From a Side Project to a Product: Introducing LodyCDP

LodyCDP did not begin as a product. It started as a personal project, a place where I could learn, experiment, and explore a question I kept coming back to: how can we better understand what people actually do on a website?

Over the years, I ran different versions of it on several real websites. It collected page views and events, helped me investigate customer journeys, and showed me where people continued, converted, or dropped off.

The project kept evolving as I learned. I tried different ways of collecting data, presenting it, and turning it into something genuinely useful. Some ideas worked. Others did not. For a long time, LodyCDP was less of a finished system and more of a living laboratory.

That was valuable, but it also meant the project was never quite ready for anyone besides me.

The arrival of better AI tools changed that. They helped me work through the long list of things separating an internal project from a real product: refining the experience, improving the documentation, finding gaps, and completing many small but important details. AI did not replace the years of work behind LodyCDP, but it gave me the leverage I needed to finally bring all those pieces together.

Today, LodyCDP is a customer journey analytics product. It captures page views and meaningful product events in real time, helping website and product owners understand how visitors move through their experience. Instead of looking only at isolated numbers, you can explore journeys, conversion, and drop-off and investigate new questions using data that has already been collected.

One of its main features is AI-assisted event discovery. Deciding what to track is often one of the hardest parts of setting up analytics. LodyCDP can examine a public website or product and suggest meaningful interactions worth measuring. These suggestions are expressed as clear tracking rules, and nothing starts recording until the site owner has reviewed and approved them. AI helps with discovery, while people remain in control of what is collected.

That control is part of a broader privacy-first approach. LodyCDP is designed to help businesses understand activity in their own products, not to create advertising profiles or follow people across the internet. It focuses on deliberate event collection rather than session replay, excludes sensitive values from AI event proposals, and does not sell customer analytics data or use it for unrelated advertising. Customers decide what to measure and who can access their data.

LodyCDP is built and operated in Singapore by Aagee AI Pte Ltd. Building the company here has shaped how I think about responsibility and trust. Our data protection policies are grounded in Singapore's Personal Data Protection Act, with clear commitments around responsible collection, use, disclosure, protection, and deletion of data. Privacy is not something added at the end; it is part of how the product is designed and operated.

This release feels different from starting something new. It is the result of returning to the same idea for years, testing it, learning from it, and slowly making it better. What began as an experiment running quietly on a handful of websites is now something I can finally share as a product.

LodyCDP is still evolving, and there is plenty more I want to build. But it has reached an important milestone: it is no longer just my experiment.

It is ready for other people to use.

check it out here