Advanced Analytics
Predictive modelling, machine learning, BI and visualisation, and process automation, moving teams from describing the past to anticipating the future.
What it is
From legacy estates to AI-ready platforms
Organisations with legacy data architectures spend 10–20% of budgets fixing foundations, with over half of the effort going to maintenance instead of innovation.
Every new use case forces engineers to start from scratch, locating data, decoding logic, rebuilding pipelines. We combine architecture, governance, analytics and agentic AI so that work is done once, properly, and reused.
And then, we scale it.
Services
What we deliver
Five services that work as one practice, from the architecture underneath to the analytics on top, accelerated by our own platforms.
Our frameworks
From data foundations to business impact.
LACE modernises your data foundation; Cortex keeps it continuously optimised for cost, performance and efficiency.
Start
The legacy estate
SAS
Oracle
SAP BW
Hadoop
Undocumented logic, duplicated pipelines, rising cost
LACE OS
Agentic AI operating system
LACE governs and orchestrates AI agents, with human validation at every step. Specialised agents cover SAS, Oracle, SAP BW and Hadoop, inside a knowledge base aligned with your rules and standards.
Without orchestration, large-scale AI programmes become chaotic: agents duplicate work, produce unreliable outputs and ignore critical business logic. LACE OS solves that coordination problem.
Five connected stages
01
Understand legacy, faster
Use AI-driven analysis to uncover data structures, lineage and dependencies at speed.
02
Design data models
Target-state modelling on modern standards: Data Lakehouse, Data Vault, Star Schema.
03
Extract business logic
Reverse-engineer the rules, calculations and flows buried in legacy code, knowledge that often exists nowhere else.
04
Generate data pipelines
Robust automated ETL/ELT pipelines, enabling parallel data movement and transformation at scale.
05
Govern every step
Governance, data quality and automated DataOps practices for sustainable long-term operation.
Cortex
COST & FINOPS INTELLIGENT FRAMEWORK
Cortex gives leadership a clear, continuous view of how efficiently your data platform is running and what it costs.
It helps prevent waste, avoid budget surprises, and reinvest the savings elsewhere. Runs entirely on your own infrastructure, with no data ever shared outside your organisation.
What it provides
Optimised cost, greater predictability
Continuously uncover inefficiencies and turn them into measurable savings.
Accountability built into every decision
Make cost ownership visible across teams, projects and workloads.
See issues before they become disruption
Identify performance and cost risks early, before they affect the business.
Prioritise what creates the most value
Focus optimisation efforts where they deliver the greatest financial impact.
One view across business and technology
Connect cost, performance and priorities through a shared source of insight
Control stays with you
Cortex runs within your environment, with no data shared externally.
How we create value
Foundations that pay for themselves
Faster time-to-value, lower delivery risk, and platforms your teams can maintain and extend.
Lower technical debt
Less budget spent maintaining foundations, more spent on initiatives that move the business.
Faster delivery
Pre-built framework components and agent-generated pipelines replace work rebuilt from scratch each project.
Trusted data
Discoverable, documented and consistent data assets, with lineage and stewardship in place.
Foresight
Risks detected early and opportunities identified, with insight accessible to everyone who needs it.
Governed AI
Agents orchestrated under human validation, with auditable outputs and controlled scale.
Our approach
Three phases, from assessment to scale.
Every engagement runs the same way: understand the estate you have, build the platform you need, then operate and extend it with your teams.
PHASE 01
Assessment
Estate discovery and dependency mapping, target architecture, governance gaps, business case and modernisation roadmap.
PHASE 02
Build
Target data models, business-logic extraction, pipeline generation, quality and governance implementation on the reference frameworks.
PHASE 03
Operate & scale
DataOps practices, stewardship and enablement, analytics adoption, and extension to the next domain.
The data chain
Inside those phases, every platform we build moves through five layers, from legacy source to decisions people act on.
01
Discover
Map systems, dependencies and the business logic hidden inside legacy code.
02
Architect
Design the target platform on proven patterns for zones, orchestration and scale.
03
Govern
Attach metadata, glossary, ownership and quality rules to every asset.
04
Modernise
Generate and deploy pipelines and models with agents under human validation.
05
Activate
Analytics, AI and agents on a governed foundation, measured and extended.
From legacy → to governed data → to intelligent impact at scale.
Make your data foundation the advantage.
We modernise legacy data platforms with agentic AI, reference frameworks and governance built in, so analytics, AI and operational intelligence run on foundations your teams can trust and extend.
Data modernisation is not a migration project.
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