# Cloudaeon

> Cloudaeon is an engineering-led Data and AI platform partner. We help enterprises design, build, fix, and run production-grade platforms on Databricks and Microsoft Fabric — turning fragile pilots into resilient, governed systems that scale.

Cloudaeon's focus areas are Databricks, Microsoft Fabric, Enterprise AI (RAG, MLOps, Agentic AI), Cloud (Azure, GCP, CloudOps), and Managed Services (DataOps, AIOps, CloudOps). Engagements range from short Proof-of-Value projects to dedicated engineering pods and long-term managed operations.

## Main Pages

- [Home](https://www.cloudaeon.com/): Cloudaeon overview and engineering-led approach to Data and AI
- [Who we are](https://www.cloudaeon.com/who-we-are): Company background, mission, and approach
- [Our team](https://www.cloudaeon.com/ourteam): Leadership and engineering team
- [Delivery model](https://www.cloudaeon.com/delivery-model): How Cloudaeon delivers from PoV to dedicated pods to managed operations
- [Contact us](https://www.cloudaeon.com/contact-us): Get in touch or book a call
- [Careers](https://www.cloudaeon.com/careers): Open roles at Cloudaeon
- [Newsroom](https://www.cloudaeon.com/newsroom): Company announcements and press
- [Privacy policy](https://www.cloudaeon.com/privacy-policy): How Cloudaeon handles personal data

## Services

- [Services overview](https://www.cloudaeon.com/services): Full catalogue of services across Data, AI, Cloud, and Managed Services
- [Databricks](https://www.cloudaeon.com/services/databricks): Lakehouse engineering, Unity Catalog, governance, cost optimisation, and rescue work
- [Microsoft Fabric](https://www.cloudaeon.com/services/microsoft-fabric): Fabric implementation, modernisation, and production engineering
- [Enterprise Artificial Intelligence](https://www.cloudaeon.com/services/enterprise-artificial-intelligence): Production AI, RAG, MLOps, Agentic AI, and AI governance
- [Cloud](https://www.cloudaeon.com/services/cloud): Azure, GCP, landing zones, DevSecOps, and CloudOps
- [Managed Services](https://www.cloudaeon.com/services/managed-services): DataOps, AIOps, and CloudOps for production platforms

## Solutions

- [Solutions overview](https://www.cloudaeon.com/solutions): Packaged solutions for enterprise AI and Lakehouse modernisation
- [AI Hub](https://www.cloudaeon.com/solutions/ai-hub): Secure, governed, repeatable enterprise AI within your tenant
- [Lakehouse Build and Modernisation](https://www.cloudaeon.com/solutions/lakehouse-modernisation): Stabilise, govern, and modernise Databricks or Microsoft Fabric Lakehouse platforms

## Resources

- [Insights](https://www.cloudaeon.com/insights): Engineering articles, playbooks, and thought leadership
- [Case studies](https://www.cloudaeon.com/case-study): Customer outcomes across Databricks, Fabric, AI, and Managed Services
- [Use cases](https://www.cloudaeon.com/use-cases): Industry and capability use cases
- [Blog archive](https://www.cloudaeon.com/blog): Legacy blog posts covering foundational cloud, big data, and analytics topics

## Partners

- [Partner with us](https://www.cloudaeon.com/partners-with-us): Partnership overview
- [Databricks partner](https://www.cloudaeon.com/partners-with-us/databrickspartner): Cloudaeon's Databricks partnership and capabilities
- [Microsoft Fabric partner](https://www.cloudaeon.com/partners-with-us/fabricpartner): Cloudaeon's Microsoft Fabric partnership and capabilities
- [Databricks](https://www.cloudaeon.com/partner/databricks): Databricks partner profile
- [Microsoft](https://www.cloudaeon.com/partner/microsoft): Microsoft partner profile
- [Prophecy](https://www.cloudaeon.com/partner/prophecy): Low-code data transformation on Databricks
- [Fivetran](https://www.cloudaeon.com/partner/fivetran): Data integration partner
- [Sigma](https://www.cloudaeon.com/partner/sigma): Analytics partner

## Events

- [Big Data LDN 2026](https://www.cloudaeon.com/big-data-ldn-2026): Cloudaeon at Big Data London 2026, Olympia, Stand C60

