SmartLayer is not a feature. It is what Totus becomes over time — a proprietary database of real estate intelligence that compounds as deal teams use the platform. More deals. Better comparables. Sharper decisions.
SmartLayer is the emergent intelligence that builds up inside Totus as your team processes deals. It is not an opaque AI model that produces a number with no explanation. Every score, every band, every comparable reference is derived from real transactions in your database — and can be inspected, traced, and audited.
This is the critical distinction: Totus is a workflow layer first. The intelligence grows from the structured data you generate while using it. You own the data. You control the logic. The system becomes smarter because your team is disciplined about how it captures deals.
For institutional teams and regulated environments, this matters fundamentally. Underwriting outputs remain deterministic and explainable, while the platform continuously improves its reference quality.
Every deal your team processes — plus ingested market data from Thomas Daily and external uploads — builds a geospatially indexed comparables database that is private to your organization.
Deterministic macro and micro-location scores computed from transaction density, price trends, recency of activity, and distance-weighted comparable data. No third-party black box required.
When a new deal arrives, the system fetches nearby comps, computes variance vs. market bands, and flags outliers automatically. Logic is transparent and formulas are configurable.
Approved deals are promoted back into the comps pool. The database gets denser over time. Scoring bands tighten. Reference quality improves. Network effects within your own data.
The foundation. A geospatially indexed store of real estate transactions, enriched from multiple sources. Radius queries return nearby deals with similarity-weighted ranking.
Deterministic scoring modules computed from structured transaction data. Every score has an explanation payload — inputs are inspectable and formulas are configurable.
The screening pipeline that orchestrates geocoding, comparable retrieval, and metric computation for each new deal. Transparent, rule-based, and reproducible.
SmartLayer is not turned on — it emerges as your team uses Totus. Each stage brings measurable improvement in screening accuracy and reference quality.
Database, geocoding pipeline, and comparables engine go live. Thomas Daily market data begins ingestion. First manual deals enter the system.
Screened and approved deals feed back into the comps pool. Location scores start incorporating internal transaction density. CSV uploads enrich coverage by asset type and geography.
Internal transaction density sufficient for reliable micro-location scoring in core markets. Screening accuracy measurably higher than at launch. Comparables coverage expands through team usage alone.
Scoring is primarily driven by internal data. New deals immediately benefit from dense historical context. The system has genuine competitive advantage that external tools cannot replicate without your deal history.
Every property in Totus has geospatial data compatible with map rendering. The backend exposes optimized endpoints for viewport-based and radius-based queries, ready for Mapbox or Leaflet integration.
All external data enters through the same controlled pipeline as internal deals. No direct writes to normalized tables. Every upload is traceable to source, batch, and file. Deduplication runs before promotion.
The SmartLayer is only as trustworthy as the data infrastructure beneath it. These architectural decisions are fixed — not because of convention, but because they are the conditions for reliable intelligence.
Mandatory. All geospatial queries run through PostGIS. No proximity search, no radius comps, no location scoring without it.
Every property record must carry geocoded coordinates. GIST spatial index supports both radius and bounding-box queries efficiently.
Transaction records are never overwritten. Scoring and screening downstream depend on this immutability. Silent history loss corrupts the feedback loop.
Geocoding, comparables, scoring, ingestion — each is a discrete service. No monolithic logic. Easily extensible without rewriting the system.
Request a demo and see how the data layer builds behind the workflow — and how your team's deal history becomes a compounding competitive asset.
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