A frontend with nowhere solid to land
Ad-hoc endpoints, no versioning, and business rules copied into three clients. We put the rules in one place.
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04Service
The interface is a rumor until the data model is true. We build the system behind the screen.
What we do
We design and implement APIs, databases, authentication, authorization, background work, webhooks, payments, and the integrations a product pretends are simple. The work is typed, observable, and boring in the ways that let you sleep. Security is not a phase; it is the shape of the endpoints.
Problems we solve
Ad-hoc endpoints, no versioning, and business rules copied into three clients. We put the rules in one place.
Nulls everywhere, money as floats, users as an afterthought. We model the domain so invalid states are hard to store.
Emails sent twice, webhooks lost, invoices stuck. Queues, idempotency keys, and dead letters are part of the build.
Login exists. Authorization is a comment. We design roles, resources, and the tests that prove a user cannot see another tenant.
Capabilities
REST, RPC, or a mix. Versioning, pagination, errors that clients can branch on.
Relational first when the domain is relational. Migrations that a human can read.
Sessions, tokens, SSO, MFA — chosen for the threat model, not the blog post.
RBAC, resource rules, and tenant isolation you can demonstrate.
WebSockets or equivalent where live state is the product, with a fallback when the socket dies.
Queues, retries, backoff, and visibility into what is stuck.
Stripe (and kin): webhooks, reconciliation, and the ledger you will wish you had.
Third-party APIs with mapping, rate limits, and a plan when they change a field.
HTTP, application, and data cache with explicit invalidation, not hope.
Secrets, headers, audit logs, and the boring checklist that still catches most incidents.
Typical projects
Approach
01
Events and entities before framework. If we cannot draw the lifecycle of an order, we are not ready to pick a queue.
02
Types, constraints, and migrations that refuse nonsense.
03
Networks retry. Users double-click. The system should not create two invoices.
04
Structured logs and traces from the first endpoint, not after the first outage.
Technology
Architecture
Client
Web, mobile, or another service. Untrusted until proven.
Deliverables
OpenAPI or equivalent, error codes, and examples that match production.
How data gets in, how it changes, and how we roll back without folklore.
What we tested, what we did not, and the first knob to turn if traffic surprises you.
Voices
“The useful part was not the model. It was the review queue, the traces, and the fact that the CRM stopped being a junk drawer. Replace this sentence with a real operations quote.”
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“They treated authorization as a product decision, not a CSS display:none. That is the only quote finance should care about. Placeholder.”
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“They mapped partner payloads into a state machine instead of pretending every shipment is on time. Dispatch lives in the exception queue now. Placeholder.”
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FAQ
We default to TypeScript across the stack when the team is product-shaped. Go when the workload is a service with strict concurrency or ops constraints. The maintenance team wins the argument.
Yes. We start with traffic, errors, and the schema as it really is — including the columns named `data2`.
We design for common classes of failure and document assumptions. Formal pentests are a specialist we can work alongside, not a badge we print ourselves.
Start
Tell us what you are trying to ship. We will come back with questions, a shape, and whether we are the right studio for it.