Stop feeding your billion-dollar agents with penny-stock plumbing. Get RVP: Recent, Vulgate, Plain.
Current RAG systems are fundamentally broken. They give your sophisticated AI agents fuzzy, unreliable context through inefficient infrastructure.
Vector searches return "maybe relevant" results. Agents need deterministic, exact context - not fuzzy approximations.
JSON serialization adds 10-100ms per request. At scale, this becomes seconds of wasted compute on data marshalling.
Regulated industries need to know exactly what data an agent saw. RAG provides zero verifiable lineage.
Data gets copied 3-5 times between processes. Your expensive GPU memory is full of redundant context copies.
Three principles that transform how AI agents receive context.
Live gRPC streaming delivers real-time updates. Agents see current data, not stale cached snapshots from minutes ago.
Apache Arrow provides a canonical format. Any language reads the same schema - Java, Python, Rust, all speak the same tongue.
Zero-copy IPC via memory-mapped files. Data stays where it is - agents read directly from shared memory.
Built from the ground up for AI agent infrastructure.
Java 25 Foreign Function & Memory API enables true zero-copy data transfer. Memory-mapped files deliver context at RAM speed.
Hierarchical topics (finance.trades.realtime) with Arrow schema versioning. Subscribe to patterns with wildcards.
Content-addressable trace IDs with eBPF kernel-level auditing. Complete provenance for regulatory compliance.
Anthropic Model Context Protocol implementation. Standardized resource and tool access for any MCP-compliant agent.
Server-streaming subscriptions with Mutiny reactive core. Agents receive IPC handles, not inline payloads.
JetBrains Xodus provides embedded ACID storage. Pure Java, no external dependencies, battle-tested reliability.
Clean separation between agents, core services, and the data plane.
Python (PyArrow) | Java (FFM) | Rust (Arrow2) | Any MCP Client
Context Orchestrator | Zero-Copy IPC | Arrow Serializer | Lineage Tracker | Xodus Store
REST :8080 | gRPC :9000 | MCP /mcp | Memory-Mapped Files /dev/shm
Real improvements over traditional RAG infrastructure.
| Metric | Traditional RAG | Qinematos |
|---|---|---|
| Context Delivery Latency | 10-100ms | <5ms |
| Memory Copies | 3-5 copies | 0 copies |
| CPU Overhead | High (serialization) | 40% lower |
| Throughput | Network-bound | RAM-speed |
| Audit Trail | None | Full lineage + eBPF |
| Cross-Language | JSON conversion | Native Arrow |
Production-grade components you can trust.
Foreign Function & Memory API for native memory access without JNI overhead.
Cloud-native runtime with GraalVM support. Lightning-fast startup, low memory footprint.
Industry-standard columnar format. Cross-language compatibility out of the box.
Reactive streaming with non-blocking I/O. High-performance message delivery.
Embedded ACID key-value store. Pure Java, transactional, reliable.
Distributed tracing and metrics. Full observability for production deployments.
From clone to running API in a few commands.
git clone https://github.com/qinematos.git
cd qinematos/qinematos-java25-quarkus
mvn clean package -DskipTestsmvn quarkus:devServer starts on :8080 (REST) and :9000 (gRPC)
# Health check
curl http://localhost:8080/api/v1/health
# Create a topic
curl -X POST http://localhost:8080/api/v1/topics \
-H "Content-Type: application/json" \
-d '{"name": "demo.context", "schemaType": "generic.keyvalue"}'
# Try zero-copy demo
curl -X POST http://localhost:8080/demo/zero-copy?records=100Building the future of AI agent infrastructure, one milestone at a time.
Join the movement to give AI agents the infrastructure they deserve.