A mobile-first inspection platform that turns scanned tags and labels into structured lifecycle intelligence — for property managers, technicians, and homeowners.
Prepared by
Nikolay Gushlekov
Section 01
Understanding the vision
Your concept describes a mobile application that does something the current generation of inspection apps doesn't do well: it understands what it's looking at. Rather than simply storing photos and notes, it extracts manufacturing dates, serial numbers, warranty information, and service histories from the physical labels on appliances, fire-safety equipment, and building assets — then uses that data to predict when each item will need attention.
This is fundamentally three products in one shell:
A data-capture tool that converts photos of stickers, tags, and QR codes into structured records — replacing today's manual photo-and-notes workflow used in tools like NetVendor and HappyCo.
A lifecycle intelligence engine that knows the expected lifespan, warranty windows, and maintenance schedules for each asset category, and automatically schedules notifications and recommendations.
A universal integration layer that pushes this data into the property management systems (Yardi, RealPage, Entrata) already in use across multifamily and hospitality.
The competitive landscape confirms the opportunity. HappyCo dominates the inspection space with template-based checklists but doesn't offer real OCR-driven asset intelligence. Inspectify recently launched OCR-based appliance capture, which validates the technical approach. No vendor currently combines all three layers above into a single, focused product — which is your opening.
The core value proposition: fewer minutes per unit during inspection, and a predictive picture of every building's condition that today exists only in disconnected spreadsheets and field notebooks.
~70%Time saved per inspection
10 yrsSmoke detector mandatory lifespan
6 yrsFire extinguisher pressure-test cycle
5–7 yrsTypical water heater warranty
Section 02
Users & roles
The application serves two distinct customer segments with different needs and pricing logic. Identifying them clearly up front shapes everything from data models to onboarding flows.
Segment A — Individuals & homeowners
A single user managing their own home. They install the app, create a small inventory of assets (water heater, fire extinguisher, smoke detectors, appliances), receive maintenance reminders, and optionally see recommendations for local service providers when something needs work. One-time purchase or low monthly subscription.
Segment B — Multifamily & commercial property management
Property management companies running portfolios of dozens to thousands of units. They need multi-tenant data isolation, role-based access, integration with their existing PMS, and dashboard-level visibility for owners. Per-unit monthly subscription with volume tiers.
Within Segment B, the product supports three role levels:
Technician — performs inspections in the field, captures asset data, completes work orders. Mobile-first.
Owner / Executive — portfolio-level dashboard with predictive analytics, capital planning views, asset condition trends. Web-first.
Section 03
Feature breakdown
Features are organised into four tiers by priority and dependency. Tier 1 is the minimum viable product. Tier 2 adds the differentiating intelligence. Tier 3 covers PMS integrations, which are technically self-contained but have long external lead times. Tier 4 covers exploratory features best validated after launch.
Tier 1 · Core MVP
The product that ships first
Everything required to make the app useful to a first paying customer. This is what's built and validated before any further investment.
Cross-platform mobile app (iOS & Android)Single codebase via React Native / Expo. Native camera, GPS, and notifications.
Medium
Offline-first operation with cloud syncTechnicians work in basements and back rooms — connectivity can't be assumed. All data captured offline, syncs when reachable.
High
Photo capture & OCR for serial / model / datesHybrid pipeline: on-device fast-path (Google ML Kit) + Claude Vision API for difficult tags, handwritten dates, and pressure-test punch tags.
High
QR & barcode scanningStandard ML Kit integration — links to product datasheets and warranty pages when available.
Low
GPS-based location detectionAutomatic unit/building identification from coordinates, with manual override for ambiguous cases.
Low
Asset CRUD & categorisationCreate, edit, browse assets. Built-in categories: water heaters, fire extinguishers, smoke detectors, HVAC, refrigerators, stoves, microwaves, dishwashers, fire panels.
Low
Lifecycle rules enginePer-category rules: warranty period, expected lifespan, mandatory service cycles. Automatically computes age, remaining life, next service date.
Medium
Push & local notificationsScheduled reminders for inspections, service dates, mandatory replacements. Calendar integration.
Medium
Basic PDF reportsPer-unit and per-portfolio reports with photos, asset list, and upcoming maintenance schedule.
Low
Multi-tier user roles & permissionsSingle user / Technician / Manager / Owner with row-level data isolation.
