Accurate by Design: AI-Connected Data Eliminates Search Errors
In Brief
AI-powered product search reduces time from minutes to seconds
Engineers and procurement teams at a global electronics manufacturer rely on fast access to product specifications, compliance data, and technical documentation. The company produces connectors and cable assemblies and operates across North America, Europe, and Asia. However, its large catalog required users to navigate multiple pages and manually compare results, slowing workflows and increasing the risk of errors.
Resource Data built an AI-to-data integration that connects AI tools to structured product information that is always up to date. Users can describe what they need in plain language and search, compare, and evaluate products in a single query, reducing research time from minutes to seconds.
Key Takeaways
From browsing to asking: faster product discovery with AI
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Product research time drops from minutes to seconds
Research that required extended navigation can now be completed almost instantly using natural language and desired formats.
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Users no longer rely on page-by-page navigation
Users can request product information in plain language, removing the need to navigate multiple pages or apply filters.
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Decisions happen faster with side-by-side comparison
Users can evaluate multiple options at once and request results in a specific format, making it easier to compare specifications and identify the right component.
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More reliable results reduce manual verification
Source-based, grounded responses limit incorrect outputs and reduce the need to double-check information.
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Product data becomes easier to access for external users
The same approach can be implemented to support customer-facing tools, making it easier for external engineers and buyers to find what they need.
The Challenge
Multi-step product search slowed engineers down
The manufacturer manages a catalog of thousands of electronic interconnect components including connectors, cable assemblies, and related systems. Every component has detailed specifications, compliance requirements, and documentation. Engineers and procurement teams needed to compare products, verify compatibility, and review technical details across multiple pages.
Engineers searching for connectors with specific attributes—such as type, gender, and number of positions—often needed to apply multiple filters and navigate several pages to find compatible options. Because this information lived in web pages, AI tools attempting to automate retrieval relied on scraping, which often returned incomplete or inconsistent results, increasing errors and requiring manual verification, slowing workflows and reducing confidence in AI-generated results.
The Solution
One reliable source of product data, accessible through AI
Resource Data built a Model Context Protocol (MCP) server that gives AI direct access to product specifications, documentation, and compliance data. The MCP server connects this data to AI tools, allowing users to request product information in plain language and receive accurate results pulled directly from source data, with access to the latest product information.
This created a single, reliable way to access product data across systems and made it easier to use AI for search, comparison, and evaluation. The initial proof of concept was delivered in one week, showing a fast path to deployment and a clear way to extend the solution across additional products and platforms.
Features
Making product data easier to access, use, and evaluate
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Plain language query interface for easier search
Users describe product requirements in plain language instead of navigating filters or category pages. The system returns relevant products, reducing time spent searching and the need to navigate multiple pages.
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Structured data retrieval for improved accuracy and consistency
Product information is returned in clearly defined fields, so results are consistent and based on source data. This reduces ambiguity and avoids incomplete or incorrect responses.
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Real-time data access up-to-date information
The solution retrieves product data directly from source systems at the time of the request. Users see the latest specifications, documentation, and compliance details.
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Multilingual interaction for global accessibility
Users can submit queries and receive results in multiple languages. This makes product information easier to access across geographic regions.
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Parallel query processing for faster comparisons
The system can run multiple searches at the same time, allowing users to compare several products side by side instead of running separate searches for each product.
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Flexible response formatting for different user needs
The system can return product information in different formats depending on the request, such as structured data, summaries, or side-by-side comparisons. This allows users to get the level of detail they need.
What used to take 20 minutes of navigating the site can now be done in seconds.
- Daniel Dubiel, Engineer, Resource Data
Results
Trusted product insights with near-zero AI errors
Users can now retrieve product specifications, documentation, and comparisons in seconds using natural language, replacing workflows that previously took 20 or more minutes of manual navigation. Users can also evaluate multiple products at once, reducing the time needed to compare options and make decisions.
Because the system returns precise, source-based information, it reduces incorrect responses and limits the need for manual verification. The same approach can extend to customer-facing tools, allowing engineers and buyers to request product information directly instead of navigating the company’s website, making it easier to find the right components without learning the manufacturer’s catalog structure.
What's Next
Scaling AI-powered data access across platforms
The solution is being expanded to support a broader product catalog and additional brand websites within the organization’s portfolio. Future efforts focus on refining the user experience, increasing adoption, and integrating customer-facing tools such as website search experiences and product selection interfaces.
As the solution expands, it will enable consistent AI-driven access across sites, supporting faster decisions and a unified user experience.
Case Study FAQs
Engineers and procurement teams struggled with a massive product catalog that required navigating multiple pages and applying complex filters to compare components. Because traditional AI tools relied on web scraping, they often returned incomplete or inconsistent data, leading to a lack of confidence in AI-generated results and forcing manual verification.
Instead of relying on scraped data, Resource Data built an MCP server that gives AI tools direct access to structured source data. This ensures the AI pulls from up-to-date specifications, compliance documentation, and technical details in real-time, virtually eliminating the “hallucinations” or errors common in standard AI searches.
The solution includes a plain-language query interface, real-time data access, and parallel query processing. This allows users to search, compare multiple products side-by-side, and receive results in flexible formats (like structured data or summaries) in any language, making the catalog globally accessible.
The implementation reduced research and product comparison time from an average of 20 minutes down to just a few seconds. By replacing manual page-by-page navigation with natural language queries, engineers can identify the right components almost instantly.
Yes. While this initial phase focused on internal workflows, the same MCP-based architecture can be integrated into public websites. This allows external buyers and engineers to find the exact parts they need using simple questions, without needing to understand the manufacturer’s specific catalog structure.