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Case Study

AI Platform Prevents 10x Repair Costs for Property Management Companies

In property management, owner trust is the real currency. Unattended HVAC failures destroy that trust.

FilterSync offers an AI-driven verification system where tenants can upload real-time photos of their filter changes, giving managers documented proof before costly damage begins.

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Client
FilterSync by ResProof
Country
USA
Industry
Real Estate

TECHNOLOGIES

Drupal 11 Python (GPT-4.1) Stripe Twilio DigitalOcean
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TEAM

6 members

YEAR LAUNCHED

2025

TECHNOLOGIES

Drupal 11 Python (GPT-4.1) Stripe Twilio DigitalOcean
See all technologies

TEAM

6 members

YEAR LAUNCHED

2025

What people say about us

AnyforSoft has been a strong and reliable development partner for FilterSync. They understood our objectives quickly and grasped the real constraints behind the product. When issues came up, their team didn’t stall or deflect. They proposed smart workarounds and shipped them fast. Often without adding cost or friction. They think like builders, not ticket takers. That made a real difference as the product evolved and requirements sharpened. Communication stayed clear. Execution stayed steady. It never felt transactional. It felt like working with a team that was invested in the outcome, not just the scope.

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CHALLENGE

The industry gap that set the foundation for FilterSync

CHALLENGE

FilterSync began with a property manager who kept seeing the same pattern: preventable HVAC failures draining budgets and damaging owner trust. The numbers made the problem impossible to overlook:

  • 15–30% of maintenance spend lost to neglect
  • 70–85% of tenants missing filter changes
  • $6K–$12K replacements triggered by clogged systems
  • Hours of manual follow-up every week

He knew the industry wasn’t dealing with a minor inconvenience. It was facing a measurable financial leak with no reliable way to confirm if a filter was ever changed. That gap set the direction: build a system that creates verifiable proof and removes assumption from a high-cost problem.

He partnered with AnyforSoft to design the platform that delivers that proof at scale.

COLLABORATION

Requirements that shaped the build

COLLABORATION

The task was to create a SaaS platform that verifies air-conditioner filters automatically and guides users through the process with minimal effort.

From the start, we faced three core product demands.

Achieving high AI accuracy

The platform needed an AI module capable of interpreting real-world photos under inconsistent lighting, framing, and device quality. This accuracy was essential for one reason: property managers cannot act on unreliable data.

False approvals risk HVAC damage; false rejections create avoidable technician dispatches. The verification engine had to perform with confidence across an entire portfolio.

Designing an effortless assessment flow for tenants

The system needed to capture a valid filter image with minimal tenant effort. Not because convenience is the goal, but because a verification system is only useful when submission rates remain high at every cycle.

We designed a guided, mobile-first flow that reduces the process to a single action, ensuring consistent participation across hundreds of units.

Architecture built for extra compliance modules 

FilterSync planned to extend the verification model to other tenant responsibilities—lawn care, winterization, water softeners, and more.

This required an architecture that could support new AI checks, roles, schedules, and escalation paths without rework. The foundation had to be modular, predictable, and capable of supporting compliance categories far beyond filters.

 

The technical core of FilterSync AI filter verification system

AI photo analysis module

A Python microservice evaluates every uploaded image and assigns a Pass/Fail status. 

It ingests the live photo, runs metadata and condition checks, and returns a result the platform can use for approving the filter change, flagging suspicious or low-confidence submissions, or triggering escalation when a valid photo never arrives

Mobile-first tenant interface

The tenant flow starts with a single SMS link. One tap opens a lightweight page with a short instruction and an immediate option to take a photo.

This keeps the submission step as close to “tap → snap → done” as possible, which supports high participation rates without adding work for property managers.

Role-based dashboards

Structured dashboards give landlords and property managers access to tenants, properties, AI results, and subscription details. 

Access is role-based, so each stakeholder sees the information that matters to their decisions. As portfolios grow, the layout stays predictable and easy to navigate, making it realistic to manage compliance across hundreds of doors.

Escalation and manual review

Human-in-the-Loop escalation flow for edge cases

Escalation and manual review

AI handles the majority of filter assessments, but certain submissions require contextual judgment that automation alone cannot provide. 

To manage these situations, we built a controlled expert review layer that maintains accuracy without slowing the system.

When a photo falls outside normal parameters—poor lighting, borderline filter condition, unusual framing—the platform routes the submission to a designated reviewer. This step is integrated into the verification flow and supports the following tasks:

  • Confirming low-confidence AI results
  • Validating authenticity when metadata signals conflict
  • Resolving ambiguous cases without triggering unnecessary technician visits
  • Preserving a complete decision record for each override

This layer reinforces the reliability of the verification loop. Property managers receive consistent, dependable outcomes, and the system maintains high accuracy even when real-world images vary in quality.

Automate maintenance verification without losing accuracy.
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How it works

FilterSync verification loop that covers the full maintenance check cycle

How it works

Here’s what happens inside the system we built each time a filter needs to be verified.

  • Step 1: Scheduled check. Each property follows automated intervals with predefined rules.
  • Step 2: Live photo capture. A secure SMS link opens a real-time camera interface for immediate submission.
  • Step 3: AI verification. The engine analyzes authenticity, timing, and filter condition to produce a Pass or Fail result.
  • Step 4: Property manager review when needed. Low-confidence cases route to a reviewer for decisive confirmation.
  • Step 5: Escalation for missed deadlines. If no valid photo arrives, the system triggers alerts and prepares technician follow-up.
  • Step 6: Audit record & Dashboard update. Dashboards update instantly with compliance rates, overdue units, and property-level insights. Managers gain a clear view of portfolio health without manual follow-up.

Once verification is complete, the next interval is scheduled automatically. The loop repeats without additional setup.

Outcome

A partnership delivering early results and future potential

Outcome

At AnyforSoft, we keep shaping FilterSync with features that strengthen its position and support the founder’s long-term vision for portfolio-wide compliance. 

Each improvement builds on the same idea that started the project: property managers deserve tools that protect their time, their owners, and their reputation.

FilterSync now stands on a solid foundation, supported by a provisional patent and early traction in the market. The platform is still young, but its direction is unmistakable. We’re proud to contribute to a product with real utility and a purpose that matters inside the industry it serves.

Have a clear problem in your industry but no technical team to build the solution? We can handle the engineering and AI behind it.
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