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Axelerant
Engineering · the lens that ships

We build platforms your
team can run for years.

Engineering here is the whole delivery lifecycle, not just the build: modernizing platforms, retiring the legacy that drains the budget, and running AI as an accelerator with the architecture and judgment kept human.

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Our approach

The build is the easy part.

Everyone can build. The harder, more valuable work is the lifecycle around the build: modernizing the platform underneath, stripping the repetitive drag out of how software ships, and wiring AI in from spec to reviewed code while the judgment stays human. The point is not speed. It is reliability your team can run on, release after release.

Our own SDLC

We rebuilt our own delivery lifecycle first.

The clearest proof of how we engineer is what we did to our own workflow. We built an open-source AI plugin that takes a Drupal ticket from spec to shipped: it writes the implementation spec, the code, the tests, and the pull request, then runs an AI-assisted security and acceptance review. It automates around 70 to 80 percent of the lifecycle, while people keep the two decisions that matter: what gets built, and what ships.

Open-source AI SDLC plugin · ~70–80% of the lifecycle automated
Six engineering practices

What we actually do, named plainly.

Pick the one closest to where you're stuck. Each is delivered by the same pod that framed the architecture, no handoff to a build partner who wasn't in the room.

Platform Engineering

Drupal, WordPress, Acquia, MACH and headless, chosen against your authoring reality and your scale, not the trend cycle. It is also where the unglamorous work lives: consolidating site sprawl and migrating legacy estates onto something maintainable.

What's inside
  • Drupal CMS, WordPress (VIP / Pantheon), Contentful, Sanity, Storyblok
  • Composable / MACH stacks: front-of-stack frameworks, edge runtimes, BFFs
  • Migration plans that protect SEO, content models and editorial workflow
Outcome

A platform editors will actually use and engineers won't quietly fork in year two.

Application Engineering

Custom web and product engineering for when the off-the-shelf stack starts to bend: modern frontends, disciplined APIs, and backend systems built to be extended.

What's inside
  • React / Next / TanStack Start front-ends, Node and Python services
  • API design, integration layer, identity and auth, payments
  • Internal tools and admin surfaces that staff don't quietly bypass
Outcome

Bespoke surfaces that read like product, not like a one-off project.

AI Engineering

Where the lifecycle itself gets faster: agentic delivery workflows and AI accelerators wired across how software ships, with the architecture and judgment kept human. This is the practice behind our open-source AI SDLC plugin.

What's inside
  • Context engineering: entity models, vector-backed institutional memory, cited retrieval
  • Governed agents that hold state, take default-deny actions, and escalate to humans
  • AI inside the DXP: classification, search, recommendations, governed generation
Outcome

AI you can put in front of procurement, and an operating system your teams actually run on.

Cloud Engineering & SRE

Multi-cloud infrastructure and SRE practice that keep the system fast, resilient, and economically sane: infrastructure as code, observability, and the on-call discipline to keep it healthy under load.

What's inside
  • Multi-cloud landing zones, Kubernetes platforms and IDP self-serve delivery
  • SRE practice: observability, incident response and on-call discipline
  • Progressive delivery, serverless/edge runtimes and cloud cost governance
Outcome

A cloud estate that scales with revenue, stays up when it matters, and doesn't make the CFO flinch.

Data Engineering

The pipelines, warehouse, and contracts that make data trustworthy enough to act on, plus the modernization work that retires legacy services quietly draining the budget.

What's inside
  • Warehouse + lake setup (BigQuery, Snowflake, Postgres, Supabase)
  • ELT with dbt, event pipelines, CDP / reverse-ETL integrations
  • Data contracts, lineage and quality monitoring, not just dashboards
Outcome

One source of truth that marketing, product and finance all reconcile against.

Quality Engineering

Test automation, accessibility, and performance run as a continuous signal, not a launch-week scramble, wired into the pipeline so quality is proven on every commit.

What's inside
  • Test pyramid: unit, integration, end-to-end with Playwright / Cypress
  • Accessibility audits to WCAG 2.2 AA, baked into CI
  • Performance budgets, Core Web Vitals regression gates, visual diffing
Outcome

A release pipeline you can ship from on a Friday without checking Slack on Saturday.

Technologies in playThe toolbox, not a feature matrix

The stack follows the scenario, not the other way around.

A working sample of the technologies we run in production today. We reach for the parts that fit the engagement, not a fixed feature matrix.

Cloud, infra & orchestration
Where the platform runs
AWS
Kubernetes
Terraform
Vercel
Frontend, backend & frameworks
What we build with
Next.js
TypeScript
Python
Django
Go
Laravel
React Native
Data, streaming & warehousing
Moves the data without dropping events
Apache Kafka
Confluent
Apache Spark
Apache Flink
Personalization & CDP
Activates the editorial graph
Salesforce
HubSpot
Lytics
Mautic
Proof

Engineering work we can point to.

Named clients, real systems in production, framed at exactly what we did.

Red Hat logo
Data engineering

Modernized marketing data infrastructure, legacy retired.

For Red Hat, we modernized the marketing data infrastructure, retiring legacy batch and Kafka-based streaming services, dozens of Python integration jobs and a streaming platform handling millions of messages, and moving their capabilities, data cleansing, consent management and persona derivation, into core platforms. It cut technical debt and freed the team to build new data and AI work instead of maintaining custom plumbing.

Case page coming soon
American Medical Association logo
Platform consolidation and modernization

Ten properties consolidated onto one governed Drupal platform.

For the AMA, we consolidated ten separate WordPress and Drupal properties into a single governed Drupal 11 platform on Acquia Cloud, built for editorial safety and scale rather than a one-off migration. We also modernized FRIEDA, their residency and fellowship platform, with a backend-led rebuild that made core search and program workflows faster.

Read the case
University of East London logo
The platform behind the outcome

Platform engineering behind a measurable lift in applications.

For UEL, we engineered the platform behind a measurable lift in applications, the build that made a conversion-focused student experience possible and kept it fast where it mattered, on mobile.

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UN Human Rights Office logo
Technical delivery partner

Engineering and design-system feasibility for a global rights platform.

For the UN Human Rights Office, we were the engineering and design-system feasibility partner behind a component-based platform, delivering the technical foundation for a global, high-scrutiny human-rights site.

Read the case

Recent work includes consolidating estates of 400+ sites and standing up subscription and commerce platforms serving over a million members.

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How engineering connects to delivery

One accountable team carries the thread the whole way.

Strategy
Design
Engineering
RevOps & Growth Marketing

Engineering makes the work real and reliable, with design ahead of it and revops & growth after it. One team carries the thread, so what ships is what was designed, and it holds up once it is live.

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