{"id":9833,"date":"2026-02-03T09:32:36","date_gmt":"2026-02-03T09:32:36","guid":{"rendered":"http:\/\/localhost\/Rysunmvplive\/?post_type=success-story&#038;p=9833"},"modified":"2026-03-26T06:56:27","modified_gmt":"2026-03-26T06:56:27","slug":"ai-powered-product-discovery-b2b-solar-marketplace","status":"publish","type":"success-story","link":"http:\/\/phpdemo03.kcspl.in:9099\/rysunmvplive\/success-story\/ai-powered-product-discovery-b2b-solar-marketplace\/","title":{"rendered":"AI-Powered Product Discovery for a B2B Solar Marketplace"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row el_class=&#8221;casestudy-main-section&#8221;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner][vc_custom_heading text=&#8221;Overview&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;custom-heading&#8221;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para&#8221;]A USA-based B2B solar marketplace operating in the renewable energy ecosystem set out to simplify how buyers discover and evaluate solar products. The platform aggregates products from multiple solar manufacturers and providers, serving installers, EPCs, and enterprise procurement teams that often need to make decisions across a wide range of technical and commercial parameters.<\/p>\n<p>Rysun partnered with the marketplace operator to design and implement <strong>Solar Query,<\/strong> a generative AI\u2013powered product discovery and sales assistant built on AWS. The solution enables buyers to interact conversationally with the marketplace, express intent in natural language, and receive accurate, data-backed product recommendations\u2014without requiring deep technical expertise in solar engineering.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row el_class=&#8221;container&#8221;][vc_column][vc_row_inner el_class=&#8221;blueboxrow animation fadeTop casestudy-overview&#8221;][vc_column_inner el_class=&#8221;overview-block&#8221; width=&#8221;1\/3&#8243;][vc_single_image image=&#8221;3684&#8243; img_size=&#8221;full&#8221; el_class=&#8221;overview-img&#8221;][vc_column_text el_class=&#8221;o-body-medium&#8221;]Industry\u200b[\/vc_column_text][vc_column_text css=&#8221;&#8221; el_class=&#8221;o-paragraph-medium&#8221;]Renewable Energy, Solar, B2B Commerce \/ Marketplace[\/vc_column_text][\/vc_column_inner][vc_column_inner el_class=&#8221;overview-block&#8221; width=&#8221;1\/3&#8243;][vc_single_image image=&#8221;8449&#8243; img_size=&#8221;full&#8221; css=&#8221;&#8221; el_class=&#8221;overview-img&#8221;][vc_column_text css=&#8221;&#8221; el_class=&#8221;o-body-medium&#8221;]Challenge[\/vc_column_text][vc_column_text css=&#8221;&#8221; el_class=&#8221;o-paragraph-medium&#8221;]Intent-based discovery gaps and inconsistent data limited scalability.[\/vc_column_text][\/vc_column_inner][vc_column_inner el_class=&#8221;overview-block&#8221; width=&#8221;1\/3&#8243;][vc_single_image image=&#8221;3686&#8243; img_size=&#8221;full&#8221; el_class=&#8221;overview-img&#8221;][vc_column_text el_class=&#8221;o-body-medium&#8221;]Solution[\/vc_column_text][vc_column_text css=&#8221;&#8221; el_class=&#8221;o-paragraph-medium&#8221;]Generative AI, Conversational AI, AI-Powered Product Discovery, B2B Sales Enablement, Data &amp; Analytics[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row el_class=&#8221;casestudy-who&#8221;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner][vc_custom_heading text=&#8221;Client Context&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]The customer operates a B2B marketplace that aggregates solar products, specifications, and providers across the renewable energy value chain. The platform serves a diverse buyer base, including solar installers, EPCs, and sustainability-focused procurement teams, each with different levels of technical expertise.<\/p>\n<p>Solar product selection is inherently complex. Decisions depend on multiple variables such as efficiency, performance under different environmental conditions, warranty terms, pricing, and compatibility with specific installation scenarios. Many buyers know what outcome they want but do not always know the precise technical terminology required to search effectively.<\/p>\n<p>As the marketplace expanded its catalog and onboarded additional providers, the limitations of traditional product discovery mechanisms became increasingly apparent.