Leverate has selected WNSTN AI to expand the capabilities of its AI Investments Assistant, adding broker-focused conversational intelligence, trader engagement tools, and client-intent analytics to the platform. The partnership aims to help brokers extract commercial insights from trader interactions while keeping clients inside the trading environment. The announcement reflects a broader industry shift as brokers, trading platforms, and fintech providers increasingly look toward AI systems that can improve retention, personalization, and operational decision-making beyond traditional chatbot functionality.
Leverate Partners With WNSTN To Add Intelligence Layer
Leverate introduced an AI assistant embedded directly within its trading platform, allowing traders to ask questions in natural language while giving brokers visibility into user interests, behavior patterns, and engagement activity. WNSTN's technology will serve as an additional intelligence layer designed to help brokers extract commercial insights from trader interactions.
The company said its AI Investments Assistant already allows traders to explore market information through natural-language interactions directly inside the trading platform. The addition of WNSTN is intended to expand that functionality by providing deeper personalization, engagement analytics, and broker-specific customization tools.
Ran Strauss, CEO of Leverate, said: "AI is fast becoming a core layer of the modern brokerage experience, but it has to be practical, embedded, and measurable. When we launched the AI Investments Assistant, our goal was not simply to add a chatbot to a trading platform. It was to give brokers a practical AI layer that improves the trader experience and produces meaningful business intelligence. WNSTN stood out as the clear choice for advancing our AI vision. Its broker-ready platform combines intelligent personalization, powerful engagement capabilities, and real-time business insights, enabling brokers to build stronger client relationships, increase platform stickiness, and drive measurable growth."
WNSTN Technology Converts Trader Interactions Into Broker Intelligence
A central element of the partnership is the ability to convert trader interactions into operational intelligence for brokerages. According to the companies, broker clients will gain visibility into trader interests, commonly asked questions, instrument searches, and engagement patterns.
That information can potentially help sales teams, retention departments, dealing desks, and marketing teams better understand client behavior. Rather than relying solely on traditional trading metrics such as deposits, volumes, positions, and profitability, brokers could gain additional context around what clients are researching, what markets attract attention, and what topics generate engagement.
For brokers operating in highly competitive retail trading markets, understanding client intent before a trade is placed may become increasingly valuable. For example, if large numbers of traders are asking questions about gold, crude oil, artificial intelligence stocks, or cryptocurrencies, brokers may be able to identify emerging areas of interest before activity appears in execution data.
Embedded AI Assistant Keeps Traders Inside Platform Environment
One of the recurring challenges for brokers is that traders frequently leave the trading platform to search for market information elsewhere. Research, educational content, technical analysis, and market commentary often take place across websites, social media platforms, video channels, messaging applications, and third-party analytics services. Every time a trader leaves the platform, brokers lose visibility into that activity.
The companies argue that embedded AI assistants can help address that issue by allowing traders to obtain market explanations, technical analysis, charts, and contextual information without interrupting their workflow. The concept of platform stickiness has become an increasingly important metric across the brokerage sector. Technology providers now compete not only on execution, charting, and market access but also on how much time users spend within the platform ecosystem.
WNSTN's technology is specifically designed to support that objective by integrating directly into the trading environment rather than redirecting users to external resources.
White-Label Deployment Allows Broker-Specific Customization
Another major component of the partnership involves white-label deployment and broker-specific customization. Leverate has traditionally focused on providing white-label technology to brokers, allowing firms to operate under their own brands while using Leverate's infrastructure. The AI initiative follows the same model.
Brokers will be able to deploy the assistant under their own branding while tailoring the experience to match business objectives, client profiles, and regional requirements.
Roy Michaeli, Co-Founder and CEO of WNSTN, said: "We are proud that Leverate selected WNSTN after a competitive review and that our technology will enhance an AI solution already positioned at the center of the broker platform. The winning approach in this market is to understand clients' needs and offer trusted cooperation in building AI together. Brokers need AI that is embedded in the trading journey, tailored to their brand, multilingual, compliant, and connected to commercial outcomes such as engagement, retention, and client understanding."
The focus on customization reflects growing recognition that brokerages operate across different jurisdictions, client demographics, regulatory environments, and product offerings. As a result, a standardized AI experience may not be sufficient for firms seeking differentiation.
Compliance Infrastructure Built For Regulated Environments
While artificial intelligence adoption continues to accelerate across financial services, regulatory concerns remain a significant consideration. Financial institutions face growing pressure to ensure AI systems operate within governance frameworks that address transparency, oversight, recordkeeping, risk controls, and client protection requirements.
Both companies highlighted compliance infrastructure as a key component of the deployment. WNSTN said its technology incorporates governance controls, guardrails, and oversight mechanisms designed for regulated environments.
That focus reflects a broader trend in financial technology where institutions increasingly prioritize controlled AI deployments over unrestricted consumer-style implementations. Brokerages, in particular, must balance automation and personalization with regulatory obligations relating to client communications, suitability, marketing, and disclosure requirements.
Frequently Asked Questions
Q: What capabilities does WNSTN AI add to Leverate's AI Investments Assistant?
A: WNSTN AI adds broker-focused conversational intelligence, trader engagement tools, and client-intent analytics to Leverate's AI Investments Assistant. The technology provides brokers with visibility into trader interests, commonly asked questions, instrument searches, and engagement patterns, helping sales teams, retention departments, dealing desks, and marketing teams better understand client behavior.
Q: How does the white-label deployment model work for brokers using this AI assistant?
A: Brokers will be able to deploy the AI assistant under their own branding while tailoring the experience to match business objectives, client profiles, and regional requirements. Leverate has traditionally focused on providing white-label technology to brokers, allowing firms to operate under their own brands while using Leverate's infrastructure, and the AI initiative follows the same model.
Q: What compliance infrastructure does WNSTN provide for regulated financial environments?
A: WNSTN's technology incorporates governance controls, guardrails, and oversight mechanisms designed for regulated environments. The compliance infrastructure addresses transparency, oversight, recordkeeping, risk controls, and client protection requirements that financial institutions face, helping brokerages balance automation and personalization with regulatory obligations relating to client communications, suitability, marketing, and disclosure requirements.
