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Private AI Factory

Based on vLLM, Kubeflow, Slurm, LangGraph, Milvus, OpenWebUI, Feast, Spark, and Kafka.

Deploy private LLM inference, RAG, ML pipelines, and agent workflows on your infrastructure — backed by XaasIO’s SLA-driven, around-the-clock enterprise support. XaasIO AI Factory is built on upstream open source and designed for production AI: governance, observability, security, and predictable operations.

Request an AI Factory Blueprint

What You Get

Private LLM Inference & Apps

Production-ready inference endpoints, internal chat experiences, and model serving patterns with scaling and controls.

RAG & Knowledge Systems

Vector search + retrieval pipelines with governed data connectors, evaluation, and traceability for enterprise use.

ML Pipelines & Feature Store

Training/inference workflows, feature engineering, and reproducible pipelines from experimentation to production.

Core Capabilities

Inference & Serving

High-throughput inference with vLLM
Model endpoints, versioning patterns, and canary rollout options
GPU utilization and capacity governance

Orchestration & Workflows

ML workflows and notebooks with Kubeflow
Batch scheduling for AI/ML with Slurm
Agent workflows with LangGraph

Retrieval & Vector Search

Vector database with Milvus
RAG pipelines, indexing patterns, evaluation workflow hooks

Data & Streaming Foundation

Batch and distributed computing with Spark
Streaming ingestion and event pipelines with Kafka
Feature store patterns with Feast

User Experience

AI UX layer with OpenWebUI
Team workspaces and controlled access patterns

Observability & Operations

Metrics and dashboards with Grafana
Monitoring and alerting with Zabbix
Log analytics with OpenSearch
Runbooks + alert tuning for production operations

Reference Architecture (Production AI on Open Source)

XaasIO AI Factory is delivered as a layered architecture so each capability can scale independently and remain governable.

Managed AI Factory by XaasIO

XaasIO operates the platform as a managed service with SLAs, upgrades, incident response, and continuous reliability improvement.

Included (high-level):

SLA-backed support (16×5 or 24×7 options)
Platform upgrades and patch cycles for AI stack components
Reliability engineering: incident response, RCA, problem management
Observability: dashboards, alerts, tuning, runbooks
Capacity planning and performance optimization (GPU/compute/storage)

Engagement Path (Blueprint → Pilot → Production)

AI Factory Blueprint
(1 – 2 weeks)

Use cases, architecture, security model, sizing, pilot milestones.

Pilot (4 – 6 weeks)

Working inference + RAG + pipelines with 1–2 priority use cases.

Production Rollout
(6 – 12 weeks)

Hardening, governance, scale-out, HA patterns, and operating cadence.

Managed Operations (Ongoing)

SLA-backed operations, upgrades, reliability and cost-performance tuning.

Use Cases

Downloads

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

AI Factory Overview (PDF)
AI Factory Reference Architecture (PDF)
vLLM Model Serving Guide (PDF)
RAG Blueprint: Milvus + LangGraph (PDF)
Managed AI Factory SLA Options (PDF)

Launch a Private AI Factory

Request an AI Factory Blueprint to validate architecture, security, sizing, and a pilot plan
-with SLA-backed managed operations from XaasIO.

Schedule Meeting