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Platform / Database

Instant Storage.
Postgres by Default.

Stop wrestling with connection strings, ORMs, and migrations. Prompt your API, and Init automatically spins up a secure Postgres database, infers the schema, and writes the queries natively within your endpoint.

1. You Prompt

"Create a POST endpoint /api/waitlist that takes an email address. Create a table if it doesn't exist, save the email, ensure there are no duplicates, and return the new user's waitlist position."

2. Init Deploys the DB & Endpoint
POST https://api.init.com/v1/waitlist
{ "email": "founder@startup.com" }

// Table created. Record inserted. 38ms
{
   "status":  "success",
   "data": {
     "id":  "wlt_7x29p",
     "position":  142,
     "created_at":  "2026-04-30T12:04:00Z"
  }
}

Fully managed, entirely invisible.

Init provisions a dedicated Serverless Postgres instance for your project the moment you ask for persistent data. No setup required.

Relational Integrity

Full Postgres power. Foreign keys, joins, and strict ACID compliance built-in.

Edge Pooling

Built-in PgBouncer ensures your serverless functions never exhaust database connections.

pgvector Native

Store AI embeddings and run semantic similarity searches directly alongside your data.

Flexible JSONB

Store unstructured data and documents with the speed and queryability of NoSQL.

Auto-Backups

Automated point-in-time recovery ensures your application data is never lost.

Zero Configuration

No migrations. No connection strings.

Forget writing DDL, managing Prisma schemas, or debugging `.env` files. When you prompt an endpoint that requires data, Init's compiler dynamically infers the required table schema, executes the migration, and binds the connection variables securely at the edge.

DATABASE_URL="postgres://user:pass@host/db"
npx prisma migrate dev
Init Auto-Provisioned Postgres
Always In Sync
Vector Ready

Seamless AI data embedding.

If your endpoint involves RAG (Retrieval-Augmented Generation) or semantic search, Init natively wires your Postgres database with `pgvector`. It automatically handles the lifecycle of converting text to embeddings and storing them alongside your standard relational data.

// Automatically generated serverless logic
async function saveDocument(req) {
   // 1. Generate embedding array
   const vector =  await ai.embed(req.content);

   // 2. Insert text and vector seamlessly
   const doc =  await db.query(
     `INSERT INTO documents (text, embedding) 
      VALUES ($1, $2) RETURNING id`,
    [req.content, vector]
  );

   return { id: doc.id };
}
Production Ready

Enterprise scale, out of the box.

Under the hood, your generated endpoints communicate with a highly-available Postgres cluster. We handle the DBA work so you don't have to—from index optimization to connection pooling and daily backups.

Auto-Indexing

Init analyzes slow queries and adds indexes automatically.

Serverless Pooling

Handle 10,000 concurrent API calls without dropping DB connections.

PITR Backups

Restore your data to any exact second within the last 7 days.

Compute Scaling

Storage and compute scale dynamically based on API load.

Data-heavy endpoints in seconds.

See how easy it is to manage state with conversational prompts.

CRUD Profiles

"Endpoint to update a user's bio and avatar. If the user doesn't exist, return a 404. Otherwise, update the DB and return the new profile."
PATCH /api/profileRelational Ops

Global Leaderboard

"Endpoint that fetches the top 100 users by score from the database, ordered descending. Cache the response for 60 seconds."
GET /api/leaderboardQuery + Cache

Semantic Search

"Take a user query, turn it into an embedding, and search my product database for the 5 most semantically similar items."
POST /api/searchpgvector Ops

Stop running migrations.

Join thousands of developers building data-rich, enterprise-ready APIs in seconds.