Data Services

Build, Modernize, Govern, and Operate Your Enterprise Data Ecosystem

100+

Global clients

20+

Years experience

5

Industries served

500+

Projects delivered

data

Trusted by Leading Brands

Trusted by 100+ global companies across Retail, Manufacturing, Healthcare, Finance, and Technology

Most enterprises have data.
Few have a data foundation that actually works.

Fragmented data stacks

Data warehouses, data lakes, and operational databases that don't talk to each other. Your teams spend hours preparing data instead of analysing it.

AI projects with no data runway

Machine learning and GenAI initiatives that stall because training data is dirty, unstructured, or inaccessible. No data readiness, no AI ROI.

Governance gaps under compliance pressure

Data warehouses, data lakes, and operational databases that don't talk to each other. Your teams spend hours preparing data instead of analysing it.

Legacy infrastructure blocking scale

On-premise data warehouses and ageing pipelines that can't handle modern analytical workloads, real-time data, or cloud-native AI integrations.

No single view for decision-makers

Executives relying on static spreadsheets and disconnected reports. No unified, trusted metrics to drive operational and strategic decisions.

Projects that deliver late or not at all

Data transformation programmes that run over budget, lose stakeholder confidence, and fail to deliver measurable business outcomes.

Six capabilities. One integrated data practice.

Saxon AI delivers across the full data lifecycle — from strategy and engineering through governance, analytics, and AI-led intelligence. Every service is designed to make your data foundation production-grade and AI-ready.
01

Data Strategy & Roadmap

Assess your current state, define your target architecture, and build a prioritised roadmap that aligns data investments to business outcomes.

02

Data Engineering

Design and build reliable, scalable data pipelines that ingest, transform, and serve clean data to reporting, analytics, and AI workloads.

03

Data Migration & Modernization

Move from legacy on-premise warehouses to cloud-native architectures on Azure Synapse, Databricks, or Fabric — with zero data loss and minimal disruption.

04

Data Governance

Establish policies, ownership, lineage, and quality controls that make your data trustworthy, compliant, and ready to serve AI and analytics at scale.

05

Reporting & Analytics

Build interactive Power BI dashboards, self-service analytics, and operational reports that give every decision-maker a single, trusted view of the business.

06

AI & Machine Learning

Apply ML models, predictive analytics, and AI-led insights directly on your data platform — from demand forecasting and churn prediction to anomaly detection.

One partner for the entire data lifecycle

Most data projects fail not because of bad technology — but because strategy, engineering, and governance are delivered by different vendors who never truly coordinate. Saxon AI owns all of it.

Single accountable delivery model

Strategy, architecture, engineering, governance, and analytics — all under one engagement, one team, one outcome.

AI-first data architecture

Every data environment we build is engineered to serve AI and ML workloads from day one — not retrofitted later at significant cost.

Microsoft & Databricks certified

Certified delivery on Azure Synapse, Microsoft Fabric, Power BI, and Databricks — the platforms that matter for enterprise data at scale.

Our credentials & partnerships

What Saxon AI data engagements deliver

Measured results from production data environments deployed across global enterprises.

60%

Reduction in time spent preparing data for reporting and analytics

3X

Faster delivery of new analytics features after data foundation modernization

40%

Lower total cost of ownership after migration from legacy on-premise stacks

99.9%

Pipeline reliability achieved with automated monitoring and alerting

Real engagements. Measurable outcomes.

See how Saxon AI has helped enterprises across pharma, luxury retail, and manufacturing build data foundations that drive real operational intelligence.
Data

AI-Driven Demand Intelligence for Luxury Supply Chain Planning

Delivering SKU-level demand intelligence through machine learning models and real-time planning dashboards for production and distribution teams. Unified fragmented supply chain data into a single intelligent layer that drives daily planning decisions.

SKU-level

Demand accuracy

Real-time

Planning dashboards

ML

Forecasting models

data2

Unified Retail Analytics Platform for Customer Happiness & Sales Intelligence

Designed and implemented an integrated data platform for a leading retail brand to unify customer feedback, survey responses, and sales transactions across multiple touchpoints. The solution consolidates data from disparate enterprise systems into a centralized analytics layer, enabling real-time visibility into customer sentiment and business performance.

