LocateAI
AI-driven retail site selection and leasing for franchises and national brands.
About
LocateAI is a tech-enabled retail real estate brokerage that pairs licensed brokers with proprietary AI models for site selection. The platform analyzes licensed anonymized mobile location data plus what the company describes as 160,000 variables (demographics, traffic, crime, weather and more) to identify the customer segments and locations most likely to perform for a brand, then stress-tests leases against simulated market conditions before signing.
Founded in 2014 by three Stanford computer science graduates, the company focuses on franchise systems and multi-unit operators across the US, covering all 50 states. It reports more than 150 brands as clients and claims its selected locations outperform the market by 15 percent, a vendor figure that should be read as marketing rather than verified research.
What it can do
- AI-powered retail site selection
- Predictive revenue forecasting
- Mobile location data analysis
- Lease stress testing
- National brokerage network
- Market trend and expansion reporting
Setup
- Contact LocateAI with your brand and expansion goals.
- Share historical store performance data for model training.
- Receive AI-ranked markets and candidate sites.
- Review predictive revenue forecasts and lease stress tests.
- Execute site selection and lease negotiation with broker support.
Prerequisites
Retail brand or franchise system planning expansion; historical sales/location data improves model quality.
Use cases
Works with
Trust score — 6/10
Scored 6/10 (TIER metrics, metrics-v1). Evidence: founded 2014 by Stanford CS graduates, 150+ brand clients (Himalayas); national brokerage coverage across 50 states (AI Tech Suite); Entrepreneur company profile corroborates the AI-plus-brokerage model. Strengths: decade-plus operating history, real client base in franchising, differentiated brokerage-plus-AI model. Docked for: (1) performance claims (15% outperformance, 1T data points) are vendor-stated; (2) service pricing is custom/brokerage-based with no public tiers; (3) press cadence is thin in recent years. License: proprietary commercial.
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 7.0/10
- Maintenance · recency, releases, issue load
- 6.0/10
- Openness · license + docs
- 5.0/10
- Manual review · sanity read + red-flag check
- 7.0/10
- · Founded 2014 by Stanford CS graduates; 150+ brand clients (Himalayas)
- · National brokerage coverage across 50 states
- · Performance claims (15% outperformance) are vendor-stated
- · Custom brokerage pricing, no public tiers
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.