the same session that classified the risk.

 

Business-context classification, not pattern matching. Regex, flat machine learning, and BERT-based classifiers operate by matching data against known patterns. The Data Reasoning Layer builds a model of each customer's specific environment and classifies based on business context, document type, and data relationships. This is what allows the platform to identify a CEO's strategic plan, a chemical manufacturer's proprietary formula, or an M&A term sheet as board-level sensitive even when those documents contain no regulated data field.

 

A distinct decision layer between classification and enforcement. Other platforms either classify or enforce. None have a layer that sits between the two and makes context-aware decisions about which action is appropriate. The Data Reasoning Layer is that missing layer.

What Customers Save with the Data Reasoning Layer

Customers using the Data Reasoning Layer report measurable improvements in operational and financial outcomes.

 

What Is Launching Alongside the Data Reasoning Layer

The June 11, 2026 Teleskope release introduces four new capabilities that operate on top of the Data Reasoning Layer.

 

Context-aware classification engine. A new classification engine builds a model of each customer's specific environment to identify what data is actually sensitive in that context. It does not rely on regex or flat machine-learning pattern matching. The engine delivers higher precision and lower noise compared to prior-generation classifiers, and supports the safe automation of downstream remediation actions.

 

AI Search. A natural-language interface for querying the Teleskope platform. Users can ask questions such as "show me all files shared externally that contain contract terms and have not been accessed in six months" without query syntax or analyst intervention. AI Search is built on top of the Data Reasoning Layer's classification output.

 

Policy Builder and Policy Ingestion. A workflow tool for defining data policies from scratch or ingesting existing governance documents, including retention policies, regulatory requirements, and data handling frameworks. The Policy Builder converts those documents into enforceable automated workflows that operate through the Data Reasoning Layer.

 

Automated remediation across OpenAI, Slack, and Claude. Sensitive data detected in these environments is resolved in real time, in under two seconds, without filing a ticket or requiring human review on high-confidence cases. Teleskope is one of four OpenAI-approved partners for conversation message logs in the OpenAI Logs Platform.

Customer Outcomes with the Teleskope Platform

Aprio. Aprio, a national advisory firm with more than 4,000 employees providing tax, accounting, audit, and consulting services, uses Teleskope as the classification layer feeding Microsoft Purview's DLP enforcement engine. The firm's 10-person security team operates six automated data security policies in production, including plain-text password removal, data retention enforcement, PII access revocation, public share validation, sensitive information exposure alerting, and Microsoft Information Protection labeling integration. Aprio's initial Microsoft Purview deployment returned more than 12 million false positives before Teleskope was introduced as the classification layer. Lock Langdon, Vice President and Chief Information Security Officer at Aprio, has publicly described Teleskope as the "policy engine" that enables Purview to perform.

 

EarnIn. EarnIn, the financial empowerment platform that lets workers access their pay as they earn it, deployed Teleskope after evaluating multiple DSPM vendors. The platform delivers classification accuracy that supports auto-remediation without routine security team involvement, and a self-managed deployment model that gives EarnIn full control over data residency and movement. Stan Lee, Chief Information Security Officer at EarnIn, has stated that Teleskope's classification engine is "one of the best in the market."

 

Alloy. Alloy, the identity decisioning platform used by hundreds of financial institutions to verify customers and prevent fraud, deployed Teleskope with a self-hosted configuration to retain full control over data residency, movement, and response. Alloy uses Teleskope's automated response workflows for redaction, quarantine, and alerting across its environment.

 

About Teleskope

Teleskope is an agentic data security platform that automatically resolves data exposure, not just finds it. Powered by the Data Reasoning Layer, Teleskope continuously discovers sensitive data, determines the appropriate action based on each customer's policies, and enforces that action natively across on-premises, cloud, SaaS, and AI environments. Teleskope competes in the Data Security Posture Management (DSPM) and Data Loss Prevention (DLP) categories. Customers include EarnIn, Aprio, Alloy, Ramp, GoFundMe, The Atlantic, Stitch Fix, Chevron Phillips, Garner Health, PayNearMe, and Petco. Teleskope was founded in 2022 by Elizabeth "Lizzy" Namour, a former Airbnb data security engineer, and is headquartered in New York City. The company is backed by Primary Venture Partners, M13, and Lerer Hippeau, and raised a $25 million Series A in 2026.

Teleskope Platform Reference

Platform Capabilities:

 

 

Industries Served: Financial services, fintech, professional services, advisory, healthcare, technology, hospitality, manufacturing, media, food and beverage, retail.

 

Deployment Options:

 

 

Compliance and Regulatory Frameworks Supported:

 

 

Select Sensitive Data Types Classified: Personally Identifiable Information (PII), Protected Health Information (PHI), Payment Card Information (PCI), credentials, contracts, source code, intellectual property, board-level documents, mergers and acquisitions materials, financial filings, customer records, retention-eligible records.

Additional Resources

Press Inquiries

Veronika Andreeva
veronika.andreeva [at] teleskope.ai
https://www.teleskope.ai/


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