Architecture planned with the product
Infrastructure decisions are easiest to get right before the first line of code. We decide early where each part of the product runs, what has to happen inside a request and what can wait for a background job, and where the data lives. Those choices shape cost, speed and reliability for years.
At Hallward that meant moving schedule parsing out of the web request and into background workers. Large Primavera files are processed chunk by chunk with Celery and Redis, so uploads return straight away and neither the browser nor the gateway is left waiting.
- Hosting on AWS and Cloudflare, with managed services where they save you work
- Managed identity with AWS Cognito, Firebase Auth or NextAuth.js in place of custom sign-in code
- Background processing with Celery and Redis, so slow work stays out of the web request
- Service boundaries drawn around the parts of the system that change or scale on their own
- Containerised services with health endpoints and structured logging
CI/CD and release engineering
A release should be routine. We set up CI/CD pipelines with automated tests, so every change is built, checked and deployed the same way, and a broken build stops before it reaches users.
We keep configuration out of the code and secrets out of the repository, use separate environments for testing and production, and make sure your team can see what each release changed.
- Automated build, test and deploy pipelines
- Separate staging and production environments
- Configuration and secrets managed outside the codebase
- Health checks, structured logs and alerts
Designing for cost
Cloud bills grow quietly. Servers are sized for a launch spike that never came, test environments outlive the test, and logs and backups pile up for years. The cheapest fix is an architecture that doesn’t create the waste in the first place.
We size infrastructure to the load it actually carries, move heavy work to background jobs that scale on their own and cache repeated work. For AI features, model spend matters as much as hosting, so we log the cost of each request and route simple steps to cheaper models. We won’t promise a saving before we’ve seen your billing data.
- Right-sizing compute and databases to real load
- Caching for repeated reads and repeated model calls
- Switching off idle and non-production resources
- Storage lifecycle rules for logs, backups and uploads
- Cost reporting by service and environment
Case studies: Kaivo, Hallward and Carbon Giant
Kaivo runs as FastAPI microservices behind a Next.js front end, deployed on Cloudflare and AWS. Each ad-platform integration lives in its own service, so a change or outage on one platform doesn’t take down the rest of the product.
Hallward moves Primavera schedule parsing off the request path into Celery workers backed by Redis, processing files chunk by chunk. Large uploads return straight away and the dashboards are ready when the job finishes, with AWS Cognito handling sign-in.
Carbon Giant runs an OCR- and API-driven ingestion pipeline on AWS Textract and Apideck, turning invoices and accounting data from Xero, QuickBooks and Sage into Scope 1–3 emissions calculations on Next.js, FastAPI and PostgreSQL.
Working with your existing setup
Not every engagement starts from a blank page. If your product already runs in the cloud, we start by understanding what’s there: how it’s deployed, how it’s monitored and what it costs. Then we agree a short list of changes, ordered by risk and effort.
We can build the changes and hand them over, or work on them alongside your engineers, so the knowledge stays in your team when we finish.
What you get
- A written architecture covering hosting, data, identity, background processing and environments
- Infrastructure set up in your own cloud accounts
- CI/CD pipelines with automated tests and separate staging and production environments
- Monitoring, structured logging and alerts for the failures that matter
- A cost breakdown by service and environment
- Architecture diagrams and runbooks your team can work from
- A handover session with your engineers
How it works
1.Discovery and scope
Before the work
An NDA if you need one, then a working session on your product, your current setup and your concerns. You get a written scope, architecture and price before any work starts.
2.Plan the architecture
Early on
We agree where each part of the system runs, how it’s deployed and monitored, and what it should cost at your expected load.
3.Build and automate
Agreed milestones
Infrastructure, pipelines and monitoring built in working increments, with each change reviewed and repeatable.
4.Hand over
At completion
Diagrams, runbooks and a handover session, so your team can run and change the infrastructure. Ongoing support is available as a retainer, priced on request.
Proof
Story No. 01Marketing & AdTech
Every client’s ad channels in one workspace, with wasted spend caught sooner
Kaivo
Story No. 04Construction & Infrastructure
Primavera P6 project-controls reporting, without the spreadsheet rebuild
Hallward
Story No. 02Climate & ESG
Turning supplier invoices and ledgers into carbon figures an auditor can check
Carbon Giant
“Steady progress, predictable delivery, and code that’s easy to review and integrate.”
Price
From£12,000
For scoped infrastructure and delivery work. If you want a senior view before committing, a £450 Strategy Session is a smaller first step. Every engagement starts with a free one-hour call, and you get a written scope with a fixed or capped price before any work starts.
FAQ
Our Build Projects start from £12,000 for scoped infrastructure and delivery work. The price depends on how many environments, services and integrations are involved. If you’d like a senior view first, a Strategy Session costs £450. Cloud usage is billed to your own accounts.
We can’t give an honest figure before we’ve seen your billing data and architecture, and we’d be wary of anyone who does. Each cost recommendation comes with the expected saving and the effort involved, so you can decide what’s worth doing.
The products in our case studies run on AWS and Cloudflare, with Google Cloud services such as Vertex AI and Firebase where the product needs them. If you’re on another provider, tell us in the intro call and we’ll be straight about whether we’re the right fit.
Often not. Kubernetes suits teams running many services with the people to operate it. Smaller teams are usually better served by managed hosting, simpler container platforms or background workers that scale on their own. We recommend the simplest setup that meets your scale and security needs.
Yes. We can work in your repositories and cloud accounts, review changes with your engineers and document as we go, so your team owns the result.