Layered demo
Three layers for two audiences on a quantitative platform
A portfolio platform has to convince a business buyer and a quant, and they cannot be shown the same thing. I packaged the pitch, the library and the notebooks as three separate entry points.
- Pitch, library and notebooks — one per audience
- 3 layersPitch, library and notebooks — one per audience
- The library ships with a test suite and CI, not as a notebook dump
- Tested and containerisedThe library ships with a test suite and CI, not as a notebook dump
- Results always shown next to the conventional approach, never alone
- Against a baselineResults always shown next to the conventional approach, never alone
The client
Institutional portfolio management — an audience split between decision-makers who need the economics of a systematic approach and quantitative researchers who will judge the whole thing by the optimiser and the backtest.
The engagement
One capability presented as three layers, each aimed at a different reader, with an explicit instruction about which to open first.
The problem
Quantitative capability is uniquely easy to demonstrate badly. Show the business audience a notebook and they see nothing; show a quant a dashboard with a flattering equity curve and they stop listening, because they know exactly how easy that curve is to manufacture. One artefact cannot do both jobs, and pretending otherwise loses both rooms.
What I did
I separated the layers and told people where to start. The commercial layer argues the case in prose — architecture, what the optimisers do, where the data comes from — and is the stated entry point for a client conversation. The library is the credibility layer, and it earns that by being installable, tested, containerised and wired to continuous integration rather than by being a folder of scripts; a quant reads that as a team that ships. The notebooks are the transparency layer, showing the pipeline from data through factors and regime analysis to optimisation, so the method can be interrogated rather than trusted. And every result in the dashboard appears against a conventional baseline with risk-adjusted metrics, drawdown and turnover, because a return shown alone is not evidence and a professional audience knows it.
What was built
Three layers — a written analysis covering architecture, optimisers and data integrations for the commercial conversation; an installable library implementing portfolio optimisation including hierarchical approaches, backtesting, metrics and loaders for the standard market data sources, with a test suite, container and continuous integration; and a set of research notebooks walking the full pipeline from data through factors and regime analysis to optimisation — plus a dashboard surfacing the risk-adjusted result against a conventional baseline.
On the table at the end
- Written marketing and architecture analysis
- Installable optimisation and backtesting library with tests, container and CI
- Research notebooks covering the full pipeline
- Comparison dashboard: risk-adjusted metrics, equity curves, drawdowns, allocations
What it changed
Let a single capability be sold twice without dilution: the business reader gets an argument, the quant gets a library with tests and a container, and neither is asked to sit through the other's material.
How it ran
- 01
Split by reader
A prose analysis, a library and notebooks — each written for the person who will actually open it.
- 02
Name the entry point
The written analysis stated as where a client conversation starts, so nobody opens a notebook in a boardroom.
- 03
Make the library shippable
Installable, tested, containerised, on continuous integration — which is how a quant reads seriousness.
- 04
Show the pipeline, not the result
Notebooks covering data, factors, regimes and optimisation, so the method can be interrogated.
- 05
Always against a baseline
Risk-adjusted metrics, drawdown and turnover next to the conventional approach — a curve alone is not evidence.
Other work
All case studies →- Financial planning software
Showing the operator's console, including where the prompts live
A planning platform demo that switches from the customer's view to the vendor's — tenant health, system status, and a sandbox where the AI's prompts are edited. That last screen is the one that sells.
- Insurance
One product, two audiences, one prototype
An annuity platform has an administrator who lives in it all day and a customer who opens it twice a year. I built both, because the demo that shows only one always gets the same question.
- Professional services
A demo library instead of a demo
Every presale was building its prototype from scratch. I catalogued fourteen of them by theme so the next one starts from an asset rather than an empty repository.
Something similar on your plate?
Thirty minutes, no deck. I will tell you whether it is worth doing at all.