Medium
Tier 2 · Intelligence layer
What makes this product different
The features below transform the app from "another inspection tool" into a predictive maintenance system. They depend on Tier 1 being live and producing data.
Handwritten punch-tag recognitionReading dates from physical service tags — the core challenge for fire-extinguisher and water-heater inspections. Trained on real samples.
High
Manufacturer serial-number decodingPer-brand rules to decode week/year of manufacture from serial-number patterns (Whirlpool, GE, Frigidaire, Kidde, A. O. Smith, and more).
Medium
Owner dashboard with predictive analyticsPortfolio-level views: condition score per building, capital-replacement forecast, items entering warning windows in the next 12 / 24 / 36 months.
Medium
Voice-to-text entryHands-free note-taking during inspection. Native speech APIs.
Low
Stylus / drawing-to-text entryFor environments where typing is impractical (gloves, weather). OCR on stylus input.
Low
Tier 3 · Property-management system integration
Pushing data where it already lives
Each PMS integration is technically a separate adapter and has its own approval / partnership timeline. These run in parallel with development but cannot be rushed by code velocity alone — partnership programs can take 8–12 weeks to clear on their own schedule.
Yardi Voyager integrationThe most widely deployed PMS. Requires Interface Partner registration. Two-way data flow for unit, asset, and work-order records.
High
RealPage integrationRequires partner-program access. Similar adapter pattern to Yardi.
High
Entrata integrationREST-based, generally the cleanest of the three modern APIs. Partnership required.
High
HappyCo / NetVendor data exchangeLikely CSV import/export rather than native — leverages existing customer workflows.
Medium
Tier 4 · Future / beta features
Validate after launch, build on real demand
These are explicitly described as optional or beta in your brief, and the recommendation is to keep them that way. Each should be validated against real customer behaviour before significant build effort.
External vendor recommendationsIntegration with Thumbtack / TaskRabbit / Angi for service-provider referrals when a user can't perform maintenance themselves.
Medium
Product database with datasheetsCentralised library of manufacturer specs, manuals, parts diagrams — likely curated, not crawled.
Medium
Vendor lead-generation marketplacePotentially a separate product line — local service companies pay for qualified leads.
High
Sponsored / advertised vendor listingsRevenue stream from approved service partners. Requires clear policy on conflicts of interest.
Low
Section 04
How a scan works
To make the core experience concrete: a technician points the phone at a water-heater dataplate. Within one to three seconds, the app extracts the relevant fields, validates them against manufacturer rules, computes lifecycle status, and writes a structured record. Below is what the result looks like inside the app.
Scan complete0.8s
Asset type
Water heater
Manufacturer
A. O. SMITH
Model
GCV-50-300
Serial
1838A123456
Manufactured
Week 38 · 2018
Age
7 years, 6 months
Warranty
Expired (6-year)
Expected life
10 years
Recommendation
Asset is in final third of expected service life. Capital replacement should be budgeted within the next 18–30 months. Annual anode-rod inspection recommended.
The structured record is written to the unit's asset list, scheduled into the maintenance calendar, and synced to the connected PMS when integration is active. The technician moves on; the system handles the rest.
Section 05
Strategic recommendations
Before specifying the build, three recommendations that significantly affect cost, risk, and time-to-revenue.
Start with the homeowner, not the enterprise
The brief positions the property-management segment as the larger opportunity, and it is. But Segment B has long sales cycles (60–120 days), requires PMS partnerships, and demands enterprise-grade features before any contract is signed. Segment A — homeowners — is the fast lane to validation, provides real OCR training data, generates testimonials, and funds further development through subscriptions while the enterprise side matures.
Defer PMS integrations to Phase 2
Yardi, RealPage, and Entrata integrations are valuable, but each requires becoming an approved interface partner — a process that can take two to three months independent of code. Ship the core product first with CSV export and Zapier as a stop-gap; this covers 60% of the value while partnerships progress in the background.
Trim voice and stylus entry from MVP
Both are listed as "optional" in the brief and they are correctly classified. They add modest user value but consume disproportionate engineering effort. Add them in Phase 3 once the core captures pipeline is proven and stable.
Following these three recommendations reduces the initial commitment from a 9–12 month enterprise build to a focused 4–5 month MVP that can be revenue-generating before larger investments are committed.
