Managed AI Services
From infrastructure to inference, we run scalable, reliable, and secure AI workloads.
As AI adoption grows and scientific computing accelerates, operational requirements shift quickly. Running models, simulations, and data pipelines at enterprise scale demands GPU-optimized infrastructure, consistent orchestration, and deep domain expertise. Cylix provides the engineering and platforms needed to keep complex workloads stable, high performing, and secure.
Cylix brings together hardware engineering, platform tooling, and real-time operational support to design, deploy, and operate production-grade AI environments. From research labs to real-time financial modeling, we help enterprise, academic, and public sector teams operate with stability, predictable performance, and agility.
Managed AI Services Portfolio
Scalable, modular services designed to maintain performance, resilience, and compliance.
AI Workload Engineering & Model Operations
- LLM and transformer orchestration with optimized inference serving
- Retrieval-Augmented Generation system upkeep and knowledge-base hygiene
- Continuous monitoring of wor APIs, retraining triggers, and bias or drift detection
- Prompt management, version control, fine-tuning automation, safety alignment, and evaluation processes
End-to-End Managed Support & Lifecycle Services
- Monitoring, alerting, SLO and SLA tracking, and root-cause analysis
- Hardware diagnostics, firmware management, and RMA coordination
- Data integrity protection, backup processes, and disaster recovery for AI pipelines and artifacts
- Model lifecycle tracking, audit logging, governance workflows, and compliance reporting
- Quarterly infrastructure reviews, capacity planning, and cost or performance tuning
Platform & Infrastructure Management
- Hybrid orchestration across on-premise environments, private cloud, and AWS or Azure
- Secure multi-tenant workspace configuration including namespaces, quotas, RBAC, and secrets management
- Image registries, feature stores, vector databases, and artifact repositories
- Performance profiling for throughput and latency, accelerator utilization, and caching strategies
Data Foundations for AI
- Streaming and batch pipelines for ingest, transform, validation, and cataloging
- Governance and lineage practices including PII handling, retention policies, and access controls
- Gold-layer data curation that supports training consistency and reproducible evaluation
Start Your Managed AI Journey
- Managed AI PoC-as-a-Service
- We help you deploy faster, operate more reliably, and scale with confidence. Explore the services that support your entire AI lifecycle.
- Validate operations before scaling. We define SLOs, build observability into the stack, and run a production-grade PoC that exercises runbooks, incident workflows, and performance envelopes to confirm readiness.
HOW IT WORKS
Managed AI Operating Model
A clear, outcome-driven framework for reliable AI operations.
Discovery & Objectives
Map workloads, risks, and compliance drivers. Define SLAs, SLOs, and incident categories.
Data & Platform Readiness
Assess pipelines, governance, and architecture. Close security and performance gaps before deployment.
Infrastructure Design & Procurement
Architect GPU-optimized stacks with partners such as Dell, Hitachi, NVIDIA, and HPE.
Model Ops Enablement
Stand up MLOps workflows, RAG retrieval layers, evaluation harnesses, and rollout policies.
Validation & Hardening
Run chaos tests, load tests, and red-teamscenarios to confirm reliability, safety boundaries, and guardrails.
Production Cutover (Edge | On-Prem | Hosted)
Perform a controlled release with rollback plans and observability baselines to ensure smooth transition to production.
Operate & Optimize
Provide continuous monitoring, performance and cost optimization, security updates, and quarterly reviews.
Schedule an Exploration Call
Book NowWho We Serve
AI-first enterprises running multimodal, real-time inference workloads
Scientific institutions conducting large-scale simulation and modeling
Public-sector teams operating secure compute environments and sensitive datasets
Research hospitals and biotech running genomics and machine learning pipelines
Academic groups requiring predictable performance, uptime, and scalable compute
Why Partner with Cylix for Managed AI
- Deep Technical Fluency – AI engineers, hardware specialists, DevOps and Kubernetes architects, and HPC consultants with deep hands-on expertise.
- Hybrid Flexibility – Support for on-premise, cloud-native (AWS and Azure), and hybrid orchestration with a security-focused design approach.
- Mission-Critical Focus – Operational reliability for uptime-sensitive, performance-intensive environments that support national research and enterprise AI systems.
- AI-Aware Service Model – Operations aligned to model size, context window requirements, memory bandwidth, embeddings, and retraining cadence.
Service Add-Ons & Integrations
- Security integrations including CrowdStrike, Cisco, and Red Hat for SIEM, EDR, and compliance
- Collaboration environments such as JupyterHub, VS Code Server, RAPIDS, and Slurm integrations
- HPC usage and cost insights with utilization reporting and carbon-impact dashboards
- AI observability stacks including Prometheus, Grafana, Elastic, and OpenTelemetry
Let's Engineer Your AI & HPC Operations
for Performance, Resilience, and Scale
Whether you are running million-parameter simulations or low-latency AI assistants, Cylix keeps your infrastructure and models optimized, supported, and compliant. We ensure your AI and HPC environments operate reliably and scale with your growth.