FundMore.ai
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About
FundMore.ai is an automated underwriting system designed to modernize the pre-funding phase of the loan lifecycle. By leveraging machine learning and artificial intelligence, the platform transforms the traditionally slow and manual mortgage process into a digitized, efficient workflow. It acts as an AI-powered loan origination system (LOS) that handles everything from the initial borrower application to the final funding and post-close management. The primary goal is to replace outdated spreadsheets and manual data entry with intelligent automation that ensures accuracy and speed for financial institutions. The platform operates through several specialized modules, including FundMore IQ for document management and FundMore AVA (Agentic Virtual Assistant) for decision-making. FundMore IQ uses optical character recognition (OCR) to extract data from uploaded documents, automatically validating it against the borrower's application and generating dynamic checklists. The system also integrates with external services for income validation, digital authentication, and auto-valuation models. Through open APIs, it connects seamlessly with credit bureaus, CRMs, and existing post-funding systems, allowing for a unified data flow across the entire lending ecosystem. This tool is specifically tailored for private lenders, mortgage brokers, and small lending institutions that need to scale their operations without significantly increasing headcount. It is particularly beneficial for organizations looking to reduce their reliance on individual talent and manual oversight, which often leads to bottlenecks. By providing a customizable dashboard and analytical reports, it allows management to gain insights into pattern recognition and risk viability, making it suitable for risk officers and underwriting teams who require data-driven approval recommendations. What sets FundMore.ai apart is its commitment to reducing the stress of the mortgage process for both the lender and the borrower. While many systems focus purely on the backend, this platform emphasizes the borrower experience with mobile-friendly application intakes and real-time status updates. It also distinguishes itself through high security standards, being SOC 2 compliant and meeting AML/KYC, OSFI, and PIPEDA requirements. The modular nature of the software allows companies to personalize their workspace, ensuring the tool adapts to specific business rules.
Pros & Cons
SOC 2 compliance ensures high-level data security and privacy for financial institutions.
Reduces document processing costs by up to 90% through OCR and automated validation.
Open API architecture allows for seamless integration with existing CRMs and credit bureaus.
Customizable modular workspace lets lenders tailor the interface to their specific workflow.
Real-time status updates improve transparency and the overall experience for borrowers.
Pricing is not transparently listed on the website, requiring a demo request for costs.
The high level of customization may require significant initial setup time for complex rules.
The platform is specifically targeted at smaller private lenders rather than large retail banks.
Use Cases
Private mortgage lenders can automate risk assessment to provide faster approval recommendations while maintaining compliance.
Mortgage brokers can use the dynamic intake forms to collect borrower documents more efficiently and reduce manual follow-ups.
Underwriting teams can leverage the predictive modeling and pattern recognition features to identify high-risk files early.
Compliance officers can automate AML and KYC checks to ensure every loan meets regulatory standards without manual auditing.
Platform
Features
• soc 2 compliant security
• automated income validation
• digital authentication & e-signatures
• customizable analytical dashboard
• real-time credit bureau integration
• fundmore ava virtual assistant
• fundmore iq ocr document extraction
• ai-driven automated underwriting
FAQs
How does FundMore automate the underwriting process?
FundMore uses its Agentic Virtual Assistant (AVA) to apply specific lender rules to every application. This allows the system to assess eligibility, calculate affordability ratios, and provide automated approval recommendations.
What is FundMore IQ?
FundMore IQ is a dedicated module that simplifies the document collection process for both lenders and borrowers. It uses OCR technology to extract data from documents and validates it against the initial loan application.
Is the platform secure for sensitive financial data?
The platform prioritizes security and is officially SOC 2 compliant. It also features built-in automation for AML, KYC, and PIPEDA compliance to ensure all data handling meets industry regulations.
Can it integrate with my current CRM?
FundMore is built with an open API architecture specifically to work as an extension of your current environment. It can integrate with leading third-party post-funding systems, CRMs, and credit bureaus.
How does it help with document collection?
Borrowers receive personalized checklists and can upload documents directly to a secure portal. The system then automatically verifies these documents, reducing the cost of collection and processing by up to 90%.
Pricing Plans
Enterprise
Unknown Price• Automated Underwriting
• FundMore IQ Document Extraction
• FundMore AVA Assistant
• SOC 2 Compliance
• Open API Access
• Income Validation
• Auto Valuation Model
• AML/KYC Automation
• Digital Authentication
• Customizable Dashboard
Job Opportunities
Senior AI Engineer
Streamline mortgage lending with AI-driven automated underwriting that reduces risk and accelerates approval times for private lenders and mortgage brokers.
Benefits:
Opportunity to work with cutting-edge AI technologies
Flexible working arrangements
Competitive salary
Benefits
Professional development opportunities
Education Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
Experience Requirements:
Minimum 1 year of experience in AI/ML development
Minimum 5 years proven experience with Python and JavaScript
Other Requirements:
Familiarity with agentic systems, RAG techniques, and LangGraph
Experience with gateway routing abstractions, Svelte, AWS, and relational databases
Strong understanding of SDLC, OOP concepts, and clean coding practices
Excellent problem-solving and communication skills
Responsibilities:
Apply the full software development life cycle (SDLC) for AI components
Write clean, maintainable code following best practices and design patterns
Develop detailed documentation for system functionality
Integrate AI solutions seamlessly using Python and JavaScript
Implement and optimize agentic systems and RAG techniques
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Ratings & Reviews
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