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Elisity Launches Open CLI for Customer-Built AI Agents on Its Microsegmentation Platform

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New command-line interface lets security teams run their own AI agents on Elisity’s microsegmentation platform, as 77% more customer organizations used Elisity Intelligence in June than in April.

SAN JOSE, Calif., Aug. 5, 2026 /PRNewswire/ — Elisity, the identity-based microsegmentation company, today launched the Elisity CLI, an open command-line interface that lets security and network teams run their own AI agents against the Elisity platform. Teams can script discovery, manage Zero Trust least-privilege access policies, and pull posture reports, then point their own AI orchestrators at the platform to keep checking that segmentation controls still hold.

Plenty of security vendors now ship AI agents that customers can’t see inside. Elisity does the reverse. Security teams point whatever agent they already run at an open interface, and built-in guardrails stop that agent from acting on a guess or making a change nobody approved. Because every action runs on identity through Elisity IdentityGraph™, an agent works from many data points Elisity has already ingested and correlated, so it can tell what a device really is instead of guessing from an IP address. Teams automate only what they want, and a person signs off before anything changes.

Elisity built a command-line interface rather than a Model Context Protocol server by design. An MCP server is a standing, privileged connection into the platform, and it widens what an agent can reach by default. That pattern has drawn steady scrutiny from security researchers, and it asks a security team to run one more always-on service inside the environment it is trying to protect. A CLI inverts the model. It runs only when it is called, it runs under the caller’s own credentials and permissions, and every state-changing command stops for human approval. The concern is not theoretical. In July 2025, researchers disclosed CVE-2025-6514, rated 9.6 out of 10, in mcp-remote, a connector downloaded more than 437,000 times: a malicious MCP server could run operating system commands on the machine that connected to it, the first documented remote code execution against an MCP client.

Elisity built the CLI for teams that want to run the platform programmatically and stand up their own agentic workflows:

466 commands covering the Elisity Cloud Control Center API, plus reporting on Zero Trust posture scores, per-site metrics, and traffic and threat vectors.An operating guide and command glossary for AI agents like Claude or ChatGPT, so an agent runs a real command instead of inventing one.Human approval on every state-changing command, and a separate confirmation for deletes.Output in JSON, table, YAML, or CSV, with profiles for production, staging, and lab.

“Most of the industry is asking customers to trust a black-box AI agent with their network. We’re doing the opposite. Our CLI hands customers the keys, so they point their own AI agents at the platform and automate exactly what they choose, with a human approving anything that changes state. And because it all runs on identity through Elisity IdentityGraph, an agent knows what a device actually is, not just a guess off an IP address. That’s the difference between automation you can audit and automation you just hope works,” said James Winebrenner, CEO, Elisity.

“Every segmentation program eventually reaches the same question: Are these policies still enforcing the outcomes we designed them to achieve? Historically, the answer came from periodic audits and the assumption that nothing had changed. With the Elisity CLI, we can continuously validate our Zero Trust least-privilege policies against realistic adversary techniques. If a policy drifts or no longer prevents lateral movement, we know within minutes instead of discovering it during an incident. In healthcare, operational resilience matters because downtime is not just an IT problem. Automating these tests gives us continuous assurance that our controls are performing the way we expect them to. Security isn’t about believing your controls still work. It’s about proving they do,” said Jason Elrod, Chief Information Security Officer, MultiCare Health System.

Customer use of Elisity Intelligence, the platform’s optional AI, has climbed steadily through 2026. The number of customer organizations using it grew 77% between April and June, and the heaviest use is in policy work, device lookups, and the overview dashboard, where the daily work happens. Nothing about it runs on its own. Administrators decide what’s on, and every recommendation waits for a person to approve it before anything changes. Customers running it already include GSK, Main Line Health, and MultiCare Health System, this year’s CSO Award winner.

Elisity offers the CLI to customers today. Teams that want to wire up their own agents can request access through their Elisity account team. Elisity’s AI capabilities data sheet explains how Elisity Intelligence works, and you can request a demo to see the platform.

About Elisity

Elisity (www.elisity.com) helps healthcare systems, manufacturers, and critical infrastructure operators stop lateral movement through identity-based microsegmentation. Elisity discovers every user, workload, and device, then enforces Zero Trust least-privilege access policies on existing network infrastructure, with no agents, new hardware, or network redesign. Elisity protects organizations including GSK, Main Line Health, MultiCare Health System, and Shaw Industries. For more information, visit www.elisity.com

Media Contact

Danielle Ostrovsky
Hi-Touch PR
Ostrovsky@Hi-TouchPR.com

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RLX Technology to Report Second Quarter 2026 Financial Results on August 14, 2026

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– Earnings Call Scheduled for 8:00 a.m. ET on August 14, 2026 –

SHENZHEN, China, Aug. 5, 2026 /PRNewswire/ — RLX Technology Inc. (“RLX Technology” or the “Company”) (NYSE: RLX), a leading global branded e-vapor company, today announced that it will report its unaudited financial results for the second quarter ended June 30, 2026, before the U.S. markets open on Friday, August 14, 2026.

