Software engineering for growing companies

We design and build software that holds up at scale.

Custom platforms, cloud infrastructure, and system integrations — from enterprise ERP and medical diagnostics to AI agents and connected devices.

Enterprise ERP · Healthcare · IoT · AI · SaaS
You own the code and the IP NDAs and MSAs welcome Works inside your existing stack

Selected work

Systems already running in production

Every engagement below was scoped, built, and shipped end to end — not prototyped and handed off.

Discuss your project

Enterprise ERP

Argus Enterprises Serv Group

Senior Software Engineer

Two enterprise ERP platforms built and deployed on AWS, with infrastructure defined as code and serverless services behind the internal tooling their teams use daily.

TypeScript AWS CDK Serverless IaC

Medical diagnostics

Targeted Bioscience

Senior Software Engineer

Diagnostic workflow tooling for lab teams, including an image processing pipeline and Python services exposed through a REST API.

Python FastAPI Image processing REST

Recruiting platform

SkillMil

Senior Software Developer

Full-stack delivery on a workforce platform, including AI chatbot agents running in production to guide candidates through matching and applications.

React Node.js AI agents

Performance testing SaaS

Relampo

Cofounder

A load testing product built from scratch: a CLI engine written in Go that runs YAML-defined scenarios, plus the SaaS platform around it.

Go CLI SaaS Distributed

Smart home technology

Digital Lifestyle Designs

Design and build

Visit

Multi-page marketing site with a full service catalog and contact flow.

Next.js Tailwind

What we do

Engineering capability, scoped to the problem

We work across the whole stack — product, backend, infrastructure — so the architecture decisions and the code that implements them come from the same place.

TypeScript · Python · Go · React · Node.js · AWS · GCP
Minimal designer workspace — laptop, notebook, and coffee on a light desk

Senior-led

The person scoping it is the person building it

Custom platforms
Internal tools, customer-facing products, and the systems your operation actually runs on — designed, built, and shipped end to end.

Where most engagements start.

Cloud & infrastructure
AWS and GCP environments defined as code with AWS CDK — serverless services, repeatable deployments, and infrastructure your team can reason about.
APIs & system integration
Connecting the systems that were never meant to talk to each other: ERPs, third-party vendors, internal services, and the data moving between them.
AI agents & automation
LLM-powered agents and chatbots running in production, wired into your real data and workflows — not a demo that breaks under load.
Data & connected devices
Pipelines, image processing, and IoT platforms that collect, move, and make sense of data from devices and systems in the field.
Performance & modernization
Legacy systems rebuilt or brought forward, slow paths profiled and fixed, and load testing to prove the system holds before your users find out.

How we engage

Scoped before it is built.

You do not need a finished spec to start the conversation. Bring the problem and the constraints — turning that into an architecture and a plan is part of the work.

Modern workspace with a laptop, coffee, and notebook

Week 1

Scope, architecture, and a written plan

Ongoing

Reviewable increments in your repo

Handover

Documented, deployed, owned by you

Nothing built before it is approved
01

Technical call

We walk through the problem, the systems already in place, and the constraints. You get an honest read on feasibility — including when the answer is that you should not build it.

02

Scope and architecture

A written proposal: what gets built, how it fits your stack, the sequence, the risks, and a fixed price or rate. Nothing starts before you approve it.

03

Build in visible increments

Work lands in your repository in reviewable pieces, with a standing check-in. You see progress continuously instead of waiting for a reveal.

04

Ship and hand over

Deployed, documented, and transferred to your team — infrastructure as code, so nothing critical lives only in someone else’s head.

Have a system that needs building or fixing?

Start with a technical call. You will leave it with a clearer picture of the problem whether or not we work together.

Book a technical call

Engagement

Three ways to work together.

Which one fits depends on how well defined the work already is. Most companies start with discovery and decide from there.

Scope and cost agreed before work starts

Discovery & architecture review

A short, fixed-scope engagement that ends in a written technical plan: architecture, risks, sequencing, and cost. Useful on its own, and it de-risks everything after it.

Engagement model

Fixed fee

Project delivery

A defined system built and shipped end to end against an agreed scope, with milestones you approve as they land.

Engagement model

Fixed scope

Embedded engineering

Senior capacity inside your team on a monthly basis — your roadmap, your standups, your repository. Best when the work is ongoing rather than a single deliverable.

Engagement model

Monthly retainer

What shapes the estimate

Pricing follows the shape of the system, not a rate card. These are the variables that move it most, and all of them get settled during discovery.

System complexity Existing codebase and stack Integrations required Compliance and security needs Cloud footprint Timeline and team overlap

FAQ

Common questions

What engineering leaders and operators usually want settled before the first call.

How do you work with an in-house engineering team?

We work inside your setup, not alongside it — your repository, your branching model, your review process, your ticket tracker. On embedded engagements we join standups and take work off the same board your team does. The goal is that our commits are indistinguishable in process from anyone else on the team.

Who owns the code and the intellectual property?

You do. All work is delivered as work-for-hire: the code, the infrastructure definitions, and the documentation are yours from the first commit. We are happy to work under your MSA, or to sign an NDA before the first technical call.

Can you take over an existing codebase?

Yes, and a good part of the work we do is exactly that — inheriting systems, mapping what is actually there, and modernizing or extending them without a rewrite nobody asked for. The first deliverable in those cases is usually an honest assessment of the current state.

What does the discovery engagement produce?

A written technical plan: the proposed architecture, how it fits the systems you already run, the sequence of work, the risks we see, and what it will cost. It is a standalone deliverable — you can take it to another vendor or build it internally, with no obligation to continue with us.

What technologies do you build with?

Primarily TypeScript, Python, and Go, with React and Angular on the front end and Node.js or FastAPI on the back. Infrastructure runs on AWS or GCP, defined as code with AWS CDK. When you already have a stack, we work in it rather than arguing for ours.

How do you handle security and compliance requirements?

They get treated as constraints on the architecture from day one, not as a review at the end. We have built in regulated contexts — including medical diagnostics — and are comfortable working under access controls, audit requirements, and customer security reviews.

How quickly can you start?

Discovery engagements can usually start within a week or two. Larger builds and embedded work depend on current commitments — the technical call is the fastest way to get a real answer on timing.

Get in touch

Tell us what you are trying to build.

Send the problem, the systems already in place, and your timeline. We will come back with an honest read on feasibility and the shape an engagement would take.

NDA before the call if you need one. No sales pitch either way.

The first call is a technical conversation, not a discovery form. Bring your engineers if you have them — the more specific the problem, the more useful the answer.