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Private AI Factory (Managed)

Production LLM inference, RAG, ML pipelines, and agent workflows on your infrastructure

Deploy private AI with vLLM, Kubeflow, Slurm, LangGraph, Milvus, OpenWebUI, Feast, Spark, and Kafka. SLA-driven enterprise support with governance, observability, and predictable operations.

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Core Capabilities

Enterprise AI platform components

Inference & Serving

High-throughput vLLM inference, model versioning, and GPU governance for production deployments

Orchestration & Workflows

Kubeflow ML workflows, Slurm batch scheduling, and LangGraph agent orchestration

Retrieval & Vector Search

Milvus vector database, RAG pipelines, and evaluation hooks for knowledge systems

Data & Streaming

Spark batch computing, Kafka event pipelines, and Feast feature store integration

User Experience

OpenWebUI with team workspaces, access controls, and customizable interfaces

Observability & Operations

Grafana dashboards, Zabbix monitoring, OpenSearch analytics, and production runbooks

Engagement Path

From blueprint to production AI

1

AI Factory Blueprint

1-2 weeks

Use cases, architecture, security, sizing, pilot milestones

2

Pilot

4-6 weeks

Working inference, RAG, pipelines with 1-2 priority use cases

3

Production Rollout

6-12 weeks

Hardening, governance, scale-out, HA patterns

4

Managed Operations

Ongoing

SLA-backed support, upgrades, reliability tuning

Key Use Cases

What you can build with Private AI Factory

Private LLM inference for internal copilots
Enterprise RAG for knowledge search and Q&A
Agent workflows for IT ops/data ops/support automation
ML pipeline training and deployment
Real-time AI pipelines with streaming data
Feature engineering and consistent serving

Request an AI Factory Blueprint

Validate architecture, security, sizing, and get a pilot plan with SLA-backed managed operations for your private AI platform.

Schedule Meeting