AI Driven Estimating & Design Platform
Budget: $5,000 – $10,000 USD
We are seeking a freelancer/developer to build a production-ready AI-powered Estimator + Design platform for a residential/general contracting business. The system will consist of two connected applications designed to streamline lead capture, early-stage estimating, and internal proposal creation.
Platform Components
Customer-Facing Estimator + Design Experience
A customer-facing AI estimating and design tool that captures project details, gathers photo uploads, and returns an AI-assisted rough estimate and design concept output. This experience may be delivered either as:
an embedded website widget (floating or inline), or
a dedicated standalone customer portal hosted on a separate URL (preferred option may be decided during development).
Internal Estimator App
A secure internal web application used by our estimating team during site visits to collect detailed project data and generate formal, branded proposals.
Both products must share a common backend and data structure to support continuity from lead intake to formal estimate creation.
Business Objectives
The goal of this platform is to improve estimating efficiency while creating a stronger homeowner experience by providing fast early-stage budget guidance and concept visuals. Key objectives include:
Capturing and qualifying website leads through an interactive AI experience
Providing homeowners with rough budget expectations quickly and clearly
Generating AI-driven design concepts and example imagery from customer inputs and uploaded photos
Enabling estimators to efficiently create formal proposals through a structured internal workflow
Centralizing project data and building the system in a way that is ready for CRM integrations and future automation
Customer-Facing Estimator + Design Experience
The customer experience should function as a guided chat-style workflow that collects project information such as project type, scope, goals, timeline, and optional property address. It must also support uploads for current-condition photos and design inspiration images.
This customer tool must be deployable in one of two formats:
Embedded widget on our existing website (floating or inline), or
Standalone estimator website/portal hosted at a separate URL where customers can complete the estimating workflow.
Using AI-driven logic, the customer-facing experience should return:
A non-binding rough budget range
A high-level category breakdown of estimated costs
Design and scope concept notes
AI-generated example concept imagery based on the customer’s details and uploads
The experience should be polished, mobile-friendly, and include clear onboarding guidance, disclaimers, progress indicators, and graceful error handling.
Deployment should be lightweight and straightforward, with configuration managed through environment variables and support for staging and production environments.
Internal Estimator App
The internal estimator application will be used by our team during on-site walkthroughs and must include secure authentication (role-based access preferred). It should support a structured estimating workflow including room-by-room or trade-by-trade inputs, measurements, material selections, labor assumptions, site condition notes, and photo/attachment capture.
The system must convert captured field information into a formal proposal draft, including:
Editable line items
Scope inclusions/exclusions
Version tracking and revision support
Optional margin/markup controls (if included in scope)
Where applicable, the internal app should be able to reuse intake data collected through the customer-facing estimator tool for lead-to-estimate continuity.
The output must support a branded, professional proposal format suitable for PDF export and client delivery, with a clear separation between preliminary public estimate output and formal proposal documentation.
AI and Backend Requirements
The platform must include a backend services layer that securely manages AI calls and business logic. AI capabilities should support:
Project intent understanding and classification
Rough estimating assistance
Design concept suggestions
Image generation using text and uploaded photo context
All AI usage must be handled server-side to ensure security (no client-side exposure of keys). The system should include fallback behavior when AI services are unavailable and maintain a structure that supports prompt/version tuning over time.
Integration-Ready Architecture (Critical Requirement)
The platform must be designed from the start for future CRM and contractor tool integrations. The architecture should include clear integration points such as:
Webhooks
Outbound REST API syncing
Retry logic and error logging for failed sync jobs
The system should be prepared to support future workflows such as:
Lead/contact creation from estimator submissions
Job/opportunity creation
Proposal status updates
Syncing of notes, photos, and attachments
Technical Expectations
The solution must follow clean and scalable architecture standards, including:
Separation of frontend UI and backend services
Secure file upload handling and storage
Input validation and sanitization
Observability through logging and basic monitoring
Audit/event logging for key actions
Environment-variable based configuration
Clear API contracts between customer-facing experience, internal app, and backend services
Deliverables
The developer will deliver a production-ready codebase including:
Customer-facing estimator experience (widget and/or standalone portal)
Internal estimator application
Backend AI and services layer
Additional deliverables include:
Setup and deployment documentation
Environment variable template
Integration documentation (API endpoints, webhook structure, auth method)
Admin handoff notes for ongoing maintenance and future expansion
Success Criteria
The project will be considered successful when:
The customer-facing estimator experience is deployable and works end-to-end (either embedded or standalone URL)
Customers can submit project details and uploads and receive budget ranges, design concepts, and AI-generated imagery
The internal estimator app can generate formal proposal drafts from on-site inputs
The system is structured to support future CRM integrations with clear extension points
All sensitive keys and services remain securely server-side and are deployment-ready via environment-based configuration
Platform Components
Customer-Facing Estimator + Design Experience
A customer-facing AI estimating and design tool that captures project details, gathers photo uploads, and returns an AI-assisted rough estimate and design concept output. This experience may be delivered either as:
an embedded website widget (floating or inline), or
a dedicated standalone customer portal hosted on a separate URL (preferred option may be decided during development).
