EliseAI Ratings (September 2025)
This page breaks down EliseAI ratings from all verified review sources to give you a clear, unbiased view of what real users think in September 2025.
We’ve aggregated the latest scores from all major platforms like Trustpilot, G2, Capterra and many more to help you understand EliseAI’s overall reputation. This data-driven overview will show you exactly how EliseAI is rated - including how it compares to competitors.
EliseAI's Overall Rating Summary
- Average Rating:4.5/5
- Total Reviews:12 reviews
- Sources:G2, Capterra
- Last updated:September 1, 2025
G2
CapterraWhat is EliseAI?
EliseAI offers an all-in-one AI assistant and CRM for housing, featuring products like LeasingAI for responding to leasing inquiries and scheduling tours, ResidentAI for handling maintenance and payment conversations, and EliseCRM for managing contacts and building reports. The platform supports communication across multiple channels (voice, text, email, chat) and automates tasks such as maintenance requests, renewals, and delinquency management. EliseAI integrates with existing software, centralizes operations, and provides advanced property cross-selling and human-like interactions to enhance the prospect-to-resident journey.
🤔 EliseAI vs Competitors: How Do Ratings Compare?
Check out EliseAI AlternativesFrequently Asked Questions
How trustworthy is EliseAI?
According to G2 and Capterra review sites EliseAI holds ratings of 4.5/5 and 5/5 respectively from 12 reviews, indicating that users consistently find value and reliability in the platform as of September 2025.
How many stars is EliseAI rated?
EliseAI has an average star rating of 4.5 out of 5 stars based on average of 12 reviews as of September 2025.
Where does the rating data come from?
The ratings are pulled from EliseAI public reviews pages on platforms: G2, Capterra. We update these ratings monthly to ensure they reflect the most current customer feedback.
How overall average rating for EliseAI is calculated?
The overall average rating is calculated by taking the weighted average of all ratings, using the total reviews count from each platform as the weight.