The AI Developer Platform
Built on an Intelligent Database
Database, auth, realtime, queues, file storage, edge functions, and auto-generated REST APIs in one platform. MongoDB and Meteor.js compatible. Just change your connection string.
const context = await db
.collection('agent_memory')
.aggregate([{
$contextSearch: {
query: userMessage,
vector: {
path: "$embedding",
limit: 20
},
temporalDecay: {
field: "timestamp",
halfLife: "7d"
},
expand: {
relationship: "references",
depth: 2
},
sessionScope: {
sessionId: currentSession
}
}
}]).toArray();Your Database Wasn't Built for AI
Building AI applications means stitching together databases, vector stores, auth providers, realtime engines, queues, and file storage. Six vendors. Six bills. Six failure domains. There's a better way.
Six Services Just to Ship an AI App
Database, vector store, auth provider, realtime engine, message queue, file storage. Six vendors, six SDKs, six bills, six failure domains. Your "application" is mostly glue code holding them together.
Context is Scattered Across Services
Your agent's memory lives in one service. Its retrieval context in another. Auth in a third. Realtime sync in a fourth. Every query requires glue code to merge them. Every inconsistency becomes a hallucination.
No Memory Lifecycle Management
Agent conversations pile up with no way to decay, archive, or summarize. You build custom TTL logic, manual archival pipelines, and brittle cleanup scripts. Or your context windows overflow.
The Multi-Vendor Tax
Auth0 for auth. Pusher for realtime. SQS for queues. S3 for files. Each charges separately. Each scales differently. Each has its own security model. You spend more time integrating services than building your product.
Architecture That Just Works
Not a proxy. Not a compatibility layer. A complete database engine with native storage tiering.
Everything You Need to Build AI Applications
An intelligent database with a complete developer platform built in. Context search, auth, realtime, queues, branching, and auto-generated APIs - all in one system.
AI Context Engine
Native $contextSearch combines vector similarity, temporal decay, relationship traversal, and session scoping in a single query. No glue code. No context assembly layer.
Built-in Auth & Document-Level Security
JWT tokens, API keys, OAuth providers, and MFA built into the platform. Document-level security policies enforce row-level access right in the storage engine.
Intelligent Tiering
Data automatically flows from NVMe hot storage to Parquet cold storage based on access patterns. Queries span both tiers transparently. 60-80% cost reduction.
Auto-Generated REST API
Every collection gets instant REST endpoints with filtering, sorting, and pagination. Auto-generated OpenAPI specs. No backend code required.
Database Branching
O(1) copy-on-write branches for dev, test, and preview environments. Branches share storage via MVCC snapshots. Merge back with conflict detection.
Edge Functions & Triggers
Run code on database events. Auto-generate embeddings on insert, fire webhooks on update, schedule cron jobs. All from your database.
Time Travel Queries
MVCC snapshots let you query data at any historical timestamp. Debug agent hallucinations, satisfy auditors, and build undo functionality.
Broadcast & Presence
WebSocket-based realtime subscriptions, broadcast messaging, and presence tracking. Live database changes pushed to connected clients.
Built-in Queues
Durable message queues with visibility timeouts, dead-letter queues, and ACID guarantees. No SQS or RabbitMQ needed.
MCP Server for AI Assistants
AI coding assistants query your schema, run queries, and write database code directly from the IDE via Model Context Protocol.
Replace Your Entire Backend Stack
Stop stitching together six vendors to build one product. Thermocline gives you the database, auth, realtime, queues, file storage, and APIs in one platform with one security model.
One platform. One connection string. Every capability your AI application needs.
What No Other Database Does
Thermocline isn't a vector database with features bolted on. It's a complete AI developer platform that replaces your entire backend stack: database, auth, realtime, queues, file storage, and APIs.
Native Context Search
Vector search is table stakes. Context search is the game.
$contextSearch combines vector similarity with temporal decay scoring, relationship expansion, and session scoping. One query returns ranked, relevant context, not just similar vectors.
Temporal Decay Scoring
Recent memories matter more
Built-in exponential, linear, and gaussian decay functions score results by recency. A conversation from yesterday outranks a similar one from last month. No application-side re-ranking.
Agent Memory Lifecycle
From session to archive, automatically
Session collections with configurable TTL, auto-archival to cold storage, and summarization hooks. Your agent's long-term memory manages itself without custom pipelines.
Intelligent Storage Tiering
Hot performance. Cold economics.
Data automatically flows between NVMe hot storage and S3 Parquet cold storage based on access patterns. Queries span both tiers transparently. No other document database does this.
Time Travel Queries
Query any point in history
MVCC snapshots let you read the database as it existed at any timestamp. Debug agent hallucinations, satisfy auditors, and build undo functionality with a single query parameter.
MongoDB & Meteor.js Compatible
Change your connection string. That's it.
Full wire protocol compatibility. Mongoose, Prisma, PyMongo, and Meteor.js all work out of the box. Existing application code, queries, and indexes carry over with zero changes.
Context-Aware Retrieval in a Single Query
Traditional RAG fetches similar vectors and hopes for relevance. Thermocline's $contextSearch combines vector similarity with temporal decay so recent conversations score higher than old ones. Add relationship expansion to pull in referenced documents. Add session scoping to stay within the current interaction. One query returns precisely ranked context.
Learn more
Agent Memory That Manages Itself
Every AI agent accumulates context that needs to age, archive, and summarize over time. Thermocline handles this natively. Active sessions live on hot NVMe. As conversations age, they automatically tier to cold storage. Summarization hooks condense long histories without losing retrieval access. No cron jobs. No custom TTL logic.
Learn more
Hot Performance. Cold Economics.
Your active data lives on NVMe SSDs with sub-millisecond reads. Historical data automatically moves to columnar Parquet on object storage at 1/10th the cost. Every query transparently spans both tiers. You get the performance of a hot database and the economics of a data lake, without managing either.
Learn moreReplace Four Services. Cut Costs by 80%.
Stop paying for a vector database, an operational database, a context layer, and cold storage separately. Thermocline replaces them all.
Works With Your Existing Stack
Connect with any MongoDB driver, ODM, or tool. Your existing code works - just change the connection string.
MongoDB Drivers
ODMs & ORMs
Tools
Embedding Providers
See How Much You'll Save
Compare your current MongoDB storage costs with Thermocline Cloud's intelligent tiering.
Performance That Speaks for Itself
Your Entire AI Data Stack. One Database.
Stop stitching together vector databases, context layers, and cold storage. Thermocline handles documents, vectors, agent memory, context retrieval, and archival in a single system.
Engineered for Scale
Uptime SLA
Enterprise-grade reliability with multi-region replication and automatic failover.
Queries/sec
Horizontally scale your reads. Vertically scale your writes. Handle any workload.
“Thermocline replaced our entire data stack. We saved 80% on our MongoDB related AWS spend by offloading historical data to cold storage without losing required access.”
Strongly.AI
80% cost reduction
Cut MongoDB AWS spend by offloading to cold storage
A42 Labs
3x faster queries
Sub-millisecond vector search at scale
Janaru
Zero downtime migration
Migrated from MongoDB in hours
From the Blog
Build AI Applications on a Database That Gets It
One database for your vectors, your context, your agent memory, and your application data. Start free. Scale without limits.