AIfortheFortunaGroupmallnetwork
The mall portfolio is managed by hand and reporting arrives weeks late — a tenant’s dip or a traffic drop is spotted after the money is already lost, and without e-document workflow paperwork bogs down. The AI brings the whole portfolio onto one screen and catches deviations the same day, turning after-the-fact reports into real-time management and protecting the network’s revenue.
AI for a shopping mall network — revenue control, leasing and operations, profitability, e-document workflow and mall websites. The whole portfolio sits on one screen, with document workflow and websites automated.
The cost of manual work
The mall portfolio is managed by hand and reporting arrives weeks late — a tenant’s dip or a traffic drop is spotted after the money is already lost, and without e-document workflow paperwork bogs down.
What AI changes
The AI brings the whole portfolio onto one screen and catches deviations the same day, turning after-the-fact reports into real-time management and protecting the network’s revenue.
Operating model
- The mall portfolio is managed by hand
- Reporting arrives late
- No e-document workflow — paperwork bogs down
- The whole portfolio on one screen
- Document workflow automated
- Mall websites automated
How we built it
Diagnostic
We mapped how the mall portfolio was managed and where reporting lost weeks. We locked the outcome metrics: consolidation speed and reaction time to a deviation.
Prototype on real data
The first working loop on real portfolio data — revenue and leasing consolidated onto one screen — within 1–6 weeks.
Production & support
We took the loop to production: the portfolio on one screen, e-document workflow and mall websites automated, deviations caught the same day.
What came out
Igor Golikov
Vitaly Kust
A digital agent team for a photo booth network
8 engineers keep 400+ booths running by hand: a breakdown surfaces via a customer complaint, service trips span half the country, and every booth’s downtime is direct revenue loss. 24/7 auto-monitoring catches a failure before the customer does and resolves up to 80% of incidents remotely, cutting the team from 8 to 1 operator and payroll by 4x.
