Fflidget.com
Flidget
“Databaset let us add memory to Flidget's retention copilot without a vector DB side quest. We store user context once and recall it on every exit flow.”
Vishal Chaudhary
Founder, Flidget
Zero-config AI memory API
Give your AI apps persistent memory. Without the infrastructure sprint.
Stop configuring vector databases, tweaking chunking scripts, and debugging latency. Databaset is a zero-config, sub-50ms utility API that extracts, indexes, and surfaces user memory out of the box.
3,000 API calls in your first month. No credit card required. On-Server VPC deployment available for enterprise privacy.
No credit cardVPC for enterpriseShip in minutes
Zero-config API
No vector DB, no chunking scripts, no embedding pipeline to maintain.
Sub-50ms recall
Fetch the right user context before every LLM call. Fast enough for production chat.
Raw text in
Pass unformatted conversation strings. Databaset handles extraction and indexing.
Enterprise ready
Global cloud by default. On-Server VPC when your data cannot leave your perimeter.
3
lines to integrate
<50ms
p95 recall target
0
vector DB setup
TODAY · User shares their stack
Saved with one API call
“We run Postgres in prod. The team builds on Next.js.”
3 WEEKS LATER · Same user, fresh chat
No stack mentioned this time
“Should I go with Supabase or Neon for this MVP?”
DATABASE MEMORY ENGINE
Finds what you mean, not just the words you typed
AI RESPONSE · Answer with context
2 memories found in 38ms
“You usually pick Postgres and Next.js. For this MVP, Neon could be a good fit. Serverless Postgres with branching.”
Integrations
Works with every AI model and framework.
From side projects to production AI teams.
OpenAI
Claude
Gemini
LangChain
Vercel AI SDK
Next.js
OpenAI
Claude
Gemini
LangChain
Vercel AI SDK
Next.js
OpenAI
Claude
Gemini
LangChain
Vercel AI SDK
Next.js
PROOF IN CODE
See the difference
50+ lines of infra, or 3 lines of code
Skip the Postgres + pgvector setup. Install the SDK, pass raw conversation text, and query by userId.
The messy way
- Set up local Postgres + pgvector
- Connect custom OpenAI embedding endpoints
- Write text overlapping and chunking functions
- Manage user workspace partition logic manually
// embedding pipeline.ts (excerpt)
const chunks = overlapSplit(text, 512, 64)
const vectors = await openai.embeddings.create(...)
await pg.query('INSERT INTO vectors ...', [
tenantId, userId, namespace, ...
])
// + retrieval, reranking, cache layer...The Databaset way
- One npm install @databaset/sdk
- Pass raw conversation text stream
- Query by userId
typescript
import { Memory } from '@databaset/sdk'; const memory = new Memory({ apiKey: 'db_prod_123' }); "text-muted">// 1. Store interaction directlyawait memory.store({ userId: 'user_99', text: 'Prefers Next.js and PostgreSQL',}); "text-muted">// 2. Fetch context instantly (<50ms)const { memories } = await memory.recall({ userId: 'user_99', query: 'preferred tech stack',});Why custom stacks fail
Production memory is harder than the demo
Teams burn weeks on vector plumbing before they ship a single memory feature. These are the traps we see every week.
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.
Scale and privacy
Built to prototype in minutes. Hardened for enterprise scale.
Start building on our high-speed global cloud instances today. When your business data requires strict on-shore data rules or strict compliance, seamlessly transition to On-Server / VPC private deployments. Maintain absolute control of your data with SOC2 and HIPAA readiness configurations.
Global cloud
Sub-50ms recall worldwide
On-Server / VPC
Your infra, your data
SOC2 & HIPAA ready
Enterprise compliance configs
PLAYGROUND
Interactive playground
See memory work before you sign up
Type any user detail on the left. Watch Databaset store, index, and surface it as clean context on the right. No API key required.
Demo: 0/3 memories·0/3 questions
StoreRecallAnswer
Memories0/3
Stored
- Loading...
Try it: add a fact like "John wants the newsletter sent weekly on Thursdays", then ask a question. I'll recall what matters before I answer.
Testimonials
Trusted by founders shipping real products
Founders at Flidget, PRBoard, and MedOn use Databaset for long-term AI memory without standing up their own vector stack.
Pricing
Start free with your whole team. Upgrade when you need more API calls, apps, and support.
Free
Perfect for side projects and prototypes
$0/month
- 3,000 API calls in your first month
- Full API access to integrate and test
- 1 app
- 7 day retention
- Community support
- Upgrade for production after month one
Most Popular
Starter
For production apps with real users
$29/month
- ≈ 100,000 active users worth of memory storage
- 50,000 recalls per month
- 10 apps
- Unlimited retention
- Email support
- Dashboard analytics
- Webhooks
Growth
For teams scaling AI products
$99/month
- ≈ 1M active users worth of memory storage
- 500,000 recalls per month
- Unlimited apps
- Unlimited retention
- Priority support
- Advanced analytics
- Custom metadata
- SLA guarantee
Enterprise
Custom limits and dedicated support
Custom
- Unlimited everything
- Self-hosted deployment option
- Dedicated support engineer
- Custom contract and billing
- SOC2 compliance
- HIPAA available
Got questions?
If you cannot find what you are looking for, get in touch.