Real-estate engineering when MLS, IDX, and spreadsheets stop scaling
Custom real estate web apps on subscription. Portals, CRMs, internal ops tools, transaction workflows. Built by the engineer behind Imohub's 120k-property portal. $3,499/mo.
Who this is for
Broker, agency principal, proptech founder, or property-management operator whose MLS/IDX setup is too restrictive and whose spreadsheet-based operations are breaking.
The pain today
- MLS and IDX do not support custom search or data needs
- Property and agent data lives in spreadsheets
- Transaction workflow is in Dropbox, email, and a 10-year-old CRM
- No branded portal for clients or agents
- Performance and SEO on existing tools is worse than competitors
The outcome you get
- Custom real estate web app on subscription at $3,499/mo
- Portal, CRM, or ops tool shipped in 8 to 16 weeks
- Performance baseline at Imohub scale (sub-500ms queries on 100k+ records)
- Clean data model handling MLS feeds, custom listings, and private listings
- Clear handoff to a full-time engineer when team grows
When off-the-shelf real estate software stops working
Brokerages hit three walls usually. MLS data is too restrictive — you cannot show it the way you want or supplement it with private listings. CRM choices are bloated and expensive (kvCORE, BoomTown) or too thin (Follow Up Boss for simple brokerages). Transaction management lives across Dropbox, email, DocuSign, and spreadsheets with no single source of truth. Custom engineering fixes all three when the brokerage is big enough to justify it — usually $5M+ in annual commissions. Below that threshold, the off-the-shelf stack is usually the better choice despite the annoyances.
Typical apps I build
Branded property portals (public-facing search, saved listings, alerts, direct-to-agent lead flow). Agent CRMs tailored to the brokerage's process. Transaction management tools (contracts, checklists, document storage, commission splits). Internal ops dashboards (pipeline, conversion, agent performance). Data sync from MLS + private listings + internal data. Buyer and seller onboarding flows. For property management specifically: tenant portals, maintenance workflows, rent payment, vacancy management. Each is 6 to 14 weeks of subscription work depending on complexity.
Performance and search at scale
Real estate data is uniquely demanding — large catalogs (10,000 to 1M+ listings), rich media per listing (photos, floor plans, videos), complex filtering (price, beds, baths, amenities, geographic). At Imohub I handled 120,000+ properties with sub-500ms query response. Stack: Next.js, React, Laravel, MongoDB, Meilisearch, AWS, Docker. The key decisions: dedicated search engine (Meilisearch or Algolia) instead of ORM queries for search; aggressive CDN caching for static catalog data; server-rendered pages for SEO; image CDN with responsive sizes for media. These patterns scale from 10,000 listings to 1M+ without architectural rewrite.
Pricing and engagement model
Standard $3,499/mo. Pro $4,500/mo. Pro for faster cycles and priority response. 14-day money-back guarantee. Cancel anytime. 100 percent code ownership under Work Made for Hire. MLS integration licensing and data costs are separate — you hold the MLS access agreement, I build the integration against it. Hosting (AWS, Vercel) is yours, typically $200 to $2,000/month at mid-size scale. For brokerages with 5,000+ listings, budget Pro tier for the first 6 months to handle the initial build cadence.
Case: Imohub — 120k+ properties, sub-500ms search, 70% infra savings
At Imohub I rebuilt a real estate portal serving 120,000+ properties with sub-500ms query response, 70 percent infrastructure cost reduction, and top three Google rankings. Stack: Next.js, React, Laravel, MongoDB, Meilisearch, AWS, Docker. The project combined heavy performance work (the search and catalog system) with SEO-first architecture (server-rendered pages, rich schema, canonical URL management). A published LinkedIn article covers the technical playbook. The same patterns apply to any real estate portal or brokerage portal at similar scale.
When a standard real estate CRM is enough
Follow Up Boss, kvCORE, BoomTown, LionDesk — each handles 80 percent of what most brokerages need. For brokerages under $5M in annual commissions, configure the CRM instead of building custom. Custom work pays back when the CRM actively blocks a strategic workflow — complex referral networks, team structures the CRM cannot model, property-management logic not in the standard tools. My target is brokerages and proptech founders where custom engineering materially affects recruit, retention, or transaction efficiency.
Recent proof
A comparable engagement, delivered and documented.
Rebuilt a real estate portal at a fraction of the cost
Rebuilt Imóveis SC's real estate portal as ImoHub — a faster, more scalable successor — handling 120k+ properties with sub-second search and drastically reduced AWS costs.
Frequently asked questions
The questions prospects ask before they book.
- How do you handle MLS/IDX integration?
- Two paths. Path one: use an aggregator's API (iHomeFinder, Showcase IDX, Realtyna) — fastest, works for smaller brokerages. Path two: direct MLS feed via RETS or RESO Web API — required for larger brokerages wanting full control. At Imohub I worked with direct feeds across multiple regional MLS systems. Licensing and data-usage rules vary by MLS — your team holds the agreement, I build the integration against it. Budget 4 to 8 weeks for initial MLS integration.
- Can you sync with our existing CRM?
- Yes. Follow Up Boss, kvCORE, BoomTown, Salesforce, HubSpot — all have APIs. Sync patterns: leads into CRM from any site form, listing assignments from CRM to site agent pages, transaction data flowing both ways. For brokerages wanting to replace the CRM with a custom build, we can do that over 10 to 14 weeks. For most, integrating with the existing CRM is faster and lower-risk — keep what works, build only what is missing.
- How do you handle search infrastructure?
- Dedicated search engine — Meilisearch (self-hosted, cost-efficient) or Algolia (managed, great relevance). For 10,000 to 1M+ records, this is the right architecture. Filtering across many facets (price, beds, baths, amenities, geo radius), typo tolerance, and sub-500ms response on any query. At Imohub I scaled Meilisearch across 120k+ properties. Every mid-to-large real estate engagement includes a search architecture decision in the first 30 days.
- What about photo performance at scale?
- MLS feeds deliver oversized photos. Every image runs through a CDN with automatic resizing, WebP or AVIF conversion, lazy loading, and priority hinting for above-the-fold shots. For 120k+ properties at Imohub, this was critical — even small performance gains per image compounded. Result: listing pages loading in under 2 seconds on mobile with 40+ photos. Image pipeline is usually a week of setup on any new engagement; ROI pays back immediately in conversion and SEO.
- Can you build tenant portals for property management?
- Yes. Tenant portals (rent payment, maintenance requests, document access, lease renewal) are a common property management app surface. Typical build: 8 to 12 weeks for a single-property-management-company portal. Integrations: Stripe or ACH for rent payment, email/SMS for notifications, document storage. For larger portfolios (1,000+ units), additional work for role-based access and multi-property support. Included in standard subscription scope.
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