Section 06
Technology stack
The stack is selected for two objectives: speed of development (heavy AI-assisted coding) and operational simplicity (minimal infrastructure to manage). Every choice trades a small amount of theoretical optimisation for a meaningful reduction in build and maintenance effort.
Mobile
React Native (Expo) · TypeScript
Single codebase for iOS & Android. EAS Build for CI. Native camera, GPS, push.
Offline / sync
PowerSync · WatermelonDB
Purpose-built offline-first sync between SQLite on device and Postgres in cloud.
On-device OCR
Google ML Kit (Text Recognition + Barcode)
Free, fast, works offline. Handles 70% of cases. No per-scan cost.
Cloud vision
Claude Vision API (Sonnet)
For complex tags, handwritten dates, punch tags. Structured JSON output via prompting. Used selectively to keep costs bounded.
Backend
Supabase (Postgres + Auth + Storage + Edge Functions)
Replaces weeks of auth, RBAC, and file-storage work. Postgres scales to enterprise.
Integration layer
Node.js (Hono) · BullMQ · Redis
Separate microservice per PMS adapter. Queue-based sync, isolated failure domains.
Web dashboard
Next.js · shadcn/ui · Tailwind
For managers and owners. Deployed to Vercel — zero infrastructure.
Billing
Stripe (Subscriptions + Billing Portal)
B2B via web checkout (no app-store cut); B2C via in-app purchase where required.
Larger ecosystem of inspection-relevant libraries; faster AI-assisted iteration; TypeScript skills transfer to web.
Supabase over Firebase
Postgres (relational, joinable, exportable) is the correct primitive for asset/lifecycle data. Avoids NoSQL data-modelling pain.
Claude Vision over a custom ML model
Custom OCR models for appliance labels require months of training data and tuning. Claude Vision with prompt engineering produces structured JSON output today, at a fraction of cost.
PowerSync over custom sync
Offline-first sync is one of the hardest problems in mobile. A purpose-built solution avoids months of edge-case debugging.
Section 07
Development approach
The proposal assumes active use of Claude Code, an AI-assisted development tool, throughout the project. This is not a marketing detail — it's a meaningful productivity multiplier (typically 30–50% for boilerplate, integrations, tests, and refactoring) that allows a solo senior engineer to deliver work that would otherwise require a small team.
Practically, this means:
Faster feedback loops. Code review, test generation, and documentation happen in parallel with implementation rather than as separate phases.
Higher coverage of edge cases. AI assistance excels at proposing the unhappy paths a human is tempted to skip.
Lower total cost. The hourly rate stays the same; the hours required go down. This proposal's effort estimates already reflect AI-assisted productivity.
What does not change with AI assistance:
Architecture and design decisions. These remain human judgement calls.
External dependencies. PMS partnership approvals, App Store reviews, third-party API quirks — these run on their own clocks.
User research and validation. No substitute for talking to real customers.
How the work is structured
Development proceeds in two-week sprints, each ending with a deployable build the client can install and test. Every milestone has a tangible deliverable — not a status report. The full progression is described in the next section.
Communication & visibility
Weekly written status update with progress, blockers, and next-week plan.
Two-week sprint demo via video call.
Shared project board (Linear or GitHub Projects) with current tasks visible at all times.
Direct channel (Slack / Telegram / email) for time-sensitive questions.
Section 08
Milestones & deliverables
The project is structured into six core phases plus optional add-on phases for PMS integrations and advanced features. Each core phase has a working deliverable that can be tested, reviewed, and approved before the next phase begins — protecting both parties from misaligned expectations.
Validate the technical core before building around it. Confirm Claude Vision can reliably extract data from real labels via a working prototype. Lock down the data model, design system, and sprint plan.
Deliverables
Functional OCR prototype tested on 50+ real label photos
Data model and entity-relationship diagram
Wireframes for primary mobile flows (in Figma)
Design system and component library scaffolded
Project repository, CI/CD pipeline, and staging environment configured
Duration: 2 weeksEffort: ~60 hours
02
Mobile core & capture pipeline
Build the mobile app's primary user experience: photo capture, hybrid OCR pipeline (on-device first, cloud fallback), QR scanning, GPS-based location detection, and the asset CRUD interface. This phase produces a working app that a single user can install and use end-to-end on one property.