## Case Studies

- [M&S cuts migration time 70% with Unity Catalog accelerator](https://www.cloudaeon.com/case-study/ms-cuts-migration-time-70-with-unity-catalog-accelerator%2F)
- [Real-time data driving M&S marketing success](https://www.cloudaeon.com/case-study/real-time-data-driving-m%26s-marketing-success-)
- [Rule-driven data quality framework for a multi-source Azure Lakehouse](https://www.cloudaeon.com/case-study/rule-driven-data-quality-framework-for-a-multi-source-azure-lakehouse)
- [Unified data governance with Microsoft Purview](https://www.cloudaeon.com/case-study/unified-data-governance-with-microsoft-purview%2F)
- [Envu data transformation with Cloudaeon](https://www.cloudaeon.com/case-study/envu-data-transformation-case-study-with-cloudaeon%2F)
- [Nasuni: 100% SLA compliance with managed services](https://www.cloudaeon.com/case-study/nasuni-achieved-100-compliance-with-sla-response)
- [On-prem to cloud data migration via Informatica](https://www.cloudaeon.com/case-study/on-prem-to-cloud-data-migration-via-informatica%2F)
- [Managed services for Cloudera with 60% less setup time](https://www.cloudaeon.com/case-study/managed-services-for-cloudera-with-60-less-setup-time%2F)
- [Databricks supply chain intelligence modernisation](https://www.cloudaeon.com/case-study/databricks-supply-chain-intelligence-modernisation)
- [Always-on managed services: DataOps, AIOps, CloudOps](https://www.cloudaeon.com/case-study/always-on-managed-services-dataops-aiops-cloudops)
- [Enterprise RAG with guardrails and AI Ops](https://www.cloudaeon.com/case-study/enterprise-rag-guardrails-ai-ops)
- [Cloud landing zone and DevSecOps automation](https://www.cloudaeon.com/case-study/cloud-landing-zone-devsecops-automation)
- [Microsoft Fabric modernisation and BI performance](https://www.cloudaeon.com/case-study/microsoft-fabric-modernisation-bi-performance)
- [Databricks Lakehouse rescue and modernisation](https://www.cloudaeon.com/case-study/databricks-lakehouse-rescue-modernisation)

## Use Cases

- [Fragmented shop-floor data to predictive manufacturing intelligence](https://www.cloudaeon.com/use-case/from-fragmented-shop-floor-data-to-predictive-manufacturing-intelligence)
- [Reinventing e-commerce returns with agentic AI](https://www.cloudaeon.com/use-case/reinventing-e-commerce-returns-with-agentic-ai%2F)
- [AI assistant speeds contract queries and reviews](https://www.cloudaeon.com/use-case/ai-assistant-speeds-contract-queries-and-reviews)
- [AI assistant transforms bakery operations and training](https://www.cloudaeon.com/use-case/ai-assistant-transforms-bakery-operations-and-training%2F)
- [Enterprise knowledge assistant with trusted RAG](https://www.cloudaeon.com/use-case/enterprise-knowledge-assistant-%28trusted-rag%29)
- [Agentic workflow automation that survives production](https://www.cloudaeon.com/use-case/agentic-workflow-automation-survives-production)
- [Real-time streaming pipeline for retail using Prophecy](https://www.cloudaeon.com/use-case/real-time-streaming-pipeline-for-the-retail-sector-using-prophecy)
- [Soda data quality integration using Prophecy](https://www.cloudaeon.com/use-case/soda-data-quality-integration-using-prophecy%2F)
- [Boosting performance with Synapse-to-Fabric migration](https://www.cloudaeon.com/use-case/boosting-performance-with-synapse-to-fabric-migration)
- [Unifying data platforms with a federated Lakehouse](https://www.cloudaeon.com/use-case/unifying-data-platforms-with-a-federated-lakehouse)
- [Production-grade Lakehouse modernisation for Databricks](https://www.cloudaeon.com/use-case/production-grade-lakehouse-modernisation-for-databricks-)
- [Operational-grade real-time analytics on Databricks](https://www.cloudaeon.com/use-case/operational-grade-real-time-analytics-on-databricks-)
- [Fabric modernisation without fragility](https://www.cloudaeon.com/use-case/fabric-modernisation-without-fragility)
- [AI-ready cloud foundation for data and analytics](https://www.cloudaeon.com/use-case/ai-ready-cloud-foundation-for-data-analytics)
- [Always-on operations for Data, AI, Cloud](https://www.cloudaeon.com/use-case/always-on-operations-for-data-ai-cloud)
- [From demo AI to reliable, operated systems](https://www.cloudaeon.com/use-case/from-demo-ai-to-reliable%2C-operated-systems-)

