“I very much respect the knowledge that you have. You have a lot of things, just in our few communications, that no one else has mentioned. No one else has even made me think about them.”
Backend Development
Backends built to hold up after launch
Node.js, NestJS, and Python backends with the contracts, data model, security, queues, and operational tooling needed to hold up after launch.
Why choose us for backend development?
A backend is judged by the team that has to operate it after launch. We build the contracts, data model, security and queues with that team in mind.
Node.js + NestJS APIs
Type-safe product APIs with validation, stable contracts, structured errors, OpenAPI docs and clear module boundaries, so the front end and every integration build against a contract that does not shift under them.
Python + FastAPI services
Async APIs and workers for AI, data and compute-heavy workloads sit behind explicit boundaries, so you get Python where it is the better tool without turning the whole product into Python by default.
Postgres + data modelling
Schemas, migrations, indexes, query plans, transactions and retention rules are designed around actual access patterns, which is why the queries that are fast in the demo stay fast under real load.
Authentication + authorization
Session and token flows, RBAC or ABAC, tenant isolation, row-level security and auditable privilege changes form one boundary before the domain code, so isolation is tested once rather than re-checked in every handler.
Queues + background jobs
BullMQ, Celery or SQS with scheduled work, backpressure, idempotency, retry policies and dead-letter handling, so bursty work is absorbed and a failed job is visible rather than silently lost.
Compliance-ready foundations
Encryption, audit logs, secrets, PII boundaries, access controls and evidence-friendly infrastructure are in the first release, so a later audit reads what exists instead of asking for a retrofit.
What we build in backend development
The server side of a product, from the API the front end calls to the jobs that run when nobody is watching.
REST and GraphQL APIs
Typed contracts in NestJS or FastAPI, depending on the workload.
- Request validation with structured, documented errors
- Versioning so old clients keep working
- Reference docs generated from the contract itself
Auth and permissions
Sessions, tokens and SSO, with every privilege change written to an audit log.
- RBAC or ABAC, chosen against how your organisation works
- Row-level security enforced in the database
- Password reset, MFA and session revocation handled
Billing systems
Stripe or Paddle wired in, so your database and the provider always agree.
- Plans, seats and usage metering mapped to entitlements
- Invoices, proration and dunning on failed payments
- Webhook reconciliation that survives retries and out-of-order events
Background job systems
Queues, schedulers and workers where a failed job is visible rather than lost.
- Idempotent handlers so a retry never double-runs
- Backpressure and rate limits per queue
- Dead-letter handling with a path to replay
Real-time services
WebSocket and server-sent event layers for live state, presence and notifications.
- Fallbacks for clients that cannot hold a connection
- Reconnect and catch-up so no update is missed
- Fan-out that scales across more than one server
Multi-tenant backends
Tenant isolation decided against your compliance obligations and enforced at the data layer.
- Shared schema, schema-per-tenant or database-per-tenant, chosen deliberately
- Isolation tested once, not in every handler
- Per-tenant limits, quotas and usage reporting
Recent products we shipped
Our most recent case studies. Each result is the one its own case study reports, in its own words.
30+ SKUs scanned into one Shopify draft order; the old version choked on large ones.
Draft Deputy
Shopify · Micro-SaaS
1,000+ skincare formulas resolved from a 60-second phone scan in 55+ San Pablo pharmacies, before the customer leaves the store.
2250
A.I · Custom Web App

3.5K students stayed online while a Lovable-built front end was mapped onto the live LMS.
Squid Academy LMS
SaaS · Custom Web App

Non-marketers launch Meta and TikTok campaigns from one plain form, and read both platforms’ results in one view instead of two ad managers.
AI Agent for Meta and TikTok Ads
MVP · SaaS
How we build backend development
Four stages, from modelling the product to a handover with the operational context intact.
Model the product
We map users, permissions, data ownership, integrations, critical transactions, and expected load before choosing architecture.
Contract + threat design
API schemas, failure semantics, authorization boundaries, and security risks are reviewed before implementation starts.
Build in vertical slices
Each slice includes persistence, business logic, API, tests, logs, and deployment: so progress is demonstrable and usable.
Load, launch, handoff
We test realistic bottlenecks, configure alerts, document runbooks, and hand the system over with its operational context intact.
- See our full process
What clients say after the build
Real client reviews, every one checkable at source.
Backend development questions
Architecture decisions should reduce operating cost and change risk: not advertise the technology choices.
Node.js and NestJS are our default for product APIs; Python and FastAPI are a strong fit for AI, data, and scientific workloads. Many products use both behind explicit boundaries. We choose per workload, not per developer preference.

