HawkSearch
Turning Product Discovery into Revenue

Dr. Ari Kahn, President and CEO

Seventy-two percent of online purchases use onsite search. When that experience fails, customers stall early, abandon sessions and take revenue elsewhere. Many search technology companies treat that moment as the finish line. HawkSearch, an AI‑powered search, product discovery and recommendations platform, treats it as the starting point.

“We don’t build a website so we can have excellent search. We build a website so we can sell more products,” says Dr. Ari Kahn, President and CEO.

That distinction shapes how it operates. Commerce teams are not measured on features. They are measured by growth. HawkSearch organizes its platform around a model called eCommerce360, based on a simple reality: online revenue depends on three connected forces: attracting the right buyers, converting them efficiently and increasing the value of each transaction. Improving one without the others doesn’t maximize the impact.

How does the eCommerce360 model connect traffic acquisition, conversion efficiency and order value?

On the traffic side, HawkSearch offers SEO- and answer-engine-optimized landing pages that surface products and solutions earlier in the discovery cycle, aligning content with how buyers and AI systems ask questions. Once visitors arrive, AI-powered site search blends keyword logic, semantic understanding and conversational interaction. Buyers describe needs in natural language. Search asks clarifying questions, refines intent and narrows results, reducing friction at the point where most journeys fail.

Order value is shaped while decisions remain open. Recommendation algorithms analyze behavior, context and historical patterns to surface complementary products, bundles or accessories at moments when buyers are still evaluating options. The result is a larger basket built through relevance rather than interruption.

Together, these capabilities shift search from a retrieval tool into an interactive sales agent that guides discovery, clarifies intent and assembles complete solutions instead of returning disconnected results.

Buying behavior is evolving. Customers often arrive with incomplete language or solution-level problems rather than product names. B2B environments add complexity through technical specifications, compatibility constraints and long-tail inventory. Purchases increasingly originate from automated replenishment systems and emerging shopping agents, as well as people. HawkSearch designs discovery to serve both human buyers and automated agents, ensuring consistent outcomes regardless of who or what initiates the search.

Its AI foundation predates current market hype. Dr. Kahn holds a PhD in artificial intelligence, dating back to 1996 and HawkSearch embedded AI capabilities, such as natural language processing and behavioral analytics, into its platform in 2019. That architecture enabled expansion into vector search, generative AI search and AI agents without re-platforming. In 2025, HawkSearch released six AI capabilities shaped directly by customer collaboration.

Performance reflects that focus. HawkSearch reports net revenue retention of 117 percent, with $2.60 in expansion revenue for every $1 in new customer revenue. A global provider of computer equipment provides a scale example, with HawkSearch reporting more than $500 million in annual revenue influenced by its e-commerce platform. Its hybrid search model generated over $40 million in sales across more than 3.5 million sessions during December 2025. In B2B distribution, one of the largest electrical distributors in North America operates hundreds of sites under centralized oversight, while one of the largest national hardware store chains powers thousands of locations across its brands, relying on real-time inventory reflected directly in search results.

How will HawkSearch AI agents automate insight generation and merchandising decision support?

The next milestone is leveraging HawkSearch AI agents to automate more and more of the front-end and back-end experiences. HawkSearch introduces a centralized data lake that captures activity across the whole commerce experience and connects external systems such as ERP order history and Google Analytics. Merchandisers access this combined data through AI interfaces, including model-context and agent-to-agent access, shifting analysis from dashboard construction to direct, question-driven insight.

“AI without analytics or information is not intelligent. It’s just dumb, fast workflow and it makes huge mistakes,” says Dr. Kahn.

HawkSearch approaches automation deliberately. AI agents operate alongside merchandising teams rather than acting independently. Teams retain control over revenue-impacting decisions while AI accelerates insight, testing and prioritization. In practice, HawkSearch functions less as a search product and more as a revenue system that is designed to reduce friction, clarify intent and translate discovery into measurable growth.