## Insights

- [How enterprise RAG solutions transform AI search and knowledge retrieval](https://www.cloudaeon.com/insights/how-enterprise-rag-solutions-transform-ai-search-and-knowledge-retrieval)
- [Why enterprise RAG hallucinates and the engineering fixes that work](https://www.cloudaeon.com/insights/why-enterprise-rag-hallucinates-and-the-engineering-fixes-that-actually-work)
- [Building production-grade RAG architecture: the engineering playbook](https://www.cloudaeon.com/insights/building-production-grade-rag-architecture%3A-the-engineering-playbook)
- [MLOps for LLM and classical ML: hybrid delivery, monitoring, and governance](https://www.cloudaeon.com/insights/mlops-for-llm-classical-ml-the-hybrid-delivery-monitoring-and-governance-pattern)
- [DataOps in the modern enterprise: reliability, observability, and continuous delivery](https://www.cloudaeon.com/insights/dataops-in-the-modern-enterprise%3A-reliability%2C-observability-%26-continuous-delivery)
- [AIOps for enterprise AI: reliability, guardrails, and monitoring](https://www.cloudaeon.com/insights/aiops-for-enterprise-ai%3A-reliability%2C-guardrails-%26-monitoring)
- [From landing zone to CloudOps: engineering a cloud platform that holds under change](https://www.cloudaeon.com/insights/from-landing-zone-to-cloudops%2C-engineering-a-cloud-platform-that-holds-under-change)
- [Fabric in production: real failure modes and the fixes that hold](https://www.cloudaeon.com/insights/fabric-in-production%3A-real-failure-modes-(not-demos)-and-the-fixes-that-actually-hold)
- [Microsoft Fabric: unified AI-ready data platform](https://www.cloudaeon.com/insights/microsoft-fabric-unified-ai-ready-data-platform)
- [Databricks rescue missions: fixing governance, pipelines, and DBU cost](https://www.cloudaeon.com/insights/databricks-rescue-missions%3A-fixing-governance%2C-pipelines-and-dbu-cost-(without-rebuilding-everything))
- [Databricks: why operations, optimisation, and continuity separate winners from also-rans](https://www.cloudaeon.com/insights/databricks-why-operations-optimisation-and-continuity-separate-the-winners-from-the-also-rans)
- [Unity Catalog migration: why strategy, not just tools, determines success](https://www.cloudaeon.com/insights/unity-catalog-migration-why-strategy-not-just-tools-determines-success)
- [Why building AI in-house may be riskier than you think](https://www.cloudaeon.com/insights/why-building-ai-in-house-may-be-riskier-than-you-think)
- [Enterprise AI fails in production ownership, not the model](https://www.cloudaeon.com/insights/enterprise-ai-doesn%E2%80%99t-fail-in-the-model.-it-fails-in-production-ownership.)
- [Agentic AI isn't failing because models are weak](https://www.cloudaeon.com/insights/agentic-ai-isn%E2%80%99t-failing-because-models-are-weak.)
- [MCP agent architecture for enterprise automation: tool governance, safety, and observability](https://www.cloudaeon.com/insights/mcp-agent-architecture-for-enterprise-automation%3A-tool-governance%2C-safety-boundaries-and-observability)
- [Simplify streaming ETL with Databricks Delta Live Tables](https://www.cloudaeon.com/insights/simplify-streaming-etl-with-databricks-delta-live-tables%2F)
- [Streamlining ETL with Databricks Lakeflow](https://www.cloudaeon.com/insights/streamlining-etl-with-databricks-lakeflow)
- [Why add a platinum layer to Databricks medallion architecture](https://www.cloudaeon.com/insights/why-add-a-platinum-layer-to-databricks-medallion-architecture%2F)
- [Airflow 2.x to 3.x migration: how automation cut manual work by 70%](https://www.cloudaeon.com/insights/airflow-2x-to-3x-migration-made-easy-how-automation-cut-manual-work-by-70%2F)
- [Building a smarter Azure cost analysis pipeline with Power BI and Databricks Genie](https://www.cloudaeon.com/insights/building-a-smarter-azure-cost-analysis-pipeline-with-power-bi-and-databricks-genie%2F)
- [Synthetic data generation](https://www.cloudaeon.com/insights/synthetic-data-generation)
- [Deploying ReactJS apps on Azure Databricks: a step-by-step guide](https://www.cloudaeon.com/insights/deployingreactjs-apps-on-azure-databricks-a-step-by-step-guide)
- [Clearing your path to AI](https://www.cloudaeon.com/insights/clearing-your-path-to-ai%2F)
- [From capacity crunch to competitive edge: rethinking data and AI hiring](https://www.cloudaeon.com/insights/from-capacity-crunch-to-competitive-edge-why-smart-enterprises-are-rethinking-data--ai-hiring%2F)
- [Mid-market platforms don't fail on technology, they fail on ownership](https://www.cloudaeon.com/insights/mid-market-platforms-don%E2%80%99t-fail-on-technology.-they-fail-on-ownership)
- [Webinar: taking AI beyond the hype with Unity Catalog](https://www.cloudaeon.com/insights/webinar-taking-ai-beyond-the-hype-with-unity-catalog%2F)

## Optional

- [Sitemap](https://www.cloudaeon.com/sitemap.xml): Full XML sitemap of cloudaeon.com