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Solutions

AI & Data Analytics

Data platforms, decision reporting and applied AI for government and enterprise organisations.

Starts with
A data readiness assessment
Reporting
Power BI, or your incumbent
Access control
Enforced at the retrieval layer

The approach

Agree the metric before building the model.

We begin with the decisions the organisation needs to support, identify the data those decisions require, and build the pipeline necessary to serve them. Scoping analytics to specific decisions shortens time to first useful output and keeps the platform maintainable.

PythonSQL ServerAzure SynapseDatabricksdbtPower BIApache AirflowPandasscikit-learnAzure OpenAIVector searchRAG
analytics — executive reporting
Model Sources Quality Metrics Dashboards Assistant Admin Users & rolesAudit log
1Agreed metric set
100%Queries logged
0Ungoverned access

Capabilities

What the practice covers

  1. 01

    Data platform

    Warehouse and lakehouse design, ingestion pipelines and dimensional modelling that accommodates new source systems without redesign.

  2. 02

    Executive reporting

    A defined set of metrics with agreed calculation rules and named owners, so reported figures are consistent across departments.

  3. 03

    Forecasting and machine learning

    Demand, churn and maintenance models evaluated against a documented baseline, with performance reviewed on a fixed schedule.

  4. 04

    LLM integration

    Retrieval-grounded assistants over internal documents and records, with citations, access control enforced at retrieval, and full answer logging.

  5. 05

    Data quality

    Validation, reconciliation and lineage tracking to keep reported figures consistent with source systems.

  6. 06

    Governance

    Access models, retention schedules and personal data handling documented to a standard suitable for PDPL and equivalent audit.

On handover

What you receive

Every engagement ends with the client holding the artefacts needed to run, extend and re-tender the system without us.

Discuss a project
  • Metric dictionary agreed with the business owners of each figure
  • Reproducible pipelines with automated data quality tests
  • Dashboards with named owners and a defined review cadence
  • For AI features: an evaluation set, measured accuracy and documented failure modes

Common questions

Frequently asked

Is our data ready for AI?
We assess readiness before recommending an approach. Where data quality or coverage is insufficient, remediation is scoped as its own phase with a defined outcome, ahead of any model development.
Can an assistant use internal documents securely?
Yes. Access control is enforced at the retrieval layer, so a user receives answers only from documents they are already permitted to open. All queries and responses are logged.
Do you standardise on Power BI?
We recommend Power BI where Microsoft licensing is already in place, which covers most organisations we work with. Alternative platforms are proposed where the existing estate justifies them.

Related

Practices that usually travel with this

All solutions

Web Application Development

Enterprise portals, workflow platforms and line-of-business systems, supported by dedicated offshore engineering teams.

Web Applications

E-Government Solutions New

Public-sector engineering on national infrastructure: Nafath and Elm platforms in Saudi Arabia, work on an economic zone client management system in the UAE, and on passenger wayfinding at Hamad International Airport.

E-Government

Cloud & Infrastructure Services

Landing zone design, workload migration and managed operations on Azure and AWS, with data residency and cost governance established from the outset.

Cloud

Begin with a two-week discovery

Discovery produces a domain model, a risk register and a written estimate, retained by the client regardless of whether the build proceeds.

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