Featured case study

Building an AI Search Agent Across Multiple Travel-Advisor Hotel Portals

Travel advisors often have access to several wholesale, advisor-only hotel suppliers — and little time to search all of them by hand. USTech.Ninja built Net Rate Radar, an AI agent that searches an advisor’s own authenticated supplier portals so they don’t have to.

IndustryTravel / Hospitality

EngagementNet Rate Radar — AI Hotel Search Agent

ClientIndependent Travel Advisor

Capabilities

AI & AutomationBrowser AutomationTravel TechnologyCustom Development

Challenge

Comparing wholesale hotel pricing across several advisor-only portals meant repeating the same search manually in every supplier’s site.

Implementation

An AI browser-automation agent was taught to navigate and search each supplier’s existing authenticated portal.

Outcome

The advisor runs one search; the agent repeats it across supplier portals and returns a consistent comparison.

Client / Industry

An independent travel advisor with access to multiple wholesale and advisor-only hotel suppliers, including TBO, Bedsonline, Room-Res, Expedia TAAP, RateHawk, and Prices Agencies.

Challenge

An advisor’s competitive advantage comes from access to more inventory and pricing channels than a typical consumer booking site. But comparing those channels can mean logging into several separate portals, running essentially the same search repeatedly, opening multiple tabs, and comparing room categories, net pricing, and supplier inventory by hand — then checking whether the “special” industry rate actually beats consumer pricing. The operational cost of manually searching every channel can make the advantage inefficient to use.

Approach

Instead of building another hotel inventory database, USTech.Ninja taught an AI agent how to use the advisor’s existing supplier portals directly — avoiding the need for every supplier to offer a clean public API.

Built an AI skill/browser-automation workflow capable of navigating and searching multiple authenticated travel-advisor portals.
Trained the agent on portal-specific navigation and search procedures for each supplier.
Extracted results into a consistent comparison format across suppliers.
Added consumer-side pricing as a sanity-check comparison.
Kept the human advisor in control of the final booking decision.

Implementation

The agent requires authentication handling, portal-specific navigation knowledge, supplier-specific search procedures, and structured output — not simple prompt engineering. Authenticated browser access was successfully established with supplier systems including RateHawk and Bedsonline, and the advisor performed live searches to iteratively refine the output, including improved visual presentation and clearer room-category comparison.

What Changed

Before: comparing wholesale hotel options meant manually repeating the same search across several separate supplier portals.

After: the advisor runs one search; the agent searches the authenticated supplier portals and returns a consistent comparison, with consumer pricing checked as a sanity test.

Verified Outcome

By late September 2026, the advisor reported performing a live search with the system operating in a format he personally liked, with continued incremental tuning expected. Live, authenticated searches were successfully run against multiple supplier portals during testing.

We do not claim autonomous final booking across every supplier, universal supplier support, guaranteed lowest pricing, or that this workflow uses traditional API integrations — it operates through browser automation against the advisor’s own authenticated portals.

Strategic Takeaway

Not every valuable business system has an API. Modern automation can combine browser control, domain knowledge, and AI to automate repetitive workflows inside the software businesses already use — augmenting the advisor’s private supplier relationships rather than replacing them.