Overview
Stridely partnered with a leading building solutions manufacturer to build a generative AI-powered customer assistant that helps users select products, explore design options, and estimate project costs. The solution combines conversational AI with domain-specific knowledge and rule-based calculations to guide customers through early-stage building decisions with better clarity and confidence.
The Client
The client operates in the exterior building materials space, serving residential and commercial construction markets across North America. With a large and diverse product portfolio, they work closely with homeowners, contractors, and builders who need guidance in choosing the right materials and configurations for their projects.
Challenges
The client faced several key challenges:
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The client’s customers struggled to identify the right building products and configurations without expert guidance, especially for small or residential projects
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Product selection required understanding design constraints, material compatibility, and cost impact, which many clients’ customers found difficult to evaluate on their own
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Sales and support teams handled a high volume of repetitive pre-sales queries related to product suitability, design options, and pricing estimates
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Manual responses led to delays and inconsistent guidance across different customer interactions
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Early-stage project discussions did not capture structured requirement data, limiting the sales team’s ability to provide precise recommendations and follow-ups
Solution
Stridely implemented a Generative AI-powered conversational assistant integrated with the client’s product data and design knowledge to support customers during early-stage project planning.
- Conversational Project Guidance
The AI assistant interacts with customers to capture project details, such as building type, dimensions, and design preferences, and then guides them to suitable product options. - Domain Grounded Responses
Using a retrieval-based architecture, the assistant pulls information from product catalogs, technical documents, and design guidelines to ensure responses are aligned with the client’s actual offerings. - Project Level Cost Estimation
The solution applies rule-driven calculation logic on captured inputs to provide estimated material and product costs, helping customers understand budget impact during planning. - Context Aware Recommendations
The assistant maintains conversation context and refines suggestions as users update their requirements, creating a more guided and interactive experience. - Structured Data Capture for Sales
Project inputs gathered during conversations are stored in a structured format, enabling sales teams to access detailed requirement data for faster and more relevant follow-ups.
Technologies Used
- Python-based backend services for orchestration and business logic
- Large Language Models via OpenAI for natural language understanding and response generation
- Retrieval Augmented Generation architecture to ground responses in product and design knowledge
- LangChain framework for tool integration, prompt flows, and conversation management
Results
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Reduced Pre-Sales Support Effort
AI-driven responses and guided assistance lowered manual involvement in early-stage product and design queries by 40% to 60%. -
Faster Customer Response Cycles
Instant recommendations and automated guidance improved response and turnaround time for planning-related queries by 30% to 50%. -
Improved Sales Team Productivity
Structured project inputs captured during conversations helped sales teams engage with better-qualified leads, improving pre-sales productivity by up to 2x. -
Higher Lead Quality for Follow Ups
Captured project requirements, such as design preferences, dimensions, and material needs, enabled more relevant and targeted sales conversations. -
Better Cost Transparency During Planning
Early stage cost estimates gave customers clearer budget visibility, reducing back and forth during later sales discussions. -
Consistent and Accurate Product Guidance
Responses grounded in product catalogs and technical data reduced the risk of incorrect or incomplete information being shared with customers. -
Stronger Digital Engagement
Customers spent more time exploring product options and design possibilities through the AI assistant, increasing interaction with the client’s digital channels. -
Scalable Customer Advisory Capability
The client can now support a much larger volume of planning and product queries without increasing support or sales headcount.
About Stridely Solutions
Stridely designs and delivers enterprise AI solutions that are built to work inside real business processes and systems. The focus stays on combining Generative AI, data engineering, and system integration to solve operational challenges at scale. With deep experience across enterprise platforms and industry workflows, Stridely builds AI systems that are secure, governed, and ready for production use.
