Engineering partnership. Velocity that lasts. Systems that work.

We embed senior architects and engineers with your team. Product delivery, platform foundations, and architecture built for AI-speed development. We help teams use coding agents without losing control of quality, ownership, or long-term system health.

See the Blueprint
Companies we've worked with
  • XM Cyber
  • Astrix
  • Elementary
  • Sentra
  • Binah
  • Vetric
  • Nimble
Beyond Headcount

We don't replace engineers. We upgrade the system they operate in.

01

Application Delivery

The Core

From roadmap to production, without trading away quality.

We embed with your engineers to ship production software, making AI-written code accountable through specs, tests, reviewable diffs, and durable release paths.

  • Feature Delivery
  • API Implementation
  • Third-Party Integrations
  • Data Migrations
  • Test Coverage
  • Performance Profiling
  • Jobs & Queues
  • Debt Paydown
02

Platform & Agentic Engineering

The Foundation

Paved roads for fast teams and AI-assisted delivery.

We build repeatable delivery foundations: CI/CD, infrastructure as code, observability, developer workflows, and AI guardrails that make agentic changes reviewable and boring.

  • CI/CD Pipelines
  • Infrastructure as Code
  • Environment Parity
  • Observability
  • Developer Workflows
  • AI Coding Guardrails
  • Agentic Workflow Setup
  • Test & Review Gates
03

Systems Architecture

The Multiplier

The architecture that survives success.

We design backend foundations, service boundaries, API contracts, and data layers so AI-assisted change lands inside systems built to verify it, not absorb debt.

  • Service Boundaries
  • API Contracts
  • Domain Modeling
  • Data Model Design
  • Event-Driven Architecture
  • AI-Assisted Engineering Controls
AI-Ready Engineering

AI-ready engineering starts with the system around the code.

Coding agents raise output. Without clear work, strong verification, and platform discipline, they move cost into review, testing, and maintenance.

See the AI engineering readiness model
01

Make Work Executable

Turn strategy, repo context, acceptance criteria, and ownership into tasks humans and agents can execute.

02

Verify Changes Early

Use tests, CI, review, and release signals to catch AI-assisted risk before production.

03

Build the Agent-Ready Platform

Route agents through trusted commands, environments, docs, tickets, permissions, and observability.

Velocity dies the same way everywhere.

These aren't people problems. They are system design problems. AI just makes the weak spots show up faster.

Technologies we work with

TypeScript
Node.js
NestJS
React
GraphQL
Kubernetes
AWS
GCP
Terraform
Python
PostgreSQL
MongoDB

Engineering partnership. Velocity that lasts.

30 minutes. No pitch. You'll talk to an engineer.