The Company’s management will host an earnings conference call at 8:00 AM U.S. Eastern Time on August 14, 2026 (8:00 PM Beijing/Hong Kong Time on August 14, 2026).

Dial-in details for the earnings conference call are as follows:

United States (toll free):

+1-888-317-6003

International:

+1-412-317-6061

Hong Kong, China:

+852-5808-1995

Mainland China:

400-120-6115

Participant Code (English line):

7036236

Participant Code (Chinese simultaneous interpretation line):

7119184

Participants may choose between the English and Chinese simultaneous interpretation options above when joining the conference call. Please note that the Chinese simultaneous interpretation option is in listen-only mode. Participants should dial-in 10 minutes before the scheduled start time and ask to be connected to the call for “RLX Technology Inc.” using the appropriate English or Chinese Participant Code above.

Additionally, a live and archived webcast of the conference call will be available on the Company’s investor relations website at https://ir.relxtech.com.

A replay of the conference call will be accessible approximately two hours after the conclusion of the call until August 21, 2026, by dialing the following telephone numbers:

United States:

+1-855-669-9658

International:

+1-412-317-0088

Replay Access Code (English line):

9911837

Replay Access Code (Chinese line):

6469534

About RLX Technology Inc.

RLX Technology Inc. (NYSE: RLX) is a leading global branded e-vapor company. The Company leverages its strong in-house technology, and product development capabilities and in-depth insights into adult smokers’ needs to develop superior e-vapor products.

For more information, please visit https://ir.relxtech.com.

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Section 2® Launches as First AML Company to Target Bad Actors and Their Criminal Networks

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Financial Crime Intelligence Company Debuts Hybrid Threat Central™ Platform

SIOUX FALLS, S.D., Aug. 5, 2026 /PRNewswire/ — Section 2, Inc., today announced its launch as an AML and financial crime intelligence company along with Hybrid Threat Central™ (HTC), a platform built to identify the criminal networks behind financial crime rather than the individual transactions they generate.

An important aspect of Section 2’s approach is a focus on false negatives — the criminal actors and transactions that slip through undetected, in contrast to the false positives that dominate industry conversation. A single missed detection can cost an institution millions of dollars once regulatory penalties and remediation are factored in, with remediation costs alone running roughly 12 times the amount of the original fine.

Despite massive AML spending, confiscation and recovery rates remain below 1% globally. The reason is the overwhelming number of alerts, and manual teams’ inability to stay ahead of the volume. A modern transaction monitoring system at a regional institution generates alerts at a rate that outpaces analyst capacity by approximately 50:1.

To solve the problem, Section 2 is introducing Hybrid Threat Central™ (HTC), a platform built to identify the criminal networks behind financial crime rather than the individual transactions they generate. It is built on Hybrid Threat Finance™ (HTF™), a patent-pending methodology developed by founder and CEO Debra Geister over more than a decade of work in AML and fraud detection.

“Every AML officer knows the number, even if they’ve learned not to say it out loud: somewhere around 1% of illicit financial flows get caught by the global anti-money-laundering apparatus,” Geister said. “Banks spend billions of dollars a year on transaction monitoring, and the detection rate hasn’t meaningfully moved in 20 years. The problem isn’t effort. It’s that the industry has been monitoring transactions when it should be identifying actors.”

From transactions to actors

Traditional transaction monitoring systems generate alert volumes that outpace analyst capacity, according to Section 2, producing false-positive rates estimated at 85% to 95% while an estimated 98% of financial crime goes undetected. The firm estimates the financial industry spends more than $200 billion annually on compliance, investing largely in manual reviews that cannot keep up with the massive number of alerts.

Section 2 said the core flaw is a unit-of-analysis problem: transactions are cheap for criminal networks to generate and abandon, while the underlying business model and network entity behind them are far more durable and far harder for criminals to change. The company uncovers the bad actors and their networks.

HTF addresses that by extending the traditional three-stage AML model — placement, layering and integration — to five stages, adding revenue generation, where criminal proceeds originate, and operational sustainment, where threat actors reinvest to fund ongoing activity.

The platform

Hybrid Threat Central™ is powered by three components, according to the company:

TENet™ (Threat Entity Network), a continuously updated library of financial crime targeting packages built on the HTF™ methodology and covering all five stages of the financial crime lifecycle, delivered via API or SFTP into a bank’s existing transaction monitoring system.TRACC™ (Threat Risk Assessment Command Center), which overlays threat intelligence with an institution’s own risk profile to identify exposure and prioritize which TENet™ packages to deploy.HTF Assist™, an analyst investigation layer that produces investigation-ready case candidates structured for suspicious activity report (SAR) filing.

