Instead of a patchwork of plugins, you get a cohesive system: 87 data models, 5 applications, CRM synchronization. A listing is entered once and the subpages generate themselves; publishing to external portals runs through ready-made adapters that we switch on once portal credentials and partnerships are connected. We keep price presentation aligned with price-information requirements — legal responsibility stays with the agency. The architecture scales from dozens to thousands of listings.
cashcrown // property platform
Estate OS
estate-osliveA complete real-estate system: a monorepo, several apps, CRM sync, task queues, and publishing of listings and visualisations.
87
data models
5
apps
CRM
sync
// 01
Problem
Property tech is usually a patchwork of plugins: listings entered over and over, the CRM out of sync with the portal, and last-minute reporting. It is hard to scale and maintain.
// 02
Capabilities
- CRM ↔ portal synchronisation
- auto-generated listing pages
- task queues and publishing
- visualisations and price compliance
// 03
Delivery scope
- Listings generated from the CRM: one source of truth, no manual re-typing
- AI vision photo descriptions and tags (Kimi K2.6) + auto-published pages
- Monorepo, CRM sync, task queues, compliance — like a product, not a patchwork
- Proven scale: 87 data models, 5 apps, 450 listings from CRM
We assemble this product from measured models and components — see the full live pipeline:
// 04
Proof-led pilot
Pilot package: listing portal with CRM
Estate OS is packaged as a productized listing portal: CRM sync, publishing, compliance and visualizations. The proof links a 450-listing case, PropTech landing, lab and dane.gov.pl.
450
listings from CRM
87
data models
5
apps
Evidence
Developer portal
The case shows 450 listings published automatically from CRM and no manual re-typing.
view proofPropTech proof bundle
The industry landing connects CRM sync, dane.gov.pl compliance and the real-estate pilot.
view proof3D Lab
The lab shows the visual layer and product thinking around user experience.
view proofPilot path
- 01We define the source of truth: CRM, API, listing fields, prices, media and statuses.
- 02We build the page generator, publishing queues and validation before SEO rollout.
- 03We add dane.gov.pl compliance, error monitoring and a rollout decision report.
// 05
Integrations
Next.jsNestJSWordPress / JetEnginekolejki
// 06
Architecture
Select a node to see its description and data flow.
Architecture — text description
- Ingest / data
- Data sources — Content, documents and events feed the index. (Flows to: BGE-M3)
- BGE-M3 — Local embeddings (1024-dim) — PII stays on-prem. (Flows to: OpenClaw router)
- AI core
- OpenClaw router — The only entry to the models — masks PII, picks the model, throttles. (Flows to: Estate OS)
- Estate OS — A complete real-estate system: a monorepo, several apps, CRM sync, task queues, and publishing of listings and visualisations. (Flows to: API)
- Serve / integrations
- API — REST surface — cited answers with access control. (Flows to: Next.js, NestJS, WordPress / JetEngine, kolejki)
- Next.js — Integration: Next.js.
- NestJS — Integration: NestJS.
- WordPress / JetEngine — Integration: WordPress / JetEngine.
- kolejki — Integration: kolejki.
// 07
Live demo
// 08
FAQ
How much does it cost and what does the rollout look like?
We work in ranges that depend on scope — we start with a fixed-cost pilot so you see the value before a larger investment. When the solution takes back a dozen to several dozen hours of work a month, it usually pays off in 2–4 months. Calculate the return in the ROI calculator.
Does it integrate with our systems and is it GDPR-compliant?
Yes. We connect to your systems through controlled, allow-listed tools, and irreversible actions require confirmation (a human-gate). We mask PII before the cloud and handle sensitive paths locally — GDPR and AI Act compliance designed in from the start.
Will it replace our CRM?
More often it integrates and synchronises your existing CRM, adding a layer of publishing and automation on top.
How many listings can it handle?
The product architecture (monorepo, queues) scales from dozens to thousands of listings.
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