vitras.ai
vitras.ai
LIVE
Product Design | Design Technology
© 2024 Product of cove.tool
Contributions: Product Manager | Design Technologist | UX, Product Design and Strategy
On June'24 cove.tool launched its flagship product vitras.ai which is envisioned to be a market leader in building analysis tools, offering users a seamless experience in generating building performance reports through AI guidance and automated workflows. vitras.ai leverages a Large Language Model contextualized to building science data to drive user interaction.As a product, it is designed to solve for the creation, management, and sharing of architectural analysis and project reports. It caters to AEC professionals, offering a streamlined solution for generating comprehensive, accurate , and visually appealing project documentation.
user persona
Architect
Problem Statement
This persona usually struggles with creating comprehensive building performance reports for their clients. They spend hours researching and compiling data, which takes time away from their design work. They need a way to streamline this process and ensure their reports are accurate and up-to-date with the latest sustainability standards.
Product Solve:
vitras helps in quickly generating professional building performance reports using AI-powered automation. To better interpret this data, this user can query a bot that is contextualized on a building science and architecture knowledge base.
Building Performance Consultant
Problem Statement
This persona finds it challenging to collaborate effectively with different architecture teams. They often receive incomplete information and spend time chasing down details. They also struggle to present their findings in a format that is easily understandable to both architects and their clients.
Product Solve:
vitras provides this user with a collaborative platform where they can easily share and receive project documents. The AI-powered chat helps them identify missing information quickly. The reports allow them to effectively communicate their findings to both technical and non-technical teams.
Construction Manager
Problem Statement
This persona struggles with interpreting complex building performance reports and translating them into actionable items for his construction team. He needs a way to quickly understand the key points and requirements without getting lost in technical jargon
Product Solve:
While this persona may not create reports themselves, they can use vitras.ai to view shared documents from architects/consultants. The LLM chat feature allows them to extract key components of the report, helping them understand the implications for construction and further coordinate with their teams.
user flow map
interface
user stats
>1000
active users
263
avg no. reports created/week
57%
chatbot resolution rate
8.2/10
current customer satisfaction rate
report previews
implementation highlights
energy benchmarking analysis
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Integration with cove.tool's baseline energy engine.
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Dynamic data visualization based on results.
implementation highlights
zoning analysis
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Data retrieval engine to query Municode for zoning codes.
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AI summarization using nuances gpt -based algorithms.
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Dynamic html content creation based on retrieved results.
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Resource referencing system.
implementation highlights
climate analysis
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Integration with cove.tool's climate database
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Report generation engine based on minimal user input.
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Data visualization for comprehensive climate metrics.
implementation highlights
cost analysis
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Integration with structured backend cost database
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Allows for user defined inputs or default pre-defined inputs with "Auto" and "Assisted" create workflows.
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Development of estimation engine for cost analysis based on factors of construction, location, and escalation.generation engine based on minimal user input.