AI for PropTech
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Solsten

AI-powered commercial real estate underwriting platform that replaces static spreadsheet assumptions with probability-weighted lease-renewal forecasting and a natural-language assistant that explains every number.

Best for: Best for CRE acquisitions analysts, brokers, and owner-operators who want institutional-grade underwriting without ARGUS-level pricing or fragile Excel models.

Last reviewed 6/14/26

Tags: cre-underwritingproforma-modelinglease-renewal-forecastingrent-rollrisk-scoringportfolio-managementai-assistant

Pricing

  • Free plan $0 forever (1 property, 1 analysis per month, 1 editor seat, full proforma engine, ML forecasting, Saga AI 50 onboarding requests), no credit card required
  • Starter $99 per month billed annually ($1,068 per year): 5 properties, 6 analyses per month, 1 portfolio, 250 Saga queries per month
  • Professional $179 per month billed annually ($1,932 per year): 15 properties, unlimited analyses, 2 editor seats, 3 portfolios, waterfall modeling, 750 Saga queries per month
  • Enterprise: custom pricing with SLA and dedicated support
Integrations
Excel import (including ARGUS Excel exports)
Property types
Office, Retail, Industrial, Multifamily, Mixed-Use
AI

How Solsten uses AI[1][3]

Two AI systems run inside the underwriting model. A machine-learning forecaster assigns each lease a renewal probability and blends those odds with the property's own payment history to project income, recalculating automatically as the deal timeline advances. Saga, a natural-language assistant, answers questions about the model's assumptions, outputs, and scenario changes in plain English, grounded in the specific property.

  • Probability-weighted modeling assigns each lease a renewal likelihood across the property timeline
  • Forecasts blend the property's actual payment history with user assumptions and sharpen as more data is entered
  • A continuously recalculating timeline rolls leases, extends vacancies, and updates projections as time advances
  • Models train on the user's own property and lease data rather than a generic dataset
  • Saga, an LLM-based assistant, explains assumptions and results grounded in the live property model

AI type: Machine Learning (Predictive), LLM/NLP

API: unknown MCP: unknown

What it helps you do

Streamline Underwriting Portfolio Optimization

Built for

Asset Managers Brokers Investors

Key numbers[1][5]

  • Proforma engine backed by 1,400+ automated backend tests (company-reported)
  • runs entirely in the browser with no install
  • free tier with no credit card required

Credibility[4][5][6][8]

Founders & team
  • Eric Davis Solo founder. US Army veteran (101st Airborne Division), Colorado State University business and real estate graduate, former CRE acquisitions analyst, and licensed Colorado broker; self-taught engineer who built Solsten from scratch
Investors
Bootstrapped and veteran-owned (Compass Holdco LLC). No outside funding reported.
Reviews
G2 5.0/5 from 2 reviews (early-stage product, company in beta)

Founded

2022

Headquarters

Greeley, CO

Stage

Bootstrapped

Employees

1-10

From Solsten

Submitted by the company

In their own words, submitted by the Solsten team. Last updated 6/14/26

Predictive lease-renewal and income modeling

The core ML system uses probability-weighted predictive modeling to forecast lease renewals across a property's timeline. Each lease in the rent roll is assigned a renewal probability, and those probabilities drive a forward-looking actual-vs-projected income view rather than a single static assumption. The models train on the user's own property and lease data, so forecasts sharpen as more deals are analyzed. These projections live inside Solsten's fluid timeline, a continuously recalculating underwriting model where, as time advances, vacancies extend, leases roll, and projections update automatically without manual rework.

Saga, a natural-language underwriting assistant

Saga is an NLP and LLM-based assistant embedded in the platform that explains underwriting assumptions, outputs, and what changed across scenarios in plain language, drawing on the live property context. Underwriting models tend to be black boxes. Saga makes the assumptions and results interrogable in natural language, in-app.

Beyond the AI

The platform also includes portfolio-level management to group and analyze multiple properties together, and team collaboration with granular, permission-based control over property data, so you can share deals with teammates and investors while controlling who can view and edit what, all from any browser.

Product walkthrough