AI RAG Chatbot: Verifiable AI for Technical Support Teams
In Brief
AI Technology That Accelerates Technical Support
Same Sky is an electronic component manufacturer with a growing catalog of highly technical products. This growth has increased the volume and complexity of customer questions. Customer support engineers spend significant time searching for thousands of datasheets and fragmented documentation, slowing response times and risking inconsistent answers.
Resource Data built an Azure OpenAI–powered RAG chatbot that retrieves and consolidates accurate product information in seconds. The chatbot supplies ~90% of the content needed for complex responses and enables faster, more consistent customer support.
Key Takeaways
AI-Assisted Support That Elevates Human Expertise
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AI RAG Chatbot Changes How Support Work Begins
The AI powered Retrieval-Augmented Generation (RAG) chatbot replaces manual document searches with a prepared starting point for each inquiry. Support engineers begin responses with relevant information already assembled.
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Reducing Research to Improve Answer Quality
By supplying most of the information needed for complex responses, the chatbot reduces repetitive research. Engineers spend more time validating answers and applying expertise rather than locating information.
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Clearer Answers with Fewer Follow-Ups
Support responses are more complete and consistent across cases. Customers receive clearer answers the first time, reducing the need for clarification and repeat exchanges and reinforcing trust in Same Sky’s technical guidance
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Transparency Enables Confident Use of AI in Support
Visible sources, such as linked datasheets and product documentation, allow engineers to verify every response. This transparency builds confidence in AI-assisted support while keeping human judgment in control
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A Central Knowledge System That Scales Across Teams
The chatbot creates a single source of product information that multiple teams can use. Expanding access does not require rebuilding documentation or workflows, making it easy to support new teams as needs grow.
Our Client
Same Sky
Same Sky is an electronic component manufacturer offering a wide range of Interconnect, Audio, Thermal Management, Motion, and Sensor solutions, such as connectors, audio components, cooling devices, and sensors. Their diverse and growing product portfolio serves customers across multiple industries. Engineers and customers rely on Same Sky’s extensive technical documentation, including detailed datasheets and specifications.
Resource Data has partnered with Same Sky since 2011, supporting their ongoing use of technology to improve both internal processes and customer-facing systems.
Challenges
Manual Research Slowed Technical Support Responses
As Same Sky’s product catalog expanded, customer support requests became increasingly detailed and technical. Customers routinely asked questions about specifications, performance characteristics, and proper application of electronic components, often requiring engineers to reference multiple documents to provide a complete answer. While accurate information existed, it was spread across thousands of datasheets, internal records, blog posts, and prior support exchanges, making it time-consuming to locate and verify.
Support engineers were responsible for answering these inquiries while maintaining consistency and accuracy across responses. As request volume increased, engineers spent more time searching for information and less time resolving customer questions. Without a more efficient way to find authoritative answers, response times slowed and the risk of inconsistent or incomplete support grew, putting customer satisfaction and Same Sky’s reputation at risk.
Our Approach
Designing for Accuracy, Transparency, and Adoption
Resource Data worked closely with Same Sky to understand how customer questions are researched and answered. Together, the teams identified common types of questions and the trusted documents used to answer them, including datasheets, technical documentation, and prior support materials.
The approach started by organizing and standardizing existing documentation to create a consistent, reliable starting point for answers. A small proof of concept was then created—a limited trial used to test the approach with real support questions. Feedback from Same Sky’s support team helped shape how information was presented and reviewed, allowing the team to confirm the approach before expanding it further.
The Solution
AI RAG Chatbot Built for Precision
An AI-powered Retrieval-Augmented Generation (RAG) chatbot supports Same Sky’s engineers respond to complex customer questions. The chatbot interprets incoming inquiries, searches Same Sky’s internal knowledge base, and assembles draft responses grounded in authoritative product documentation.
Built using Azure OpenAI and Azure Cognitive Search, the system indexes more than 3,000 datasheets and technical resources. A multi-agent architecture retrieves information from both structured and unstructured sources, while a validation step checks answers for completeness and accuracy before presenting them with clear citations. Integrated securely within Same Sky’s Azure environment, the chatbot acts as a trusted research assistant, enabling engineers to answer customer questions more efficiently and consistently.
Features
Technology Connecting Data to Answers
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Multi-Agent Information Retrievals for More Complete Responses
Specialized agents retrieve data from structured records and unstructured documents, allowing the chatbot to assemble thorough answers from multiple authoritative sources.
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Validation and Self-Review Step for Reduced Errors and Omissions
Before presenting an answer, the system checks for missing details and verifies supporting sources, improving accuracy and reliability.
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Centralized Knowledge Base Indexing for Consistent Information Access
More than 3,000 product datasheets and technical resources are indexed, ensuring engineers reference the same approved information every time.
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Citation-Backed Responses for Transparent Verification
Each response includes clear references to source documents, allowing engineers to quickly confirm details and build confidence in the information provided.
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Secure Azure Integration for Protected Proprietary Data
Authentication via Entra ID and Azure-based storage keep all content and interactions within Same Sky’s secure environment.
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Usage Logging and Feedback Capture for Continuous Improvement
Query logs and engineer ratings help identify gaps, refine prompts, and improve answer quality over time.
Results
Clearer, Faster Support for Engineers and Customers
With the RAG chatbot in place, Same Sky’s support engineers no longer begin each inquiry with manual research. Instead, they start with a structured, citation-backed draft that consolidates relevant product information. In early use, the system supplies roughly 90% of the content needed for complex responses, significantly reducing repetitive research and improving consistency across similar inquiries.
Customers receive clearer, more complete answers grounded in approved documentation. Responses are easier to understand and verify, resulting in fewer follow-up exchanges. Together, these improvements increase internal confidence while delivering more reliable and consistent support experience for Same Sky’s customers.
What's Next
Expanding AI Support Across More Workflows
Resource Data continues partnering with Same Sky to evolve the chatbot as support needs grow. Planned next steps include expanding the indexed knowledge base, improving answer quality through ongoing feedback, and integrating the tool more deeply into existing support systems.
As adoption expands, the chatbot can support additional customer-facing teams, creating a consistent and scalable way to deliver technical information across the organization.
