Cervo — Making Personal Finance Understandable

Cervo is a personal finance management product designed to bring fragmented financial information into one coherent workspace.

The product consolidates accounts, transactions, and balance snapshots, helping users understand their financial position without manually reconciling information across different sources.

My work spans product strategy, information architecture, interaction design, financial data modelling, and AI-assisted product development.

Managing money across multiple accounts creates a problem that conventional dashboards don’t fully solve.

Transactions arrive in different formats. Transfers between personal accounts can be mistaken for expenses. Historical balances don’t always align with transaction records. Import errors can undermine confidence in the entire system.

The challenge was to design a product that could accommodate complex financial data while keeping everyday interactions straightforward.

The central product question became:

I worked across the product lifecycle, connecting financial workflows, interface decisions, data structures, and implementation.

My responsibilities included:

Defining the product scope and prioritising core workflows

Designing the account and transaction information architecture

Structuring transaction import and reconciliation experiences

Defining error handling and data correction behaviours

Developing and iterating on the product using AI-assisted tools

Reviewing implementation quality and identifying gaps between intended and actual behaviour

A visually polished dashboard is of limited value if the underlying numbers cannot be trusted.

I prioritised the relationships between accounts, transactions, and balance snapshots before expanding the reporting experience.

This established a clear product principle:

Importing financial history is not simply a file-upload interaction.

A useful import workflow needs to handle inconsistent formats, duplicate records, large datasets, and errors that users may not know how to diagnose.

The product direction therefore included support for large transaction histories, clearer validation, and automated correction of recoverable errors.

The goal was to reduce manual cleanup without hiding uncertainty or silently changing financial records.

Moving money between personal accounts should not automatically count as spending.

Similarly, transaction history and balance snapshots represent related but different financial information.

Separating these concepts in the product model helps prevent misleading totals and supports more meaningful financial analysis.

Users should not need to understand the underlying data architecture to maintain accurate records.

I focused on making common tasks understandable: reviewing transactions, checking balances, identifying discrepancies, and correcting information.

The interface should expose complexity when a decision requires it, rather than forcing users to manage that complexity continuously.

Cervo brings together three connected layers:

Accounts — a consolidated view of financial sources and balances.

Transactions — a structured history of financial activity, including the relationships between accounts.

Balance snapshots — historical reference points for understanding how financial positions change over time.

These layers form the foundation for reconciliation, analysis, and future automation.

The product is being developed through an iterative workflow that combines product reasoning, UX design, implementation, and validation.

The working dataset includes:

The import architecture is being developed with a target of handling more than 50,000 transactions, alongside improved error recovery and data consistency checks.

These figures describe the current working scope and technical targets, not customer adoption or measured business outcomes.

Cervo reflects my approach to designing products in complex domains.

I start by identifying the underlying system and the decisions users need to make, then design the interface around those relationships.

The most important work often happens before the screens: defining data boundaries, resolving ambiguous states, prioritising failure modes, and determining what the product should automate.

Cervo is an actively developed product.

Current priorities include validating large-scale transaction imports, improving automatic error recovery, removing demonstration data, and strengthening end-to-end consistency between accounts, movements, and balances.

The next milestone is a more reliable working product, with financial correctness and everyday usability taking priority over additional dashboard features.