memyoo — Next-Gen AI Data Management & Real-Time Inference
Engineered to eradicate context retrieval latency. memyoo synchronizes real-time enterprise streaming datasets with continuous distributed vector indexing directly on Google Cloud Platform — delivering deterministic, sub-millisecond inference cache injection.
Engineered for Google Cloud Infrastructure
memyoo relies strictly on GCP enterprise backbones to ensure multi-region elasticity, sub-millisecond data coordination, and automated compute scaling during intensive model inference.
Vertex AI
Direct integration with Vertex AI Feature Store, real-time embeddings endpoints, and low-latency Foundation Model serving (Gemini & open LLMs).
Google Kubernetes Engine (GKE)
Autopilot clusters running high-throughput memyoo worker nodes with custom hardware acceleration (TPU v5e & NVIDIA H100 GPU slicing).
BigQuery
Petabyte-scale cold and warm storage layer leveraging BigQuery Vector Search and Zero-ETL streaming ingest for historical audit log analysis.
Cloud Firestore
Serverless NoSQL state machine handling concurrent agent lockings, session synchronization, and immediate event subscriptions across instances.
Planned: Google Cloud VPC Service Controls & CMEK
All memyoo inference routes are planned to use Customer-Managed Encryption Keys within dedicated GCP project perimeters.
Built for Scalability by Design
Founded by an independent developer
Founder & Systems Architect
Mission: Resilient, low-latency AI backbones
“Inference bottlenecks are fundamentally data coordination bottlenecks. With memyoo, we are building a zero-overhead data plane tailored directly for Google Cloud Platform, enabling enterprise AI applications to query live state without latency degradations.”