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What is Lev?

Lev is an enterprise AI platform purpose-built for the commercial real estate industry, enabling sponsors, brokers, lenders, investment sales teams, and real estate operators to automate critical transaction workflows while leveraging proprietary market intelligence and relationship data. The platform unifies deal sourcing, underwriting, financing, marketing, outreach, document generation, pipeline management, and transaction execution into a single operational environment. Lev’s AI agents assist users throughout the deal lifecycle by researching properties, extracting data from leases and financial statements, generating offering memorandums, recommending financing structures, matching lenders based on real-time market activity, automating outreach campaigns, analyzing term sheets, and producing actionable pipeline insights. Its financing capabilities leverage historical deal outcomes and lender activity to rank financing partners according to appetite, asset class preferences, geography, transaction type, and loan characteristics. The platform also supports investment sales and acquisition teams through contact enrichment, buyer and sponsor discovery, deal room management, diligence workflows, and collaborative project tracking. For enterprise organizations, Lev offers APIs, workflow automation tools, custom AI agent development, integrations with existing systems, and on-site implementation support. By combining AI-driven automation with commercial real estate-specific data and workflows, Lev enables firms to improve productivity, reduce manual work, accelerate transaction timelines, and gain greater visibility across their investment, lending, and capital markets activities.

What is Help With My Loan?

Automated underwriting and loan matching through AI technology has achieved a remarkable funding rate of 95%, yet the industry struggles with an average funding rate of only 55% due to a disjointed lending process. HWML addressed this challenge by providing brokers, banks, and consumers with access to a platform that connects them with over 300 lenders across various sectors, including Commercial Real Estate, Residential Real Estate, Business, and Personal loans. This innovative approach has enabled HWML to facilitate funding exceeding $600 million, with loans ranging between $100,000 and $50 million. By streamlining the lending process, HWML not only enhances efficiency but also significantly boosts the chances of securing funding for borrowers.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

$99.99
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Lev

Date Founded

2019

Company Location

United States

Company Website

www.lev.com

Company Facts

Organization Name

Help With My Loan

Date Founded

2017

Company Location

United States

Company Website

hwml.app/

Categories and Features

AI Real Estate

Not specified

Categories and Features

AI Lending

Not specified

Banking

Corporate Banking
Credit Union
Multi-Branch
Online Banking
Private Banking
Retail Banking

Commercial Loan

Complex Debt Structures
Dashboard
Document Management
Lead Management
Pipeline Management

Commercial Real Estate

Brand Management
CRM
Cash Flow Analysis
Deal Management
For Brokers
For Investors
Strategic Planning

Loan Origination

Amortization Schedule
Customer Database
Document Management
Loan Processing

Mortgage and Loans

Amortization Schedule
Client Database
Commercial Mortgages
Government Loans
Loan Origination
Loan Servicing
Pipeline Management
Pre-Qualification
Refinance Management
Residential Mortgages

Real Estate

Not specified

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