Confidential planning brief Landlord opportunity No public walk-in traffic

Turn Suite L120 into productive AI infrastructure.

A proposal to convert and operate Suite L120 as a secure mini data center / server room supporting AdPrompt.Ai and the compute requirements of AdChain and AdToken — structured as a revenue-share partnership, with a flexible layout that can also host presentations and events plus future managed compute for local businesses.

$65K–$175K
The landlord-funded Phase 1 build-out — a durable, landlord-owned equipment and infrastructure asset that AdPrompt designs, builds, and operates.
$31K
Illustrative monthly compute revenue the room can generate in the Growth scenario, before costs and support.
~$18.6K
Illustrative monthly landlord share at a 60% split in the Growth scenario — return on the funded build-out that scales with utilization.
The opportunity

A win-win use for Suite L120.

The core idea is simple: convert Suite L120 into a secured technology infrastructure room that puts underused space to productive use, supports the compute requirements of AdChain and AdToken, and generates upside when excess capacity is sold to third parties. AdPrompt.Ai, AdChain, and AdToken become the anchor use cases — the landlord funds and owns the build-out, AdPrompt brings the expertise to design, build, operate, maintain, and grow it, and the landlord earns the upside revenue share the room produces.

1

Productive use of the space

Underused square footage becomes an active, revenue-generating asset — producing returns instead of sitting vacant or cycling through retail and office tenants.

2

Upside revenue share

As the funding partner, the landlord earns the majority share of the compute revenue the room generates, with income that grows as utilization and capacity scale.

3

An owned asset

The landlord funds and owns durable equipment plus power, cooling, security, and monitoring upgrades that stay with the property and raise its long-term value.

4

Low-traffic use

The operation is infrastructure-focused, with dedicated equipment and no public walk-in traffic.

5

Built-in compute demand

AdChain and AdToken require compute for verification, indexing, monitoring, storage, and network services before any outside customers are added.

+

Future managed compute

Over time, unused GPU and CPU capacity could be packaged as managed compute for local businesses.

Why Suite L120 works

The layout is better suited for infrastructure than retail-style office use.

Suite L120’s separation, lower visibility, enclosed layout, and limited foot traffic make it a strong candidate for a controlled server-room environment, with a flexible middle zone that can also function as a presentation or event area.

Proposed use of the space

  • GPU servers for AI inference, model fine-tuning, creative generation, automation, and AdToken compute-heavy services.
  • CPU / storage servers for AdChain and AdToken verification nodes, indexing, storage, monitoring, and supporting workloads.
  • Server rack walls along the sides of the secure hall, with a central event / demo area using row seating for walkthroughs and partner meetings.
  • Dedicated cabling, switches, power distribution, cooling, access control, and operational monitoring.
  • Managed compute capacity for local businesses as demand grows.

Operational guardrails

  • Secure access, monitoring, and defined operating procedures.
  • Phased implementation after power, HVAC, code, and insurance review.
  • Noise, heat, airflow, and equipment load addressed before installation.
  • No retail storefront, no public walk-in traffic, and no disruption-oriented use.
Concept visuals & renderings

The intended look and feel of the hub.

These renderings illustrate the design direction: warm reclaimed wood and exposed brick paired with secured, green-lit server walls, a comfortable lounge, a presentation space, and a refreshment bar — a controlled infrastructure room that still reads as a modern AI environment.

Concept walkthrough — animated fly-through
Animated fly-through of the proposed Suite L120 build-out. Tap the speaker icon to unmute.
Still renderings of the space
Economics

Upside potential.

These are planning assumptions, not final financial commitments. Phase 1 is intentionally framed as a minimum viable validation deployment for AdPrompt.Ai, AdChain, and AdToken before committing to a larger installation.

Minimum viable Phase 1 build-out target

This keeps Phase 1 deliberately lean: one starter rack, staged equipment purchases, essential power / cooling / security work, and no large-scale GPU expansion until anchor workloads and outside demand justify it.

