Backend engineering

From MVP
to millions of daily users.

We design the distributed systems and pipelines that start small and hold when the load arrives. Fast iteration. Production that lasts.

MVP → millionsDistributed systemsProcessing pipelines

MVP → millions

The path we design for — first ship through daily scale, without a rewrite at every order of magnitude.

Fast iteration

Short cycles in production. The architecture stays coherent while you ship.

Senior only

The people who scope the work write the code. No bait-and-switch staffing.

Industries

The load we know.

AdTech

High-volume data pipelines

Ingest, enrich, and serve event firehoses at Weborama-scale — without silent drift.

Re-commerce

KYC and electronic wallets

Identity, payouts, and marketplace integrity. The Leboncoin class of problem: money and trust.

Social

Spiky load, many services

Notifications, feeds, graphs, ads. A BeReal-scale estate that has to hold when everyone opens the app.

What we build

Complex backends. Clear ownership.

01

Distributed systems

Microservice estates, social graphs, notification fabrics, feeds, and ads. Designed for failure and for the next spike.

02

Processing pipelines

High-volume ingest, streaming, and the jobs that turn raw events into something the product can trust.

Stack

The tools we reach for.

A short list, chosen because we have run them at the load this page talks about — not because they are fashionable.

Backend

Go

Honest about concurrency, fast to ship, boring in production. The default when the pipeline has to keep up.

Golang
Frontend

React + TypeScript

One component model from the first screen to the console operators live in. Types where the contracts matter.

ReactTypeScript
Mobile

React Native + Expo

Ship the client without a second backend team. Same language, native enough for social and marketplace apps.

React NativeExpo
Observability

Datadog, Prometheus, Grafana

If we cannot see the spike, we cannot ship the fix. Metrics, traces, and the graph on-call actually opens.

DatadogPrometheusGrafana
Data

The store matches the access pattern

Spanner when you need global truth. Cassandra and Couchbase for wide writes. Postgres for the ledger. Elasticsearch for search.

SpannerCassandraCouchbasePostgresElasticsearch
Prototyping

Claude Code + Grok Build

Shorten the loop from idea to a running slice. Then we keep the contracts and throw away what should not last.

Claude CodeGrok Build

Approach

Reliable through fast iteration.

01

See it

Map the load, the failure modes, and the constraint.

02

Ship it

Short cycles. Visible progress. Production weekly.

03

Own it

SLOs, runbooks, a system your team can operate.

FAQ

Before the first call.

What do you build?

Distributed systems and processing pipelines — the backends behind AdTech, re-commerce, and social at millions of DAU. Not product UI. Not branding.

Who is this for?

Teams on the path from first version to millions of DAU. If the system will be load-bearing, that is the work.

How do you move?

Short cycles in production. We embed, ship weekly, and leave a system your engineers own. The people who scope the work write the code.

What does an engagement look like?

A short diagnostic, then weeks of shipping — not a six-month black box.

Start a project

Where is the load.

The system, the spike, the constraint. We reply ourselves.