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row el_class=&#8221;casestudy-who&#8221;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner el_class=&#8221;casestudy-who&#8221;][vc_custom_heading text=&#8221;Business Challenge&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]The marketplace faced two core challenges that directly impacted buyer experience and platform scalability. [\/vc_column_text][vc_custom_heading text=&#8221;1. Product Discovery for Non-Technical Buyers&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Traditional keyword-based search and static filters required buyers to know exact product attributes and technical terms. This made discovery difficult for users who wanted to express intent-based needs such as:<\/p>\n<ul>\n<li>\u201cHigh efficiency panels that perform well in low-light conditions\u201d<\/li>\n<li>\u201cCost-effective solutions for commercial rooftops\u201d<\/li>\n<li>\u201cPanels with longer warranty and lower degradation\u201d<\/li>\n<\/ul>\n<p>As a result, buyers often relied on manual exploration or expert assistance, slowing down decision cycles and reducing conversion efficiency.[\/vc_column_text][vc_custom_heading text=&#8221;2. Data Scale and Consistency&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Solar product data was sourced from multiple providers in inconsistent formats, including spreadsheets and CSV files. Manual data preparation and schema alignment slowed updates, increased operational overhead, and made it difficult to keep recommendations current as new products were added.<\/p>\n<p>Relying on subject-matter experts to interpret data and guide buyers did not scale as the marketplace grew. The platform needed a solution that could:<\/p>\n<ul>\n<li>Translate buyer intent into accurate product queries<\/li>\n<li>Combine structured product attributes with semantic understanding<\/li>\n<li>Scale discovery without increasing manual intervention<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row el_class=&#8221;casestudy-bg-gradient mt-200&#8243;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner el_class=&#8221;casestudy-who&#8221;][vc_custom_heading text=&#8221;Solution Overview: Solar Query&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Rysun designed <strong>Solar Query<\/strong> as an AI-powered conversational sales and discovery assistant that bridges the gap between buyer intent and complex solar product data.<\/p>\n<p>Rather than acting as a simple chatbot, Solar Query functions as an <strong>intelligent product discovery layer<\/strong> embedded within the marketplace. It allows buyers to ask natural-language questions, refine requirements through dialogue, and receive contextual recommendations supported by real product data.<\/p>\n<p>The solution was intentionally designed to <strong>augment decision-making,<\/strong> not replace human expertise. Buyers remain in control of final selection, while AI accelerates discovery, comparison, and understanding.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner el_class=&#8221;casestudy-who&#8221;][vc_custom_heading text=&#8221;AWS Architecture for Intent-Based Product Discovery&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Solar Query is built on a scalable, cloud-native architecture using AWS services that combine data engineering, analytics, and generative AI.[\/vc_column_text][vc_custom_heading text=&#8221;1. Intent Interpretation and Hybrid Query Execution&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Buyer queries are processed through a serverless orchestration layer that interprets intent and determines how each request should be handled. Depending on the query, the system dynamically executes:<\/p>\n<ul>\n<li>Structured filtering and aggregation against curated datasets<\/li>\n<li>Semantic similarity searches across product descriptions<\/li>\n<li>Contextual reasoning that combines multiple attributes and constraints<\/li>\n<\/ul>\n<p>This hybrid approach ensures that generative AI is used responsibly and only where it adds value.[\/vc_column_text][vc_custom_heading text=&#8221;2. Retrieval-Augmented Generation for Product Matching and Comparison&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]To generate trustworthy responses, Solar Query implements a retrieval-augmented generation (RAG) pattern. Product specifications and metadata are indexed for semantic search, enabling the system to retrieve the most relevant products before generating explanations or recommendations.<\/p>\n<p>Generative AI models are used to:<\/p>\n<ul>\n<li>Translate buyer intent into understandable options<\/li>\n<li>Explain trade-offs between products<\/li>\n<li>Provide context around why certain products are recommended<\/li>\n<\/ul>\n<p>This ensures responses remain grounded in authoritative marketplace data rather than generic model knowledge.