Buy-to-Let
Find cash-flowing rental opportunities.
Explore Buy-to-LetFind deals worth investigating.
YieldDNA analyses South African property listings, rental evidence and sale comparables to surface opportunities with strong yield potential.
YieldDNA analyses listings, rental evidence and sale comparables to surface stronger property opportunities.
Select the market that matches how you invest.
Find cash-flowing rental opportunities.
Explore Buy-to-LetFind distressed assets below market value.
Explore Sheriff AuctionsTrack new development opportunities.
Sample Analysis
Pricing
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Discover opportunities.
R499/mo
Make investment decisions.
Real data. Conservative assumptions. No guesswork.
Deal memos. Risk checks. Cashflow first.
Track deals, build lists and compare scenarios.
Ranked opportunities updated weekly.
Ranked investment opportunities based on yield, rent evidence and risk.
| Opportunity | Asking | Gross Yield | Net Yield | Status | |||
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Find sheriff auctions worth investigating.
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| Auction opportunity | Auction date | Bid discipline | Confidence | ||
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How YieldDNA Works
YieldDNA underwrites SA residential listings against rental evidence and operating costs, then surfaces only the deals worth investigating. The focus is on underwriting deals — not showcasing properties.
Investment Philosophy
Strong property investing is driven by disciplined underwriting, conservative assumptions, and pricing discipline — not speculation.
Sustainable income
Deals are evaluated on what they produce today — not projected rent growth or capital appreciation.
Conservative assumptions
Costs, vacancies, and rental estimates are deliberately conservative. We prefer exclusion over optimism.
Margin of safety
The engine is biased toward rejection. Most deals are filtered out. Only high-conviction candidates surface.
Pipeline Architecture
5-stage engine
Continuous analysis of residential listings across selected investment nodes — apartments, sectional title, high-liquidity urban markets with repeatable buy-to-let economics.
Property type, pricing range, location quality, and rental suitability filters remove the bulk of listings before deeper underwriting begins. The goal is focus, not volume.
Rental evidence is aggregated and normalised using comparables, unit characteristics, size adjustments, and confidence weighting. Optimistic asking rents are discarded in favour of defensible long-term baselines.
Cap rate, breakeven pricing, and 10Y return are computed under conservative assumptions — levies, rates, vacancy, and maintenance included. The objective is a realistic, repeatable outcome, not the highest theoretical return.
Deals are ranked by underwritten yield, pricing attractiveness, rental confidence, and evidence quality. Higher-ranked deals combine stronger cashflow, better pricing relative to income, and more defensible economics.
Financial Model
The model reduces each deal to its essentials. Underwritten Net Yield reflects net operating income after vacancy, maintenance, levies, and rates. Equity build reflects principal repaid through standard bond amortisation. No assumptions are made about rent growth or future price appreciation.
Understanding the Metrics
Annual rent divided by asking price, before costs.
Net operating income divided by asking price, after estimated levies, rates and operating costs, before financing.
Estimated long-term return including underwritten income yield and equity build-up assumptions (incl. financing).
YieldDNA’s 0–100 investment attractiveness score, based on underwritten returns, price gap, rental evidence and risk controls.
How strong the rental evidence is behind the rent estimate.
The price at which the deal meets YieldDNA’s underwriting thresholds. Helps identify overpriced listings and negotiation opportunities.
Verdict Framework
Why trust these numbers?
Every rent estimate is built from comparable rental listings in the same suburb and property category — not the landlord's asking rent, not an agent's projection, not a national average. Here's how:
Active rental listings in the same suburb and property type (apartment, sectional title, house) are gathered. Outliers are removed.
Comps are filtered to match the target unit's bedroom count and size band. A 1-bed apartment in Rosebank isn't benchmarked against a 3-bed house.
The estimate uses P30–P40 of the comparable range — not the median, not the mean. This deliberately anchors the estimate toward the lower end of achievable rents.
If fewer than 6 comps are available, or the size match is imprecise, or the distribution is wide, confidence is marked Low or Medium. A deal can only achieve High confidence with strong, consistent evidence.
If rental evidence doesn't meet the publication threshold, the deal is withheld or clearly flagged. We don't publish uncertain rent estimates as if they were reliable.
Rental confidence is suburb-specific. A dense rental market like Sea Point will have 20+ comps. A less liquid suburb may have 3. That difference is reflected in the confidence label and in the score — a deal with weak rental evidence scores lower, regardless of the headline yield.
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Full investment memos, rental evidence, operating cost breakdowns, sheriff auction intelligence, and saved workflow.
Discipline over volume. Transparency over complexity. Downside protection over optimism.
View ranked dealsContact Us
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| Opportunity | Asking | Gross Yield | Net Yield | |||
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| Auction opportunity | Auction date | Bid / reserve | Confidence | ||
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