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Backend APIs and data platforms to connect tools, data and workflows

Backend and Data Platform Area

When dashboards, automations and applications need to talk to each other, they need a clear backend: APIs, databases, permissions and integration logic.

I build backend services and internal data platforms to avoid every tool working in isolation. I often work with FastAPI, Supabase, PostgreSQL and MongoDB, choosing pragmatic architectures that remain readable for small teams too.

When it makes sense

  • Data is distributed across tools and there is no reliable access layer.
  • Automations need stable APIs instead of improvised calls.
  • A dashboard or frontend requires authentication, roles and correctly filtered data.
  • The team needs a small CMS or operational panel to manage content, records or workflows.

What I actually build

  • REST APIs with FastAPI or a similar stack, organized by domain and responsibility.
  • Database schema, tables, views, policies and operational queries.
  • Integrations with Supabase, PostgreSQL, MongoDB, storage, webhooks or cloud services.
  • Essential technical documentation for endpoints, environment variables, deployment and maintenance.

How I work

  • Analysis of core entities, read/write flows and user roles, starting from real use cases: who reads, who writes, what errors must be handled.
  • Design of the schema, the minimum necessary endpoints and the boundaries between API, database and frontend.
  • Incremental implementation with integrations to external tools or AI services, plus error handling, validation and logging.
  • Review with real data, with a backend that's documented, testable and ready to evolve before adding secondary features.

FAQ

When should we choose Supabase instead of a custom backend?
Supabase is useful when database, authentication, storage and policies are needed quickly. A custom backend is better when application logic, integrations or workflows require more control.

Can we start from an MVP?
Yes. It usually makes sense to start with a few well-designed endpoints and add features once the real workflow has been validated.

Can the backend support AI automations too?
Yes. The important part is separating inputs, rules, external calls, logs and human review when the result affects content or operational decisions.