The Systems of Support: How Mosaic AI Aims to Solve B2B Complexity

TEL AVIV, Israel & TORONTO – June 09, 2026

In a technology landscape increasingly shaped by artificial intelligence, a peculiar paradox has emerged: the same AI that accelerates product development is creating unprecedented complexity for the customer support teams tasked with keeping pace. It’s a challenge that generic AI tools, designed for simpler consumer-facing interactions, have largely failed to meet. Stepping into this gap is Mosaic AI, which today announced the launch of its enterprise AI platform, a purpose-built system designed to navigate the intricate world of Business-to-Business (B2B) support.

The launch marks a significant strategic pivot for the company, formerly known as Ask-AI. Moving beyond its initial offering of a general enterprise assistant, Mosaic AI now presents a comprehensive platform aimed at B2B organizations wrestling with large product portfolios, fragmented data systems, and highly technical customer needs. By connecting disparate data sources and enriching them with organizational context, the company promises not just faster answers, but a fundamental reduction in operational costs and a direct line from customer data to measurable business outcomes.

A Market Built on Complexity

The fundamental challenge for AI in the B2B sector is that no two problems are exactly alike. Unlike B2C support, which often deals with high volumes of repeatable questions, B2B inquiries are frequently unique, technical, and layered with context. A single support ticket can depend on a customer’s specific product version, unique configuration, account history, and past engineering escalations. This information is rarely stored in one place; it's scattered across CRMs like Salesforce, helpdesks like Zendesk, engineering logs in Jira, and conversations in Slack.

This data fragmentation is the Achilles' heel of many enterprise AI solutions, including those from major platform players. While powerful within their own ecosystems, they often struggle to see the whole picture. “Existing AI tools struggle to handle the complexity that comes with supporting B2B enterprises," said Alon Talmor, founder and CEO of Mosaic AI. “They lack the product, customer and organizational context to deliver the right information to customers and the internal teams that support them. As AI enables developers to ship much faster, that gap is only getting wider.”

This widening gap creates a critical need for a new kind of infrastructure—one that doesn't just answer questions, but understands the intricate web of relationships between products, customers, and internal processes. Industry analysts note that while many organizations are eager to adopt AI, they are often stymied by the reality that their existing systems and siloed data are not AI-ready. This is the complex system that Mosaic AI purports to untangle.

Weaving a Coherent Digital Mosaic

True to its name, Mosaic AI’s platform is designed to piece together fragmented information into a coherent, actionable whole. The company's approach is built on a three-part model: connect, enrich, and power. It begins by integrating with a customer's entire tech stack—connecting to hundreds of potential tools to ingest data from every corner of the business. This goes far beyond the capabilities of tools confined to a single vendor's domain.

Once connected, the platform's core technology works to enrich this raw data. It builds a dynamic knowledge graph that understands the unique context of the business: its product catalog, its customer hierarchy, its internal team structures, and its specific operational processes. This contextual layer is what allows the AI to move from simple keyword matching to genuine understanding.

This enriched data then powers a suite of ready-made “agentic AI products” that can be deployed across customer-facing workflows. These agents can autonomously deflect routine cases, surface precise answers and account history for human agents, and recommend the next best action in a complex troubleshooting scenario. Critically, the system also works proactively, identifying gaps in the company's knowledge base and flagging potential customer or product risks before they escalate into major issues. The platform starts where the pain is most acute and measurable—Customer Support—with plans to extend its capabilities into Customer Success and Sales.

The ROI Revolution in Enterprise Support

For any enterprise technology, the ultimate measure of success is its return on investment. Mosaic AI is leaning heavily on this metric, positioning its platform not as a technology project, but as a business solution with a clear and rapid path to value. The company claims its platform can reduce operational costs by up to 30 percent and offers a deployment timeline that is radically accelerated compared to industry norms.

Customers are reportedly seeing tangible results in weeks, not quarters. AssetWorks, a provider of software for asset-intensive industries, saw a 39% reduction in the cost to resolve a support case within the first 90 days. “We scaled our Mosaic deployment from production pilot to full adoption across multiple business units in under 10 weeks,” said Greg Richards, President and GM of AssetWorks.

Similarly, Point of Rental, a rental and inventory management software company, reported a 44% reduction in case resolution time and saw its customer satisfaction (CSAT) score climb to 92%. Brooke Ryan, SVP of Global Customer Experience at the company, highlighted the platform's forward-looking potential. “Not only did it cover what we needed out of the box, the vision was there,” she stated. “There’s so much more that we can do with the platform in the future that I’m very excited about.”

This rapid ROI is underscored by Mosaic AI's own business momentum. The company reports having tripled its revenue and average annual contract value over the past year, signing nearly $1 million in new ARR in the last 30 days alone. This suggests the message of measurable, fast-turnaround results is resonating with enterprise leaders.

A Founder's Vision: From Assistant to Platform

The company’s strategic direction is deeply rooted in the experience of its founder. Alon Talmor, an AI PhD, is a second-time founder who previously sold a startup to Salesforce.com and subsequently served as Chief Data Scientist of Salesforce Data.com. This experience gave him a front-row seat to the power—and limitations—of a large-scale enterprise platform. It’s a perspective that clearly informed the pivot from a simple AI assistant to a comprehensive underlying platform.

This evolution from a tool to a system reflects a maturing understanding of the enterprise AI market. The initial hype around generative AI focused on conversational chatbots, but the deeper, more strategic value lies in building the connective tissue that makes an entire organization smarter. The $20 million in funding raised by Mosaic AI to date serves as a strong vote of confidence from investors in this platform-centric vision.

By moving from Ask-AI to Mosaic AI, the company is making a clear statement: the future of enterprise AI isn’t about building a single, all-knowing oracle. It's about architecting an intelligent system that can navigate the inherent complexity of modern business, connecting disparate knowledge to solve real-world problems and empower the people on the front lines.