Backend systems built to last.
System's core infrastructure, security frameworks, and application foundations.
- A core service is fragile under load, and nobody wants to be the one who touches it.
- The roadmap needs a backend or a first version your team cannot staff this quarter.
- A framework is past end of life and the upgrade keeps slipping behind feature work.
- A customer security questionnaire arrived and nobody is sure of the answers.
Why this keeps happening
Platforms accrete services faster than teams can operate them. A product that started as a few services is dozens a few years later, each with its own deploy path, its own alerting gaps, and one person who understands it. Most production pain we see is not a missing feature. It is operability: a release that only one engineer can run, a page at 3 a.m. that goes to the wrong person, a framework that left support while the roadmap was full.
The usual response is to add more: another service, another dashboard, another layer. It costs money twice. First in the engineering time to build it, then every week in the attention it takes to keep it alive. Teams end up spending their best people on keeping the lights on, which is exactly when the roadmap slips.
Security goes the same way. Services trust each other because they always have, and the first audit of that trust is a customer questionnaire or an incident.
How we work on it
We design for the on-call engineer first. Before we add anything, we ask what happens when it fails at 3 a.m., who gets paged, and what they will need to see. That changes what gets built: event replay instead of manual fixes, jobs that can be stopped and resumed, boundaries that match how your teams are organized.
Tests and runbooks are part of done, not a phase after. A service ships with its coverage, its alerts, and a one-page runbook, or it does not ship.
Every change lands in your repository, in steps your team can review. We use AI-assisted development to move faster on scaffolding, tests, and refactoring; the review bar does not move.
What we do in Software Engineering
Robust core developmentYour services block each other, and every release waits on the team that owns the shared table.
Prior experience. Backend services and REST APIs for the order-fulfillment platform at Walmart Global Tech; the figures are on the card below.
Fits best in: retail and logistics, SaaS.
Legacy Java and .NET modernizationMove off end-of-life frameworks and split the monolith without stopping feature work.
Method. Characterization tests first, then the upgrade in shippable steps: runtime, frameworks, then the seams worth splitting. CI gates keep each step from regressing.
Fits best in: retail and logistics, SaaS.
Production foundationsGet a release path, tests, monitoring, and on-call runbooks the whole team can run, so shipping stops depending on one person.
Prior experience. The release gates, alerting, and runbooks on the order-fulfillment services at Walmart Global Tech; the figures are on the card below.
Fits best in: SaaS, retail and logistics, early-stage products.
System-wide securityClose the gaps between services, data, and people before an audit, a customer questionnaire, or an incident finds them first.
Method. Security built into the backend work we do rather than bolted on: authenticated service-to-service calls, role-based access, input validation at every boundary, secrets outside the code, audit logs that answer who did what.
Fits best in: SaaS, retail and logistics.
Multi-tenant SaaS architectureServe many customers from one codebase without one tenant's data or load reaching another.
Prior experience. Multi-tenant fulfillment services serving North American stores and tenants in the UK and South Africa, with tenant and store identifiers leading the hot-table indexes.
Fits best in: SaaS, retail and logistics.
MVP buildsGo from idea to a working first version your first customers can use.
Method. We scope with the founders, build a small stack any engineer can pick up, and put access control and audit logging in the data model from day one.
Fits best in: early-stage products, SaaS.
The work behind it
Prior experience: work by the people behind Data Fact Tree in previous roles.
Walmart Global Tech · 2022 to 2025
4,700+ storesOrder-fulfillment microservices for 4,700+ stores
Java, Spring Boot and Kafka multi-tenant microservices for North American stores plus UK and South Africa tenants, with event-driven flows across five picking services and event replay.
Event replay across five picking services let stuck orders recover without manual fixes; 80%+ integration coverage enforced through Jenkins and SonarQube gates.
Read the full story →Ancestry (internship) · 2021
94% test coverageReusable messaging component with 94% unit-test coverage
One component replaced several teams' near-duplicate messaging code.
Algorithm included in a patent filing; hackathon category win.
University of Michigan-Dearborn · 2020 to 2021
Under 10 ms latencyMessaging protocol proofs of concept under 10 ms latency
Proofs of concept comparing HTTP, MQTT, WebSocket and CoAP for device messaging, with under 10 ms internal latency, and a published paper on securing IoT networks.
Two IEEE papers, including "Secure Smart Lock System Utilizing the MQTT Protocol" (2022).
How an engagement is shaped
We quote within 48 hours of a technical consultation.
MVP build
Working software in your repository with access control, tests and CI/CD, weekly demos, and handover
Production-readiness review
Review report, test and release gates, runbooks, on-call plan
Retained advisory
Design and code review, incident support, hiring help
If one service is where every estimate goes to die, that is usually where we start. Get in touch.