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2 min readKolaybase Team

How to Choose a Backend for Your AI App

AI apps still need a normal backend: users, conversation history, document storage, and usage limits. Here's how to choose one that won't slow you down.

AIbackendLLMarchitecture

It's easy to spend all your time on prompts and models and forget that an AI product is still a normal application underneath. Users sign in. Conversations get saved. Documents get uploaded. Usage needs limits. The backend you pick for that foundation decides how fast you can ship everything around the model.

What an AI app actually needs from a backend

Strip away the model and most AI apps need:

  1. Accounts — authentication and user profiles.
  2. History — conversations, messages, prompts, and outputs.
  3. Documents — file uploads for retrieval (RAG) and the metadata to find them.
  4. Limits & billing data — usage counters, plans, quotas.
  5. An API — so your app and any background workers can read and write all of the above.

None of that is AI-specific. It's the same backend every app needs — which means you shouldn't build it from scratch.

Relational data fits AI apps better than you'd think

Conversations belong to users. Messages belong to conversations. Documents belong to workspaces. That's relational data, and PostgreSQL models it cleanly with foreign keys and fast queries — much better than stuffing everything into documents and reconstructing relationships in code.

create table messages (
  id bigint generated always as identity primary key,
  conversation_id bigint references conversations(id),
  role text not null,
  content text not null,
  created_at timestamptz not null default now()
);

Checklist for choosing

  • Does it include auth, storage, and an API? If not, you'll build them.
  • Is it standard PostgreSQL? Standard SQL keeps you portable and lets you adopt ecosystem extensions as your needs grow.
  • Can you self-host? Useful for data-sensitive workloads.
  • Is access control at the database? Row-level security keeps user data isolated — see the RLS guide.

Where Kolaybase fits

Kolaybase gives you the whole non-model foundation — PostgreSQL, authentication, S3-compatible storage, and a REST API — so the only thing left to build is the part that's actually yours. See the backend for AI applications use case, or compare the build-vs-buy trade-off before you decide.

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