[\/vc_column_text][vc_custom_heading text=&#8221;3. Automated Product Data Engineering and Catalog Refresh&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Solar product datasets are ingested through automated pipelines that standardize source files, manage schema evolution, and optimize data for analytics and search. This enables faster updates, reduces manual effort, and ensures new products are available for discovery without delay.[\/vc_column_text][vc_custom_heading text=&#8221;4. Governance, Security, and Observability&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]The platform includes built-in monitoring, access controls, and operational visibility to ensure secure, reliable, and scalable buyer experiences. Usage patterns, performance, and data quality can be continuously observed and refined as the marketplace grows.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner el_class=&#8221;casestudy-who&#8221;][vc_custom_heading text=&#8221;Outcomes and Business Impact&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Solar Query significantly improved how buyers interact with the marketplace and how the platform scales discovery.[\/vc_column_text][vc_custom_heading text=&#8221;Buyer Experience Improvements&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]<\/p>\n<ul>\n<li>Buyers can discover suitable products using natural language rather than technical filters<\/li>\n<li>Non-technical users can explore complex solar specifications conversationally<\/li>\n<li>Decision cycles are shorter due to faster access to relevant options and comparisons<\/li>\n<\/ul>\n<p>[\/vc_column_text][vc_custom_heading text=&#8221;Platform and Operational Impact&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h4&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]<\/p>\n<ul>\n<li>A majority of discovery interactions are handled autonomously without expert intervention<\/li>\n<li>Response times for product queries are substantially reduced<\/li>\n<li>Dataset updates are faster and more consistent through automated ingestion pipelines<\/li>\n<li>Marketplace teams can scale catalog size and user volume without increasing manual support<\/li>\n<\/ul>\n<p>Overall, the solution transformed product discovery from a static, filter-driven experience into an interactive, intent-based journey aligned with how buyers actually think and decide.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row el_class=&#8221;casestudy-bg-gradient mt-200&#8243;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner el_class=&#8221;casestudy-who&#8221;][vc_custom_heading text=&#8221;Why AWS and Rysun&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]AWS provided the scalable foundation required to combine data engineering, analytics, and generative AI into a single, production-ready solution. Managed and serverless services enabled the platform to scale dynamically while minimizing operational overhead.<\/p>\n<p>Rysun brought deep expertise in building <strong>enterprise-grade AI systems for data-rich, technical domains.<\/strong> By combining retrieval-augmented generation patterns with strong data engineering practices, Rysun delivered a solution that is accurate, explainable, and designed for long-term growth.[\/vc_column_text][vc_custom_heading text=&#8221;Summary&#8221; font_container=&#8221;tag:h3|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;o-header&#8211;h3&#8243;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para common-listing&#8221;]Solar Query demonstrates how generative AI can unlock smarter product discovery in B2B marketplaces where data complexity and buyer intent rarely align. By enabling conversational, intent-based exploration of solar products, the platform improves buyer experience, reduces operational friction, and supports scalable growth across the renewable energy ecosystem.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row el_class=&#8221;casestudy-main-section&#8221;][vc_column][vc_row_inner el_class=&#8221;container animation fadeTop&#8221;][vc_column_inner][vc_custom_heading text=&#8221;Overview&#8221; use_theme_fonts=&#8221;yes&#8221; css=&#8221;&#8221; el_class=&#8221;custom-heading&#8221;][vc_column_text css=&#8221;&#8221; el_class=&#8221;common-para&#8221;]A USA-based B2B solar marketplace operating in the renewable energy ecosystem set out to simplify how buyers discover and evaluate solar products. 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