AI Harness
The brain behind your operation. Powered by Spark.
Spark is the intelligence layer for multifamily operations. Ask anything, monitor portfolio performance, and run AI agents across every property from one connected view.
Say it once. It’s handled.
A tour follow-up, an urgent repair, a policy call. Spark reads across your systems, shows its work, and waits for you before anything goes out.
Good morning, Amy- Reading the maintenance log for 140C
- Checking technician schedules for today
- Matching a plumbing specialist to the job
- Setting priority from the water damage risk
Dispatch plumbing technician to Unit 140C with priority urgent.
- Reviewing the complaint history for 207
- Looking up the community noise policy
- Checking the lease agreement on quiet hours
Based on the guidelines in Community_Noise_Policy_2026.pdf, this is the third complaint in thirty days, which meets the threshold in lease clause 12.3. The next step is a written warning on file, with a follow-up review in seven days.
Spark runs on your company brain.
Not a generic model with a property-management prompt. Spark works from the knowledge, permissions, history, and live signals that make your organization yours.
One operating memory
Policies, playbooks, property history, and team knowledge stay connected and useful.
Nothing is invented
Each answer names the policy, lease, or record it came from, so you can check it.
Patterns across the portfolio
The same fault in four buildings reads as one pattern, not four unrelated tickets.
Connected to the work
An answer at the desk becomes a work order in the field and an update to the resident.
It learns as you work
The notes, decisions, and corrections your teams make become part of what Spark knows.
One brain, every community
The same memory serves a single property and the whole portfolio, with no setup per site.
Briefed before they arrive
Spark reads the unit’s history and says what was tried the last time.
The fix, from your own manuals
Answers drawn from the equipment documents and past repairs on that unit.
Asked out loud, answered in place
Speak the question with gloves on and Spark answers from your records.
It writes the close-out
Say what you did; Spark writes the notes and the update to the resident.
Role specific.
Spark inherits each person’s role and permissions. Admins set the rules once.
Context by community.
Every answer starts from the community you’re in: its policies, its history, its residents.
Nothing moves without you.
Actions that carry weight wait for a person, and every step is recorded.
Set up on your systems.
Connect your PMS, work orders, and documents. Nothing to migrate.
FAQ
The essentials about Spark.
What can Spark actually do?
Create and assign work orders, draft tour follow-ups, change tour bookings, summarize calls, extract policies and information, update the knowledge base, draft reports, automate workflows, and flag preventive maintenance before it becomes a repair.
How is Spark different from a generic AI tool?
Where does Spark get its data?
How do guardrails and permissions work?
Which AI model is behind Spark?
Start with one workflow
Put Spark to work on your portfolio.
Your properties, your teams, your rules. Talk to us about where Spark fits, and see it on your own operation.
