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.
Google Cloud VPC Service Controls & CMEK Compliant
All memyoo inference routes are locked into Customer-Managed Encryption Keys within dedicated GCP project perimeters.
Built for Scalability by Design
Founded by Mahsuni Andac
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.”