Data and reporting for wealth managers and IFAs
Every platformone set of columns
A dashboard is only as honest as the feed behind it. One platform sends a CSV. Another sends a PDF that looks like a CSV. The columns mean slightly different things. Somebody decides what a valuation date means, and that decision holds everywhere. Do that once and the numbers stop needing a covering note. Ongoing fee, funds under management, drift against the model, and the risk score that Dynamic Planner gave it.
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What actually slows wealth managers and IFAs
The fact-find gets entered more than once
It starts in the meeting, on paper or in a form. Then it goes into Intelliflo or Curo, then into Voyant for the cashflow, then into the suitability report. Each system wants it in its own shape, so somebody retypes it and somebody else checks the retyping.
Annual reviews come in a wave
Anniversary dates bunch up, because clients were taken on in bunches. The pack, the valuation, the refreshed cashflow and the file note all want doing at once, and the tax year end sits on top. Then it goes quiet until the next batch.
Consumer Duty evidence lives in nobody's system
The work happens. The vulnerability note is in an email, the value discussion is in a file note, the reason behind the recommendation is in somebody's head. Pulling that together for a file check means opening several systems and hoping the person who wrote it is still here.
Every platform reports in its own format
Transact sends one thing, the next platform sends another, and the columns never line up. Somebody downloads them, pastes them into a spreadsheet, and squares the ongoing fee against what actually arrived. The performance figures then get pulled again from FE fundinfo, and the risk mapping again from Dynamic Planner.
data, modelling and reporting
A dashboard request is usually an argument about what counts as won and when a month ends. Have it, write it down, and then the pipeline. Data pulled from the source systems, features built from it, parameters searched, and the model tested against data it has never seen.
- Definitions agreed before anything gets built
- What counts as a customer, an order, a live account, and when a month ends. Also the fields that are typed too loosely to count, which is why two reports on the same week disagree.
- A number you can trace to source
- Each figure on the report opens onto the query and the rows behind it. Challenge a total in a meeting and you can show the working there and then, instead of going away to check.
- How often the model gets it wrong
- The model is checked on data it never saw in training, and scored against a plain average. Now and then it loses, and you get told, which saves you building on top of a guess.
Selected projects
Products I built and open-source projects I maintain. Open a project to see the work for yourself.
- 012026
Dr Flavia Pretti Aslanian
Healthcare · Practice site
A bilingual dermatology website for a practice in Harley Street and Wimbledon
A new landing page guides patients to medical, aesthetic and surgical care. The practice edits its own content, and staff have a password-protected dictation tool in the same app.
- Next.js
- Sanity CMS
- Tailwind v4
- Radix
- Motion
- ISR
- Railway
- Cloudflare
Design · Build · Deploy
- 84 published English and Portuguese routes
- 72 treatment pages with clinic-editable content
- Custom before/after comparison UI
- Internal clinician dictation tool
- 02
2025 →Delta Xi
E-commerce · Brand
A mathematics apparel brand on a storefront I wrote from scratch
I built the cart, checkout, product recommendations, affiliate programme and support desk, and run the infrastructure myself.
- Next.js
- React Server Components
- Stripe
- Auth.js
- Tailwind
- Umami
- Chatwoot
- Cloudflare
Founder · Engineer · Operator
- Custom checkout on Stripe + Klarna
- Server-rendered recommendation engine
- Self-hosted analytics and live chat
- 50+ STEM explainers driving organic search
See 4 more projects
- 03
2026Continuum
Web3 · DeFi protocol
A Solana DeFi protocol for 24/7 synthetic exposure to real-world assets
Deposit USDC, mint matched long and short tokens at NAV, sell the leg you don't want. A constant-product invariant keeps the pair redeemable back to the deposit.
- Rust
- Anchor
- Solana
- TypeScript
- Pyth
- Next.js
- Bun
- Railway
Pre-mainnet. Devnet markets, audits pending.
Protocol · Frontend · Infra
- 5 Solana smart contracts in Rust
- 8 synthetic markets on devnet
- 4-state oracle risk machine
- Volatility-scaled fee curve
- 042026
Dray
AI tools · Product website
A product website for keeping project context across AI agents
An editorial landing page introduces shared project context, shows illustrative agent workflows and explains setup and privacy ahead of beta.
Beta coming soon. The public demos illustrate the workflow; they are not live agent connections.
Design · Build
- Interactive agent-linking illustration
- Project-context walkthrough
- Setup and privacy guidance
- 05
2026Tallylamp
Open source · Browser infrastructure
A browser for AI agents that you can watch and take over
I built the browser service, dashboard, MCP server and public website. Agents use Chrome on your server while you watch the same browser live. Take control to sign in, then hand it back; saved profiles carry between sessions.
- TypeScript
- Next.js
- Chrome
- MCP
- SQLite
- Docker
- Railway
Public site at tallylamp.dev. The browser service and dashboard are self-hosted.
Creator · Engineer · Maintainer
- Live viewing and explicit human handoff
- Separate agent permissions and reusable profiles
- MIT licensed, with a Railway deploy template
- 06
2025 →CarClout
SaaS · AI content engine
A subscription app that turns a phone photo of a car into something worth posting
Upload a photo, pick a template, get the edit back a moment later. Thirteen AI models sit behind a metered credit ledger, next to a layer editor, a post scheduler and a live chat room.
- Next.js
- SurrealDB
- Auth.js
- Stripe
- fal.ai
- Cloudflare R2
- Stream.io
- Railway
Engineering · Infra · SEO
- 724 generated landing pages, all live
- 128 API routes behind one app
- 13 AI models on a metered credit ledger
- Instagram posting, scheduling and analytics
One runs on the client's own domain and one is internal to theirs, so there is nothing here of mine to show you.
- ClientJooyontechAI sales assistant, Korean and English
- ClientPHFWeb, AI and automation · private medical practices, UK
Not everything is public. A fair amount of the work sits in private repositories I cannot hand you a link to. Ask, and I will walk you through it.
Ask to see moreHow a project runs
- 01Before code
Scope
One call, then a written spec. What it does, what it deliberately does not do, and what milestone one is. You sign that off before I write a line.
- 02Early
First deploy
A narrow slice that actually works, running where it belongs. A URL you can open, a build on your phone, a job on your own servers. Real data, real hosting, no placeholder screens.
- 03Ongoing
Build in the open
Deploys land as the thing fills in, not in one drop at the end. You watch it happen. And you get to change your mind while changing it is still cheap.
- 04Handover
Yours to run
The product runs in your accounts, with the domain, hosting and documentation under your control. Source-code transfer is quoted separately; we agree what is included during scoping.
Rafael Aslanian
I got my hands on a computer at 6 and never really stopped.
Now it is decentralised finance, tokenising real-world assets and topological deep learning, then building whatever those turn into. Continuum came out of that. So did Delta Xi (δξ, an infinitesimal change in a random variable).
Bossa nova and MPB were always on at home, so I sang before I played anything. Guitar and piano came later, then jazz.
- Based
- London, UK
- Languages
- English, Portuguese; intermediate Spanish and Chinese
- Focus
- Web3, DeFi, real-world asset tokenisation
- Also
- Music
Have an idea? Tell me.
Need the audience too?
I can build the thing. Getting people to notice it is a separate job, and not mine. For that I work with Nytforge, who film, edit and put the work in front of a local audience. They are strongest with automotive and local businesses.