Milvus Vector Database Services

High-throughput vector storage, hybrid search, and streaming ingestion for production RAG

Build retrieval-ready systems with Milvus resilience

Oodles AI designs and deploys production-grade Milvus vector database systems. We architect collections, partitions, indexes, and replication strategies, and implement ingestion, compaction, observability, and access controls to ensure accurate and low-latency vector search at scale.

What we build with Milvus

Oodles AI delivers Milvus-based reference architectures covering ingestion, indexing, and operations—optimized for scale, reliability, and enterprise compliance.

• Milvus cluster architecture: partitions, replicas, TTL, and compaction
• Vector and hybrid search pipelines with metadata filtering and re-ranking
• Streaming and batch ingestion with schema validation and index lifecycle management
• Operational automation: backup strategies, rolling upgrades, and SLA monitoring

Multi-cloud & VPC Hosting

Deploy Milvus on Kubernetes, bare metal, or private VPC environments with secure secrets management and isolation.

Schema & Collection Design

Design Milvus collections, vector dimensions, indexes, and metadata fields for dense, sparse, and multi-modal embeddings.

Ingestion & Pipelines

Design Milvus collections, vector dimensions, indexes, and metadata fields for dense, sparse, and multi-modal embeddings.

Monitoring & Reliability

Implement Milvus monitoring for QPS, recall, compaction, memory usage, and failover readiness using observability tooling.

High-impact Milvus use cases

Knowledge Retrieval & RAG

Vector-based retrieval over documents and knowledge bases using Milvus for RAG pipelines with controlled recall and latency.

Agent Memory Stores

Short- and long-term vector memory stores backed by Milvus for agent and autonomous system workflows.

Search Modernization

Combine keyword, BM25-style filters, and Milvus vector search to modernize enterprise and customer-facing search systems.

Document Intelligence

Store and retrieve document embeddings with Milvus using structured metadata, retention policies, and access controls.

Telemetry & Anomaly Mining

Vectorize telemetry, logs, or signals and use Milvus similarity search to surface related incidents and anomalies.

Integrations & tooling

Oodles AI integrates Milvus with ingestion pipelines, security layers, and LLM orchestration frameworks to enable production-ready vector search systems.

Milvus + Attu Milvus Operator / K8s LangChain & LlamaIndex Kafka / Flink / Airbyte Hybrid Search + BM25 OpenAI / Claude / Llama Azure / AWS / GCP VPC Grafana & Prometheus Role-based Access & Audit

Delivery approach

A structured engagement model used by Oodles AI to design, deploy, and optimize Milvus vector database environments.

Goals & Workloads: Define recall targets, latency constraints, compliance requirements, and data domains for Milvus workloads.

Data & Policy Setup: Configure data sources, chunking logic, partitions, TTL policies, and role-based access for Milvus collections.

Indexing & Evaluation: Tune Milvus index types and parameters, validate recall and precision, and benchmark hybrid search performance.

LLM & App Integrations: Integrate Milvus with LLM stacks, application services, caching layers, and retrieval pipelines.

Operations & Optimization: Operate Milvus clusters with monitoring, cost optimization, automated backups, and continuous performance tuning.

Request For Proposal

Ready to build with Milvus? Let's talk

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