Deliverables
iOS & Android builds installable via TestFlight / internal track
Camera capture flow with on-device OCR (ML Kit) integration
Claude Vision API fallback with structured JSON parsing
Asset categories: water heater, fire extinguisher, smoke detector, HVAC, appliances
Local SQLite storage; offline operation confirmed
GPS + reverse geocoding for unit identification
Duration: 5 weeksEffort: ~150 hours
03
Lifecycle intelligence & reporting
The brain of the product. Implement the rules engine that knows the expected lifespan, warranty windows, and inspection cycles for each asset category. Wire up notifications, calendar reminders, and PDF report generation. This is the phase that turns the app from data collection to data intelligence.
Deliverables
Lifecycle rules engine with per-category logic (lifespan, warranty, service cycles)
Manufacturer serial-number decoding for 5–8 major brands
Notification system: scheduled push, local reminders, calendar integration
PDF report generation: per-unit and per-property summaries with photos
Repeat-visit detection: when the user returns to a known location, surface what's due
Duration: 3 weeksEffort: ~90 hours
04
Cloud sync, multi-tenancy & role-based access
Promote the single-user app to a multi-user system. Implement cloud sync (PowerSync), role-based access control (technician / manager / owner), and the web dashboard for managers and owners. At the end of this phase, a property-management company can onboard real staff and run real inspections.
Deliverables
End-to-end offline-to-cloud sync with conflict resolution
RBAC: row-level security per organisation, hierarchical roles
Web dashboard (Next.js): portfolio view, unit drill-down, asset history
User invitation, onboarding, and team-management flows
Audit log of inspections, edits, and assignments
Admin panel for managing categories, rules, and templates
Duration: 5 weeksEffort: ~150 hours
05
Subscription billing & account management
Make the product commercially viable. Integrate Stripe for B2B subscriptions (web checkout), set up plan tiers for individuals and property managers, configure the customer billing portal, and implement entitlement enforcement throughout the app.
Deliverables
Stripe subscription integration with three plan tiers
Customer billing portal (self-service plan changes, invoices, payment methods)
In-app purchase support for individual (B2C) tier where required by app stores
Entitlement checks on units, users, and feature flags
Trial period & grace-period logic
Duration: 2 weeksEffort: ~60 hours
06
Hardening, App Store submission & launch
End-to-end testing, performance optimisation, security review, accessibility pass, store-listing preparation, and submission to Apple App Store and Google Play. Includes onboarding documentation and a basic marketing landing page.
Deliverables
End-to-end test suite covering primary user journeys
Security review: auth flows, data isolation, encryption, GDPR compliance
Performance optimisation: cold-start time, sync efficiency, image handling
Apple App Store and Google Play submission packages
Marketing landing page (Next.js, deployed to Vercel)
User onboarding documentation and in-app help
Admin documentation for ongoing operations
Duration: 3 weeksEffort: ~90 hours
Optional add-on phases
The following phases can be commissioned independently after the core product launches, or run in parallel with the later core phases if budget allows.
A1
Yardi Voyager integration
Build the Yardi adapter as a separate microservice. Includes interface-partner registration support, sandbox testing, and two-way sync for assets, units, and work orders. Note: partnership approval is on Yardi's clock and can add 8–12 weeks of waiting before integration can go live, independent of code work.
Duration: 4 weeks devEffort: ~120 hours
A2
RealPage integration
Adapter for RealPage. Same pattern as Yardi but with RealPage's partner program. Costs are similar; lead times are similar.
Duration: 4 weeks devEffort: ~120 hours
A3
Entrata integration
Adapter for Entrata. Generally the cleanest of the three modern APIs to work with.
Duration: 4 weeks devEffort: ~120 hours
B1
Advanced entry modes — voice & stylus
Voice-to-text dictation during inspection. Stylus / drawing entry for environments where typing is impractical. Both use native platform APIs.
Duration: 2 weeksEffort: ~60 hours
B2
Vendor recommendation engine
Integration with one or two service-marketplace APIs (Thumbtack, Angi) for in-app service-provider referrals. Logic for matching asset / problem to relevant provider categories. Geographic awareness.
Duration: 3 weeksEffort: ~90 hours
B3
Advanced analytics dashboard
Owner-level views: capital-replacement forecasts, asset condition trends, comparison across properties. Built on the same data already captured.
