Stop waiting on engineering to build personalization.
You own conversion, engagement, and retention. But every personalization initiative you launch ends the same way — stuck in a backlog behind pipeline work, model training, and infrastructure you have no control over.
NEXTGRES gives product and growth teams a personalization engine they can operate directly. Define audiences in natural language. Preview experiences before they ship. Understand every recommendation. Ship in hours — not quarters.
Today personalization takes four teams and six months.
With NEXTGRES — you and an afternoon.
Here's what launching personalization actually looks like:
You define what you want to personalize. You write a brief. You meet with analytics to scope the data and audit what exists. Half the signals you need live in systems nobody owns.
Data engineering builds a pipeline to get the right signals into the right system. This alone takes two months — because it depends on other teams' backlogs and priorities that aren't yours.
Data science and ML engineering experiment with features and models. They iterate. They retrain. You wait. You check in. You wait more.
Software engineering integrates the model into your product. QA. Staging. Deploy. Six months in and you haven't learned a thing yet. And that's if nothing slipped.
Connect to your existing databases and event streams. Read-only — your source systems are never modified.
NEXTGRES automatically analyzes your data, determines the right models and features, and builds them. No tickets filed. No teams engaged.
You're previewing personalized experiences, defining audiences in plain language, and watching live recommendations.
NEXTGRES runs data ingestion, feature engineering, model training, and decision serving inside a single unified system.
See how the architecture works →Move the metrics you're accountable for — starting week one.
Our approach drives measurable lift across conversion, engagement, and retention within weeks of deployment.
Most recommendation engines need weeks of behavioral data. New users from your best campaigns land on generic onboarding and bounce.
NEXTGRES builds synthetic personas from your existing users and matches new users from their very first click. The first session is personalized — not a coin flip.
A user skips a category, abandons a cart. In a pipeline-based system, that signal arrives hours later. By then, they've seen five irrelevant recommendations and disengaged.
NEXTGRES reflects behavioral changes in real time — because the models and the data live in the same system. What your user did at 2:04 PM shapes what they see at 2:05 PM.
The dropped session, the preference shift — these predict churn. In a fragmented stack, they sit in an event stream your personalization layer doesn't read. By the time a batch process surfaces them, the user is gone.
NEXTGRES reads behavioral signals and acts on them in the same system, in real time. The intervention reaches the user before the session ends.
See everything. Explain everything. Control everything.
Built by practitioners, not theorists.
We've built and scaled personalization systems serving hundreds of millions of users
behind the scenes at some of the world's most recognized brands.
See what owning personalization actually looks like.
Watch how growth and product teams use NEXTGRES to define audiences in natural language, simulate experiences before they go live, and understand every recommendation — without a single engineering ticket.
Your first pilot takes hours, not months.
We're onboarding a select group of product and growth teams. Connect to your existing data and see personalized recommendations the same day.