Databaset

Databaset

A zero-config AI memory API that provides persistent, semantic memory for LLMs without requiring vector databases or complex RAG pipelines.

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PlanFree: 3,000 API calls in your first month. No credit card required. · Starter: $29/month for production apps with real users (50,000 recalls per month). · Growth: $99/month for teams scaling AI products (500,000 recalls per month).
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About Databaset

Give your AI apps persistent memory without the infrastructure sprint

Databaset is a zero-config, sub-50ms utility API that extracts, indexes, and surfaces user memory out of the box. Stop configuring vector databases, tweaking chunking scripts, and debugging latency. Instead of spending weeks on vector plumbing, you can start shipping memory features in minutes.

Why choose Databaset over custom stacks?

Production memory is harder than it looks. Many teams burn weeks on infrastructure before they ship a single feature. Databaset solves the common traps of custom builds:

  • The Vector Namespace Trap: Re-architecting multi-tenant database rules for every client is a massive time sink. Databaset securely isolates user memory by userId automatically behind a single API key.
  • The Latency Problem: Custom RAG lookups or multi-hop knowledge graph queries can tank application performance. Databaset guarantees sub-50ms p95 recall latency globally.
  • The Ingestion Burden: Cleaning, token-trimming, and formatting chat transcripts eats up hours of developer time. Databaset accepts raw, unformatted text strings directly.

Seamless Integration with Your Favorite Tools

Databaset works with every AI model and framework, allowing you to scale from side projects to production-grade AI teams.

  • OpenAI, Claude, Gemini
  • LangChain, Vercel AI SDK, Next.js

How it Works

  1. Store: Pass raw conversation text directly to the API. Databaset handles the extraction and indexing automatically.
  2. Recall: Query by userId and a natural language query. The engine finds what you mean, not just the words you typed.
  3. Respond: Inject the recalled context into your LLM prompt for an answer with full user history and preferences.

Enterprise-Ready Security and Scale

Built to prototype in minutes but hardened for enterprise scale. While global cloud instances are available by default, you can seamlessly transition to On-Server / VPC private deployments when your business data requires strict on-shore data rules or compliance.

  • Global cloud with sub-50ms recall worldwide
  • On-Server / VPC for your infrastructure and data
  • SOC2 & HIPAA ready configurations for enterprise compliance

Value & Audience

Value Proposition

A zero-config AI memory API that provides persistent, semantic memory for LLMs without the need for vector databases or RAG pipelines.

Problem Solved

Eliminates the user's need to build and maintain complex infrastructure for long-term AI memory, including vector databases, chunking scripts, and embedding pipelines.

Target Audience

Developers and production AI teams building applications with LLMs like GPTClaudeand Gemini.

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Databaset FAQ

Common questions about Databaset's features, pricing, and use cases

What does Databaset do?

A zero-config AI memory API that provides persistent, semantic memory for LLMs without the need for vector databases or RAG pipelines.

Is Databaset free to use?

Databaset offers a free tier alongside its other Database & Storage plans. Pricing details are listed on the Databaset product page on TechLogHub.

What problem does Databaset solve?

Eliminates the user's need to build and maintain complex infrastructure for long-term AI memory, including vector databases, chunking scripts, and embedding pipelines.

Who is Databaset built for?

Developers and production AI teams building applications with LLMs like GPT, Claude, and Gemini.

What tech stack does Databaset use?

Databaset is built with Postgres, Next.js, Vercel AI SDK, LangChain.

What category is Databaset listed under?

Databaset is listed in the Database & Storage category on TechLogHub, alongside curated alternatives with community ratings and pricing comparisons.

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