Duration: 2 weeksEffort: ~60 hours
Section 09
Pricing & effort breakdown
Rates are quoted at $25 per hour, reflecting senior fullstack engineering work for an international client. Estimates are firm for each phase: if the work runs over due to my own scope error, the overrun is on me. If scope changes are requested, we agree the change and its cost before proceeding.
Three realistic starting points, depending on appetite and timeline:
MVP only (Phases 01–03, 05, 06) — $11,250 over ~15 weeks. Single-user homeowner product launched and revenue-capable. Skip multi-tenancy for now.
Full core (Phases 01–06) — $15,000 over ~20 weeks. Complete commercial product for both segments, no PMS integrations yet.
Full core + first PMS (Phases 01–06 + A3) — $18,000 over ~24 weeks. Enterprise-ready with Entrata integration (recommended first due to API quality).
Payment schedule
Payment is structured per phase, released upon acceptance of each phase's deliverables:
20% retainer on contract signing, prior to start of Phase 01
Per-phase payment on acceptance of each phase, prorated from the retainer
Final 10% on launch and acceptance of Phase 06
For add-on phases (A* and B*), the same per-phase model applies: 20% on commission, 80% on acceptance.
Flexibility
Any phase can be deferred, descoped, or replaced with a smaller scope without affecting the others. Phases 02, 03, and 04 are sequential and core; the others can move. If you want a phase split into smaller commits (e.g. Phase 04 as two 2-week chunks), I'm happy to restructure.
Section 10
Terms & what's included
Included in the quoted price
All design and development hours described in each phase
Claude Vision API usage — typically $50–300/month at MVP scale, scaling with volume
Apple Developer Program — $99/year
Google Play Developer — $25 one-time
Domain & email — ~$30/year
PMS partnership / interface fees — varies; typically charged by the PMS vendor
Stripe transaction fees — standard 1.5–2.9% + €0.25 per transaction, deducted from payouts
Stock imagery, fonts, branding assets — if commissioned separately
I will set up all of the above on the client's behalf using credentials supplied by the client; the bills flow directly to the client, not through me.
Working assumptions
Access to real label photos (50–100 examples across asset categories) for OCR validation during Phase 01.
Decisions on visual identity (logo, primary colours) confirmed by start of Phase 02 — if not, I'll propose a starting point.
Client provides timely feedback on phase deliverables (within 5 business days). Phases pause if review is delayed.
Major scope changes (new features not listed here) are estimated and quoted separately before being added to the plan.
Intellectual property
Upon final payment, all custom-developed code, designs, and documentation become the client's property under a perpetual, royalty-free license. Third-party open-source libraries retain their original licenses. I retain the right to reference the project (anonymously if preferred) in my portfolio.
Section 11
Post-launch support
Warranty period — included
Six months from final acceptance of Phase 06. Defects in delivered functionality — anything that doesn't behave as described in the scope — are fixed at no additional charge. Bug fixes are prioritised within 2 business days for production-blocking issues, 5 business days for non-blocking.
Ongoing support after warranty
Option A — Pay-as-you-go
For occasional changes, enhancements, or new features. Each request is scoped and quoted before work begins. Hourly rate: $25/hour. No monthly commitment. Best for stable products with predictable, infrequent changes.
Option B — Monthly retainer
For projects with continuous iteration or where rapid response is needed. Reserved hours per month, used flexibly across maintenance, small features, and consulting. Typical packages:
Unused hours roll over for one month. Response SLA: 1 business day for retainer clients.
Recommendation
For the first three months after launch I recommend either pay-as-you-go or the 10-hour retainer. Real usage patterns reveal what's actually needed; committing to a larger retainer before that point is usually premature.
Section 12
Next steps
If this proposal looks aligned with what you have in mind, the next conversation is short and concrete:
Confirm the starting scope — full core, MVP only, or core + first PMS. This determines the contract.
Schedule a 60-minute kick-off call to review open questions, agree the kick-off date, and align on the first sprint goals.
Sign the contract and pay the 20% retainer. Phase 01 starts within 5 business days.
I begin Discovery — and from week one, you have something tangible to look at.
If anything in this document doesn't match your expectations, that's expected on first pass. I'd rather adjust the scope, pricing, or approach now than discover mismatches mid-build. Email or call me with any concerns and we'll revise.
Thank you for the opportunity to put this together. I'm genuinely interested in this problem — it sits at a useful intersection of computer vision, mobile, and a real industry need — and would enjoy building it.