EFIP reads your statements, invoices and receipts, sorts the transactions itself, catches the subscriptions and costs that quietly slip through — then answers questions about your money in plain sentences, not spreadsheets.
The demo opens the real dashboard on a public account. No signup, no card.
78
transactions processed
24
merchants recognised
5
subscriptions detected
9
spending categories
Every number on this page comes from the demo account — none of it is invented.
Below is the real state of the demo account: the same numbers you get when you click "Open the demo".
Period
Jan 2026 — Jul 2026
Average monthly spend
£1,647
Income
£23,010
Expenses
£11,532
Net saved
£11,478
49.9% savings rate
Financial health
100
out of 100
£1,133.16 per year
Account balance
£3,578.68
Barclays
£2,450.21
Monzo
£1,128.47
The analyst does not guess. Before it answers it pulls real rows from your database — sums transactions, checks categories, compares months.
Where am I burning the most, and what can I do about it?
I went through every transaction in the demo period. Three things stand out:
Want me to turn this into a monthly budget and set the alerts up?
The answer above illustrates a conversation over the demo data. The analyst always computes from your transactions, never from the model’s general knowledge.
The same engine — different questions it answers.
Operating costs, SaaS tools, invoices and receipts in one place — ready for the conversation with your accountant.
Instead of a manual spreadsheet — a history that organises itself and tells you what changed.
Four steps. The first takes a minute, the system does the rest.
CSV, XLSX or PDF from your bank. Columns are detected automatically, so there is no manual mapping.
Bank gibberish becomes readable names, and re-imported rows are caught before they clutter the history.
Category, merchant, subscription, recurring payment — assigned automatically, correctable with rules.
Dashboard, forecasts, alerts and an AI analyst computing over your transactions.
The modules shipping today — exactly the ones you will see in the demo.
Transactions
Full history with filters, search and bulk editing.
Categories and rules
Your own categories plus rules that assign them automatically.
Merchants
A profile per merchant: how much, how often, since when.
Subscriptions
Detected recurring payments with monthly and annual cost.
Reports
Period breakdowns with export and saved views.
Trends
Period comparison and shifts in your spending mix.
AI analyst
A conversation over real data, with conversation history.
Forecasts
Spending and savings projected 3, 6 and 12 months out.
Alerts
Unusual spend, blown budgets and risks caught on their own.
Budgets
Category limits with usage tracked over time.
Accounts
Multiple accounts and banks in one balance picture.
Statements
Import history, duplicate detection and a preview before saving.
Receipts and invoices
Documents linked to specific transactions.
Profiles
Separate data spaces with a switcher in the dashboard.
Finances are not something to hand to someone else’s server.
Runs on your infrastructure
App and database sit wherever you decide — fully on your own hardware if you want.
Pick your AI model
OpenAI, Anthropic, Google or a local Ollama. With a local model nothing leaves your network.
Email or Google sign-in
Hashed passwords, signed sessions, access scoped per profile.
Profile isolation
Every query is scoped to the active workspace — company data never mixes with personal.
Honestly: not in the demo yet, but on the plan.
Company mode
A separate data model for a registered business.
VAT intelligence
Recognising tax rates and amounts on documents.
Business dashboard
A view built around company costs and cash flow.
Receipt OCR
Reading line items off a receipt and attaching them to the transaction.
The demo account is open. Go in, click around, ask the analyst something.
The demo is read-only — you can browse everything without breaking anything.