Updated
Supabase appears in published cases including Appster, This is HCD, Release Coach AI, Inspire Film and TrendinChat. Those records establish delivery scope, not a count of products guaranteed to remain live. For a new engagement, define the application data, account boundaries and operating responsibilities.
Standing Supabase up is easy. Standing it up securely is a separate job. This page explains why row level security is the most consequential decision you will make, and when we choose a different path entirely.
Appster’s case describes semantic search, catalogue administration and content pages on a Next.js and Supabase stack. This is HCD uses Supabase for member activity alongside Sanity editorial content. These examples show connected product scope, not that every new backend is quicker to build or needs no separate service. Evaluate a representative workflow before agreeing the architecture.
The security problem we see most often in Supabase projects is row level security policies that are missing or written too broadly. Because the client talks to the database directly, one wrong policy means a user can read another user's records. These tables and policies are always designed and reviewed by an engineer. This is one area where we do not trust generated code, no matter how convincing the generated policy reads on the first pass.
List business operations, background work, access boundaries and environment requirements before deciding where each should run. Reveal’s case documents a Hono and Drizzle server layer with PostgreSQL; it does not establish why Supabase was rejected. Compare the actual workload and operating responsibilities rather than treating a project stack as a universal rule.
Estimate the product’s representative storage, traffic, processing and operational needs against its intended setup. Confirm how usage will be measured and when the team reviews it. Do not infer a fixed cost or saving from record count alone or from another project’s technology choices. Define any data or media move as its own tested scope.
Senior engineers building your product with AI coding agents: web, mobile, SaaS or browser extension, reviewed before anything ships.
AI-accelerated development, billed monthly. We confirm scope, capacity and start date in writing before checkout.
Assess the product’s data model, access rules, deployment and operating responsibilities. Published cases show Supabase used in delivered products; they do not guarantee a new application’s security or availability. Agree representative checks before release.
The data is portable because standard PostgreSQL sits underneath. The authentication and storage layers take additional work. If you know this is a possibility from the start, we can structure the codebase to make that move less painful.
Yes. We look at table policies, where service keys are being used and what surface is exposed to the client, then produce a written report. This work usually runs under the ongoing support arrangement.
Appster’s published case includes semantic vector search over an OpenAI-embedded catalogue on a Supabase stack. For your product, define retrieval examples, data updates and operating requirements before choosing the search integration. The case does not establish that every AI feature needs no separate service.
One paragraph on what you are building, roughly when you need it, and who it is for. No brief, no form with fifteen fields.
From the engineer who would do the work, not a sales team. If we are not the right fit we say so, and where possible we point you somewhere better.
Scope, price and timeline in writing before anything is committed. You decide with the numbers in front of you.
No long contract to begin, no lock-in to our tooling, and the code is yours from the first commit.
Start a conversationA short note about the product, the timeline and who it is for is enough to start. You will hear back from the engineer who would do the work, not a sales team.
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