Problem
Invoicing software has to handle everyday administrative work reliably while adapting to changing business, currency and regulatory requirements. AI assistance is only useful when it understands that product context.
Current Deliverists.IO product
Quento: Building invoicing and AI assistance around real business workflows
An invoicing platform with AI-assisted workflows, multi-currency support and tools for companies working locally and internationally.
Case study
From product problem to working software
My contribution
My work includes product direction, architecture, implementation, AI and agent integrations, and ongoing product development.
Co-built with the Deliverists.IO team.
Product decision
Build AI assistance into the invoicing product and its business data instead of treating it as a separate chat demonstration.
Implementation
A web product combining invoicing, company data, multi-currency support and AI-assisted workflows, designed so the operational core and assistance can evolve together.
Practical outcome
A working Deliverists.IO product used to test and improve invoicing and administrative workflows through real product development.
Lessons carried forward
- Domain context matters more than a generic AI interface
- Operational reliability remains the foundation of an AI-assisted product
- Product feedback should guide where automation earns further investment
Attribution
Clear about the boundaries of the work
Co-built with the Deliverists.IO team.
This page describes Grzegorz Smajdor's contribution and publicly shareable product context. It does not claim sole authorship or undisclosed client metrics.
Start with the situation
Let’s find the most practical next step for your product
Tell me what you are building, what is currently blocking progress and what outcome you want to achieve. During the first conversation, we will clarify the situation, identify the most important risks and decide whether I am the right person to help.