CategoryEstimated costWhat it supports
Starter GPU / AI compute$25K–$60KMinimum useful AI inference, automation, and creative generation — early AdPrompt.Ai capacity without a full GPU fleet up front.
CPU / storage / networking$15K–$45KAdChain and AdToken verification, indexing, storage, monitoring, and supporting network services.
Power, cooling, racks & cabling$15K–$50KRack build-out, power distribution, cooling, and structured cabling for a safe pilot deployment.
Security, monitoring, fire / code review, contingency$10K–$20KBasic resilience, safety, monitoring, access control, code items, and a lean contingency reserve.
Estimated minimum viable Phase 1 total$65K–$175KAssumes a pilot-scale deployment using existing building capacity where possible; major service upgrades quoted separately.
Lean Phase 1 principle: start with the smallest safe and useful deployment, support AdPrompt.Ai plus AdChain / AdToken anchor workloads, and defer larger GPU purchases, full redundancy, and major electrical or cooling expansion until utilization is proven.

Monthly gross potential by scenario

Starter
~$3K–$5K
Monthly gross potential
4–8 GPUs at roughly 50% utilization and $1.75 per GPU-hour, assuming a 30-day month and a deliberately small pilot.
Growth
~$31K
Monthly gross potential
32 GPUs at 60% utilization and $2.25 per GPU-hour, assuming a 30-day month after staged expansion.
Expanded
~$51K
Monthly gross potential
48 GPUs at 65% utilization and $2.25 per GPU-hour, assuming a 30-day month at fuller build-out.

Illustrative landlord revenue share

As the funding partner, the landlord takes the majority share of the compute revenue above, while AdPrompt’s share covers all operations, maintenance, support, and growth. The figures below show monthly landlord income at several negotiable splits across the three scenarios — income that scales directly with utilization.

Landlord shareStarter (~$4K)Growth (~$31K)Expanded (~$51K)
50%~$2,000 / mo~$15,500 / mo~$25,500 / mo
60%~$2,400 / mo~$18,600 / mo~$30,600 / mo
70%~$2,800 / mo~$21,700 / mo~$35,700 / mo
Mutual benefit. The landlord funds a durable, owned equipment asset in their own building and takes the majority of the revenue, while AdPrompt contributes the expertise to build, run, maintain, and grow it — covering all operating costs from its share. At the illustrative 60% Growth split, the landlord’s build-out investment is recovered in roughly 4 to 9 months depending on build-out size, after which the revenue share is ongoing return. Splits are illustrative and fully negotiable.
Deal structure

Flexible models for how the deal works.

Every model is built around a simple split of roles: the landlord funds the build-out and owns the equipment, AdPrompt provides the expertise to design, build, operate, maintain, and grow it, and the landlord earns the upside revenue share — with the exact split tied to whichever structure both sides prefer.

A

Landlord-funded build-out

The landlord funds Phase 1 and owns the equipment and improvements; AdPrompt designs, builds, operates, maintains, and grows the room; and the landlord earns the majority revenue share as the return on that investment.

B

Staged funding

The landlord funds the lean Phase 1 first, with expansion capital released only as utilization is proven — protecting the landlord’s downside while preserving the upside.

C

Optional co-investment

AdPrompt can optionally co-fund part of the equipment to share risk, with the revenue split adjusted to reflect each side’s contribution.

The upside compounds. Because the landlord’s return is a share of compute revenue, it grows automatically as utilization climbs from the Starter pilot toward the Growth and Expanded scenarios — turning a static space into an income-producing asset the landlord owns. See the illustrative revenue-share figures in the economics section.

Phase 1 launch

  • Deploy AdPrompt.Ai, AdChain, and AdToken anchor workloads first.
  • Validate utilization, power, cooling, and operating procedures at pilot scale.
  • Expand excess compute offerings only as outside demand grows.

Choose a structure

  • Landlord-funded build-out with the majority revenue share.
  • Staged funding that releases expansion capital as utilization proves out.
  • Optional AdPrompt co-investment to share equipment risk.
Next step

Let’s schedule a technical walkthrough.

Review the opportunity, confirm power, HVAC, and code feasibility for Suite L120, and align on a partnership structure to launch the lean Phase 1 deployment.

Schedule the walkthrough