Ivy The AI Context Engine
Fresh context for every inference. One SQL query across Kafka, MQTT, sensors, databases—always fresh, never stale.
Your AI Is Starving
Batch pipelines. Stale embeddings. Five systems to query before your model gets context. By the time your RAG retrieves, the world has moved on. Agents need answers in milliseconds, not hours.
The Context Layer Your AI Needs
Ivy captures data from everywhere—Kafka, MQTT, AMQP, IoT, databases—and makes it queryable in real-time. One platform. Always fresh. SQL access.
Sub-50ms Freshness
Context that's current, not cached. Real-time ingestion, real-time query. Your AI never waits.
SQL Over Streams
Query live data with standard SQL. No custom consumers, no pipeline code. Self-serve context.
Captures From Anywhere
Kafka, MQTT, AMQP, Pulsar, NATS—native protocol adapters, not connectors. Bring your existing producers.
Cloud-Native Storage
S3-tiered, Iceberg-native. Infinite retention at object storage costs. Historical + real-time unified.
Built for the Context-Hungry
Agents don't sleep. They query thousands of times per minute. RAG needs fresh retrieval, not yesterday's index. ML features need streaming and batch unified. Ivy is infrastructure designed for AI workloads.
Real-Time RAG
Query across all sources in one SQL statement. Fresh context for every LLM request—no stale batch pipelines.
Agent-Native
Built for the query patterns of autonomous AI. Thousands of requests per second, sub-50ms response.
ML Feature Pipelines
Stream + batch unified. Point-in-time correct features without the pipeline spaghetti.
Training Data on Demand
SQL over streams means simpler dataset creation. No ETL, no CDC complexity, no waiting.
Native CDC
Stream database changes without Debezium, without connectors. Built-in change data capture.
Transactions
ACID guarantees across all protocols. Kafka-style transactions without protocol lock-in.
S3-Tiered Storage
Infinite retention at object storage costs. Hot data in memory, cold data in S3.
Governance Built-In
RBAC, audit logging, encryption—verified at compile-time. Security by design, not bolted on.
Native Integrations
Postgres, Iceberg, Databricks, Snowflake, ClickHouse. Your data stack, connected.
Integrated Gateway
Kafka proxy capabilities built in. Governance without a separate product.
Zero Migration Risk
Don't rewrite producers. Don't change consumers. Connect what you have—Ivy speaks your protocol natively.
IoT at Scale
Millions of MQTT devices feeding the same context layer as enterprise Kafka. Unified, not translated.
Event Backbone
All protocols, one source of truth. Accessible from anywhere, queryable by anyone.
LangChain & LlamaIndex
One retriever connection for all your context sources. No adapter sprawl.
Parallel Cutover
Run alongside existing systems. Migrate when ready. No big bang required.
Feed Your AI Stack
Not replacing your tools. Feeding them fresh context.
Native Integrations
One context layer, every AI tool.
One data source for all retrieval. No adapter sprawl.
Native CDC keeps embeddings fresh. Pinecone, Weaviate, Qdrant—continuously fed.
Unity Catalog, Iceberg tables. Your lakehouse, our streams.
First-class AWS integration for ML workloads.
Where AI Gets Its Context
The bottleneck shifted from compute to context. Ivy is where context lives—fresh, unified, queryable.
Launching 2026 — Early access available now