100%

visibility into customer feedback

50%

faster report generation cycle

40%

reduction in reporting errors

Data solutions built for your sector

We bring deep domain context to every engagement — because a data strategy for a pharma company looks very different from one for a manufacturer or retailer.

Microsoft Fabric

Microsoft Fabric

End-to-end analytics on the unified SaaS platform — data engineering, warehousing, and Power BI in one experience.

Azure Synapse

Azure Synapse Analytics

Limitless analytics with deeply integrated data lake, warehouse, and Spark — designed for enterprise-scale workloads.

Databricks

Databricks Lakehouse

Unified analytics and ML on a single lakehouse platform. Our Databricks partnership ensures best-practice implementation.

Power BI

Power BI & Analytics

Self-service BI, embedded analytics, and enterprise reporting built on Power BI — the most widely adopted BI platform.

How a Saxon AI data engagement works

A structured, outcome-driven process from assessment to operational excellence — with clear milestones and accountability at every stage.

Data Discovery

Assess your current data estate, identify quality issues, map sources, and benchmark maturity against delivery goals.

Architecture & Design

Define target state architecture, select platforms, model data domains, and create a prioritised delivery roadmap.

Engineering & Pipelines

Implement pipelines, data models, governance controls, and analytics layers in iterative, testable sprints.

Testing & Validation

Reconcile data quality, validate outputs against source systems, and certify the data environment for production.

Run & Optimise

Monitor pipeline health, manage performance, deliver enhancements, and continuously optimise cost and quality.

Questions about enterprise data services

What does an enterprise data services engagement with Saxon AI cover?

We cover the full data lifecycle — strategy and roadmap, data engineering and pipeline design, migration from legacy systems, governance and compliance frameworks, reporting and analytics delivery, and AI/ML enablement. Engagements can be scoped to a single capability or structured as a full transformation programme, depending on your priorities and current maturity.

Every engagement starts with a structured discovery phase. We assess your current data sources, toolchain, quality issues, team capabilities, and business objectives before recommending any technology or architecture. The output is a prioritised roadmap with cost estimates, timelines, and defined outcomes — so you know exactly what you’re committing to before work begins.
Our primary delivery platforms are Microsoft Fabric, Azure Synapse Analytics, Databricks Lakehouse, and Power BI. As a Microsoft Solutions Partner and Databricks Delivery Partner, we have certified expertise on both ecosystems. We recommend platforms based on your existing investment, workload profile, and long-term strategy — not vendor preference.
Governance is built into every engagement from day one — not added at the end. We implement data cataloguing, lineage tracking, access controls, data quality rules, and audit trails aligned to GDPR, HIPAA, SOX, or sector-specific regulatory requirements. We use Microsoft Purview and Unity Catalog (Databricks) as the primary governance layers, depending on your platform.
Yes. We follow a structured migration methodology that runs the legacy and cloud environments in parallel during transition, with full data reconciliation and rollback capability at each milestone. We have delivered migrations from Oracle, Teradata, SQL Server, and Netezza to Azure Synapse and Databricks — with zero data loss and minimal operational disruption.
AI readiness requires clean, well-documented, consistently structured data. We enforce data quality standards at ingestion, implement feature stores for ML workloads, build semantic layers for LLM access, and design data architectures that support vector databases and retrieval-augmented generation (RAG). Every data environment we build is designed to serve both traditional BI and advanced AI workloads from the same foundation.
Yes. We offer a managed data operations service that covers pipeline monitoring, performance optimisation, incident response, platform upgrades, and continuous delivery of new data products. Scope is flexible — some clients want full managed operations; others prefer a standing team-extension model. We work around your internal capabilities and governance model.
A focused engagement — such as building a new data pipeline layer or delivering a Power BI analytics environment — typically runs 4–8 weeks. A full data modernisation programme (strategy through migration and governance) runs 3–9 months depending on the complexity of your environment and the number of data domains in scope. We always deliver in phases with measurable milestones, so you see value incrementally rather than waiting for a single go-live.

Ready to build a data
foundation that works?