The platform is built on Google Cloud infrastructure, with Vertex AI powering its machine learning layer. Section 2 designed HTC to be an intelligence layer, not a replacement system — it works alongside an institution’s existing transaction monitoring infrastructure rather than requiring a rip-and-replace. In one deployment alongside an existing transaction monitoring system, Section 2 found that TENet™ reduced false positives from 94% to 18%.

Addressing national priorities and the effectiveness rule

The Section 2 platform is designed to help institutions respond to the Financial Crimes Enforcement Network’s (FinCEN) eight government-wide AML/CFT priorities: corruption, cybercrime, terrorist financing, fraud, transnational criminal organizations, drug trafficking, human trafficking and smuggling, and proliferation financing.

The company also pointed to the “effectiveness rule,” a standard under the U.S. Federal Sentencing Guidelines and the Department of Justice’s Evaluation of Corporate Compliance Programs. Under that standard, a written compliance program is not sufficient on its own; institutions must show their programs are actively working, adequately funded and capable of preventing, detecting and correcting violations to receive legal and sentencing credit. Section 2 said actor-level attribution gives institutions a clearer way to demonstrate the outcomes regulators now expect, rather than alert volume alone.

Built on a decade of investigative practice

Section 2’s Special Investigations Unit (SIU), a team of career intelligence, law enforcement and financial services compliance professionals, serves as the human-in-the-loop oversight behind the platform, the company said. The unit keeps Section 2’s threat actor and typology databases current, produces the whitepapers and case studies that back the platform’s findings, and reviews every classification before it reaches a customer, so that outputs remain sourced, defensible and examiner-ready. The SIU also provides specialized investigation support directly to partners on complex cases requiring deep-dive research.

About Section 2

Section 2, Inc. is a financial crime intelligence company founded by Debra Geister, a three-decade veteran of the AML and fraud detection industry. Geister began her career building foundational detection systems at LexisNexis in the years following the USA PATRIOT Act and later oversaw global compliance functions for major financial institutions before founding Section 2. She has worked as a practitioner in all facets of AML — CIP/IDV, KYC, sanctions, and AML operations. The result is the company’s Hybrid Threat Finance™ methodology and Hybrid Threat Central™ platform which are designed to shift financial crime detection from isolated transactions to the criminal networks and business models behind them.

More information is available at section2.com.

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As AI Demand Outpaces Skills, Datarails Brings Forward Deployed Financial Engineers Into the CFO’s Office

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The Datarails AI Transformation Package joins wave of forward deployed engineering (FDE) initiatives at Microsoft and OpenAI

NEW YORK, Aug. 5, 2026 /PRNewswire/ — Datarails, the AI-native financial operating system for the CFO’s Office, today launched the AI Transformation Package, a service that embeds a dedicated Forward Deployed Financial Engineer (FDFE) inside a customer’s finance team to build custom AI workflows directly in their Datarails FinanceOS environment.

The launch follows a wave of forward deployed engineering (FDE) initiatives at companies like Microsoft and OpenAI, as tech giants invest billions to deploy technical talent inside customer organizations. Datarails is bringing that model to a function it says those efforts have largely skipped: the CFO’s Office.

The move is backed by recent research which found that nearly one in three finance jobs (31%) now requires AI skills, up from one in four a year ago – outpacing teams’ ability to hire or build against that demand. Moreover, independent research from the Financial Education & Research Foundation (FERF) found that only 15% of organizations consider themselves well or fully prepared to support advanced analytics and AI initiatives.

“You cannot parachute a generalist engineer into finance and expect trustworthy output, which is why we have seen vast demand in the market for finance engineers embedded inside of finance teams,” said Didi Gurfinkel, CEO and co-founder of Datarails. “Our FDFEs have decades of experience on finance teams, which they now bring to bear as they work directly with customers to build bespoke solutions on top of the FinanceOS that underpins their AI efforts. This ensures that all outputs – from Claude, Gemini or ChatGPT – are accurate, governed, repeatable and auditable.”

The service is designed for teams with limited bandwidth but ambitious automation goals; organizations that want to fast-track AI adoption without requiring a lengthy and expensive IT project; and finance leaders who want to increase team output without adding headcount.

Each engagement pairs a customer with an FDFE for 25 hours per quarter across a four-phase model – Discover, Build, Deploy, Evolve – designed to reach a live production workflow within the first quarter.

The AI Transformation Package is now available to existing Datarails customers: https://lp.datarails.com/ai-implementation-services.

About Datarails
Datarails is the AI finance operating system for teams across FP&A, cash management, and month-end close. Uniting financial and operational data, FinanceOS is the trusted data layer for finance teams ensuring every AI output is accurate, governed, repeatable and auditable. It lets users stay within Excel and a web-based platform, transforming the CFO’s office into the home of business insights.

Media Contact
datarails@concrete.media

 

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