Internal Estimator App
A secure internal web application used by our estimating team during site visits to collect detailed project data and generate formal, branded proposals.
Both products must share a common backend and data structure to support continuity from lead intake to formal estimate creation.
Business Objectives
The goal of this platform is to improve estimating efficiency while creating a stronger homeowner experience by providing fast early-stage budget guidance and concept visuals. Key objectives include:
Capturing and qualifying website leads through an interactive AI experience
Providing homeowners with rough budget expectations quickly and clearly
Generating AI-driven design concepts and example imagery from customer inputs and uploaded photos
Enabling estimators to efficiently create formal proposals through a structured internal workflow
Centralizing project data and building the system in a way that is ready for CRM integrations and future automation
Customer-Facing Estimator + Design Experience
The customer experience should function as a guided chat-style workflow that collects project information such as project type, scope, goals, timeline, and optional property address. It must also support uploads for current-condition photos and design inspiration images.
This customer tool must be deployable in one of two formats:
Embedded widget on our existing website (floating or inline), or
Standalone estimator website/portal hosted at a separate URL where customers can complete the estimating workflow.
Using AI-driven logic, the customer-facing experience should return:
A non-binding rough budget range
A high-level category breakdown of estimated costs
Design and scope concept notes
AI-generated example concept imagery based on the customer’s details and uploads
The experience should be polished, mobile-friendly, and include clear onboarding guidance, disclaimers, progress indicators, and graceful error handling.
Deployment should be lightweight and straightforward, with configuration managed through environment variables and support for staging and production environments.
Internal Estimator App
The internal estimator application will be used by our team during on-site walkthroughs and must include secure authentication (role-based access preferred). It should support a structured estimating workflow including room-by-room or trade-by-trade inputs, measurements, material selections, labor assumptions, site condition notes, and photo/attachment capture.
The system must convert captured field information into a formal proposal draft, including:
Editable line items
Scope inclusions/exclusions
Version tracking and revision support
Optional margin/markup controls (if included in scope)
Where applicable, the internal app should be able to reuse intake data collected through the customer-facing estimator tool for lead-to-estimate continuity.
The output must support a branded, professional proposal format suitable for PDF export and client delivery, with a clear separation between preliminary public estimate output and formal proposal documentation.
AI and Backend Requirements
The platform must include a backend services layer that securely manages AI calls and business logic. AI capabilities should support:
Project intent understanding and classification
Rough estimating assistance
Design concept suggestions
Image generation using text and uploaded photo context
All AI usage must be handled server-side to ensure security (no client-side exposure of keys). The system should include fallback behavior when AI services are unavailable and maintain a structure that supports prompt/version tuning over time.
Integration-Ready Architecture (Critical Requirement)
The platform must be designed from the start for future CRM and contractor tool integrations. The architecture should include clear integration points such as:
Webhooks
Outbound REST API syncing
Retry logic and error logging for failed sync jobs
The system should be prepared to support future workflows such as:
Lead/contact creation from estimator submissions
Job/opportunity creation
Proposal status updates
Syncing of notes, photos, and attachments
Technical Expectations
The solution must follow clean and scalable architecture standards, including:
Separation of frontend UI and backend services
Secure file upload handling and storage
Input validation and sanitization
Observability through logging and basic monitoring
Audit/event logging for key actions
Environment-variable based configuration
Clear API contracts between customer-facing experience, internal app, and backend services
Deliverables
The developer will deliver a production-ready codebase including:
Customer-facing estimator experience (widget and/or standalone portal)
Internal estimator application
Backend AI and services layer
Additional deliverables include:
Setup and deployment documentation
Environment variable template
Integration documentation (API endpoints, webhook structure, auth method)
Admin handoff notes for ongoing maintenance and future expansion
Success Criteria
The project will be considered successful when:
The customer-facing estimator experience is deployable and works end-to-end (either embedded or standalone URL)
Customers can submit project details and uploads and receive budget ranges, design concepts, and AI-generated imagery
The internal estimator app can generate formal proposal drafts from on-site inputs
The system is structured to support future CRM integrations with clear extension points
All sensitive keys and services remain securely server-side and are deployment-ready via environment-based configuration