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AI Native Product Engineering

AI native product engineering for modern businesses. We design, build, and operate the systems your company runs on.

99.99%Platform uptime
42msp99 API latency
4Cloud regions
1.2M+Requests / day
Engineering philosophy

How we decide what to build, and how.

Four commitments that survive contact with a deadline.

01

Correctness is a feature.

A system that is fast and wrong is just wrong sooner. We pick the guarantee first — ordering, consistency, durability — and then make it fast inside that constraint.

02

Boring infrastructure, ambitious products.

Postgres, Go, containers, Terraform. We spend our novelty budget on the product surface, not on the parts that page someone at 3am.

03

AI that reasons over facts, not vibes.

Models narrate; they don't compute. Every number an AI feature reports is derived deterministically before the model ever sees it, and every claim traces back to its source.

04

Own the thing you ship.

The engineer who builds a service runs it. That closes the loop between the design decision and the pager, which is the only thing that reliably produces good design decisions.

Technology

The stack we bet on.

Chosen for operational boredom, not for the changelog.

  • GoServices
  • TypeScriptWeb
  • Next.jsFrontend
  • FlutterMobile
  • PythonAI / data
  • PostgreSQLSystem of record
  • RedisCache / presence
  • KubernetesOrchestration
  • DockerPackaging
  • TerraformInfrastructure
  • GCPCloud
  • gRPCTransport
Testimonials

Teams we've built with.

They rewrote our sync layer in six weeks. What shipped had fewer moving parts than what we asked for, and it has not paged anyone since.

Priya RaghunathanVP Engineering, Kestrel

The first thing they did was tell us the feature we'd scoped was the wrong one. They were right. That conversation saved us a quarter.

Daniel OkonjoCTO, Northwind Labs

Most vendors hand you a repo and vanish. Synops handed us runbooks, dashboards, and an on-call rotation that our own team could actually take over.

Mira HalvorsenHead of Platform, Ardent
Open source

The parts worth giving away.

When we solve something general, it leaves the building. These are extracted from products we run in production.

synops/relay

Ordered, resumable WebSocket fan-out for Go. The sequencing core extracted from Mesh.

Go2.4k138

synops/ledger

Deterministic double-entry accounting primitives with exact decimal arithmetic.

Go1.1k74

synops/evals

A test runner for LLM pipelines. Assert on behaviour, gate the prompt change in CI.

Python3.8k291

Let's build something that lasts.

Tell us what you're working on. We'll tell you honestly whether we're the right team for it.