Supabase & Postgres Development
We build production data layers on Supabase + Postgres. Row-level security, real-time subscriptions, pgvector for AI, and the architecture decisions that survive scale.
Why we picked this stack
Supabase gives us Postgres plus Auth, Realtime, Storage, and Edge Functions in a single managed package: perfect for funded startups that need to move fast without standing up five services. Postgres is the right default: relational, mature, JSON-flexible when needed, and vector-capable with pgvector. Row-level security policies let us implement multi-tenant and permission systems without auth-service complexity. And when Supabase stops being the right fit, a self-host migration path exists; so the stack survives scale instead of trapping you.
What we build with it
Schema design + migrations
Postgres schema design and migrations via Supabase migrations, Prisma, or raw SQL: versioned and reviewable.
Row-level security
RLS policies for multi-tenant SaaS: permissions enforced in the database, not bolted on in app code.
Realtime subscriptions
Live dashboards, chat, and collaborative tools backed by Supabase Realtime over Postgres replication.
pgvector for AI/RAG
Vector search in Postgres when scale is moderate and operational simplicity beats a separate vector DB.
Edge Functions
Serverless backend logic deployed at the edge: webhooks, integrations, and on-the-fly transforms.
Auth integration
Supabase Auth wired into your app: or a clean migration to Clerk or Auth0 when you outgrow it.
The technology is the starting point, not the pitch
Versions and libraries we use
- Supabase (managed)Our default for most projects: Postgres, Auth, Realtime, Storage, and Edge Functions in one package.
- Postgres 15+We keep current: the relational core under everything we ship.
- pgvectorVector search at moderate scale, embedded in the same database as your relational data.
- Prisma / Supabase generated typesType-safe queries end to end: generated from the schema, not hand-maintained.
- PostgREST patternsSupabase auto-generated REST: used where it fits, bypassed where raw SQL is clearer.
- pgBouncerConnection pooling for serverless and high-concurrency workloads at scale.
- Supabase JS / Python clientsFirst-class clients for both our TypeScript front ends and Python data/AI services.
Anti-patterns we avoid
Deferring RLS policies
You will not "add them later." We design for multi-tenant isolation from day 1, in the database.
Supabase Auth for enterprise SSO
Need SAML, SSO, or enterprise features? We move you to Clerk or Auth0 rather than fight the limits.
Reaching for Pinecone too early
A few hundred thousand vectors run fine on pgvector. We avoid a second datastore until scale demands it.
ORM-only mindset
An ORM is a tool, not a rule. When raw SQL is clearer or faster, we write raw SQL.
No self-host migration plan
If data residency or cost becomes an issue, you need an exit. We architect for migratability from the start.
Where Supabase + Postgres ships most
AI Marketing
Ad platforms, outbound engines, and content tooling on a fast relational data layer.
- AI ad-creative platforms
- Outbound + enrichment engines
- Content + AEO tooling
AI Healthtech
Self-hosted Supabase on HIPAA-eligible infrastructure for clinical and medical-document workflows.
- Clinical copilots
- Triage + intake
- Medical document workflows
AI Fintech
Relational integrity and row-level security for underwriting, risk, and document-intelligence pipelines.
- Underwriting + risk models
- Fraud detection
- Document intelligence
Built on Supabase + Postgres
AI Ads Assistant for Meta and TikTok
We built a minimum viable product to connect disparate advertising APIs into a single, intuitive user interface.
AI Mental Health Companion
We engineered a voice-first AI companion with a therapeutic framework to validate a new model for mental health support.
AI Contract Generation Platform
We built the technical foundation for a SaaS platform that automates complex legal document creation with usage-based pricing system
Related technologies
Next.js
The front end and full-stack layer we most often pair with a Supabase + Postgres backend.
ExploreRAG Systems
Retrieval-augmented generation grounded on pgvector when scale and simplicity allow.
ExploreAI/ML
LLM apps, agents, and vision pipelines that read and write the data layer Postgres holds.
ExploreHire senior Postgres + Supabase engineers
Need to extend your team with engineers who have shipped production data layers? We embed senior backend engineers who design RLS, tune Postgres, and ship Supabase the right way from day one.
Frequently asked questions
Postgres beats Firestore for relational data and AI workloads. Supabase gives you better SQL ergonomics and an open-source, self-hostable path that Firebase cannot match.
Production engineering
The technology is the starting point, not the deliverable
We select tools for the problem, not for the portfolio. Every technology detail page on this site describes a stack we reach for because it ships, not because it trends.
Building on Supabase or Postgres? Schedule a meeting.
No account managers. No discovery theatre. A direct conversation about your data layer, your RLS model, and what it takes to ship it to production.