tnt nt nt Tan & Co. - A I Real Estate Analytics and Property Management Solutions in Singaporent nt nt
AI real estate Singapore

Data-backed decisions for every property.

AI that values, scores, and predicts, so property professionals can act fast. Tan & Co. builds models around Singapore's HDB resale trends, commercial cap rates, tenant records, and local transaction data.

Singapore skyline with layered property valuation data and glowing analytics points across residential towers

Indicative valuation check

Enter a postal code to see how the demo reads a local market signal.

Indicative range: S$1.18m - S$1.31m
Built for property teams

AI tools for real estate professionals.

Useful outputs arrive inside the systems your team already uses. Each model has a clear input, a measurable result, and a review path for human judgement.

Property valuation models

Automated AVMs compare URA transactions, locational attributes, floor level, building age, and nearby amenities to produce a defensible pricing range.

Lead scoring for agents

Rank enquiries by likelihood to transact using browsing behaviour, response patterns, viewing history, and CRM records. Agents see who needs attention first.

Portfolio risk analytics

Stress-test rent rolls and property values against vacancy changes, cap-rate movement, and interest rate shocks before they affect your cash plan.

Tenant issue triaging

Natural language processing reads maintenance requests and routes each issue to the right contractor, urgency level, and property record.

Market timing analytics

Combine macro indicators with micro-market signals to identify a stronger listing or acquisition window for a specific asset.

Decision-ready data

Bring scattered spreadsheets, CRM activity, tenancy data, and transaction feeds into one view your team can explain and act on.

Agency case study

Boutique agency boosts lead conversion by 22%.

A 12-agent firm received more than 500 monthly leads. Tan & Co. trained a scoring model on three years of CRM data, then gave agents a simple top-quartile queue.

Within two months, conversion moved from 8% to 10%. The team spent less time chasing cold enquiries and more time on people ready to transact.

"We stopped chasing cold leads and started closing warm ones." Meijin P., Agency Director
Before
8% conversion
After
10% conversion

Top-quartile lead queues gave agents a clear next call.

Portfolio risk analytics

See how your portfolio handles market shocks.

82 health score
Projected cash flow change: -8.4% under this scenario.
A01
12%
A02
38%
A03
9%
B01
76%
B02
44%
B03
16%
C01
11%
C02
68%
C03
14%
Tenant maintenance prediction

Predict maintenance before tenants complain.

The model reads maintenance logs, building age, and sensor data. It scores each unit for AC failure, water leakage, and electrical faults before an emergency call arrives.

  • Connect Yardi, MRI, or a custom property management system.
  • Send high-risk units to the right contractor queue.
  • A property manager cut emergency repair spend by 30%.
Property valuation tools

Try our AI valuation engine.

See how a postal code becomes an indicative range. The model considers URA transactions, MRT distance, floor level, and property age. A consultation is required for an actual valuation.

Singapore valuation demo

Use any six-digit postal code.

Indicative range: S$1.18m - S$1.31m

Make your property data work harder.

Let's build a valuation and scoring model tailored to your portfolio, sales process, or tenant operations.

Schedule Strategy Session
ntnt