Valyrify is a property-investment platform for UK buy-to-let investors. Most property tools guess at a yield and call it analysis; its founder wanted something that couldn't get away with that — a platform where every figure had to hold up against real lending and property expertise, not just look plausible on a dashboard.
We built it: deal appraisal, portfolio stress-testing, full UK tax treatment across personal and company ownership, lender coverage tests pegged to actual PRA convention, and a valuation model reconciled to real market cap rates. The whole platform ran on an AI-orchestrated stack — Claude Code architecting and writing the engineering, Claude Design shaping the interface, Lovable carrying it to a live, deployable product — and went from first architecture decision to a verified platform in under three weeks.
Buy-to-let math looks simple from the outside and isn't. A defensible appraisal has to stress a mortgage the way a lender actually would, not with an invented safety margin; it has to run personal and corporate tax correctly, including the Section 24 relief restriction most calculators quietly skip; and it has to band SDLT and corporation tax properly instead of flattening them into one rate that's wrong at every threshold.
None of that is normally fast to build. Getting it right usually means trading speed for rigor — a founder either ships quickly with a shallow model, or gets a defensible one built slowly, at a cost that doesn't suit an early-stage build.
We ran the build end to end on three tools working together. Claude Code architected and wrote the calculation engine itself — one deterministic, config-driven module kept deliberately apart from the interface, so every assumption (SDLT bands, tax thresholds, stress-rate conventions) lives in a single reviewed block instead of scattered logic, with a bisection solver underneath handling every “what's the breakeven?” question the product needs to answer. Claude Design shaped the product's interface and visual system. Lovable took the engine and design work and carried it through to a live, deployable platform.
Moving fast didn't mean cutting the rigor. We built an independent, live-formula Excel model to cross-check the engine's output figure for figure, then walked the founder through a comment-by-comment technical review of both the model and the product — the same standard of scrutiny a chartered surveyor or accountant would apply, compressed into a build measured in weeks rather than months. The same discipline shaped the valuation methodology, reconciling a Gordon Growth valuation to real market yields using a property-specific risk premium the founder proposed and we implemented to the decimal.
The real result here isn't the speed on its own — it's that the speed didn't cost anything on the rigor side. Every load-bearing number in Valyrify went through the same level of technical scrutiny a much slower, much more expensive build would have demanded, and the platform still moved from architecture to a shipped product in under three weeks.
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