Service 06 — Digital Transformation & AI

Complete digital transformation, with AI where it earns its place.

Modernise operations end-to-end — processes, platforms, data and people — and put generative and predictive AI to work on the workflows that move your numbers, with the security and governance to run it in production.

  • Transformation roadmap
  • Generative AI & agents
  • Automation
  • Data platform
  • Weeksto a working pilot
  • Model-agnosticClaude · GPT · Gemini · open
  • Privatedata stays in your tenancy

Why it matters

Transformation isn't a tool purchase. It's a redesign of how work gets done.

Bolting a chatbot onto a broken process just makes the broken process faster. We start with the business outcome, redesign the workflow, modernise the systems and data underneath it, then apply AI — copilots, agents, prediction, automation — where it measurably helps. Everything ships with evaluation, guardrails and monitoring, so it survives past the demo.

Six pillars

What a transformation actually covers.

Every programme is assessed and planned across all six — because a gap in any one of them is where initiatives stall.

  1. 01

    Strategy & operating model

    Value-stream mapping, target operating model, initiative portfolio and business cases

  2. 02

    Process & automation

    Workflow redesign, RPA and API-driven automation, document processing, system integration

  3. 03

    Generative & agentic AI

    Copilots, retrieval-augmented assistants and agent workflows with evaluation suites and guardrails

  4. 04

    Predictive AI & analytics

    Forecasting, anomaly detection, recommendation and risk scoring with MLOps for retraining

  5. 05

    Data platform

    Warehouse / lakehouse, streaming, data quality, governance and the semantic layer AI can trust

  6. 06

    People & change

    Enablement, adoption metrics, communications and the rhythm that makes change stick

AI use-case portfolio

Where AI pays for itself.

01

Customer operations

Support copilots, ticket triage and summarisation, knowledge assistants over policies and manuals.

02

Finance & back office

Invoice and document extraction, reconciliation, anomaly detection, close-process automation.

03

Sales & marketing

Lead scoring, proposal drafting, personalised content with brand guardrails.

04

Operations & supply chain

Demand forecasting, predictive maintenance, routing and inventory optimisation.

05

Engineering & IT

Code assistants, incident summarisation, runbook agents, log and alert triage.

06

Risk & compliance

Policy checking, KYC/AML document review, audit evidence assembly.

What we deliver

Transformation capabilities.

01

Transformation strategy & roadmap

Operating-model assessment, value-stream mapping, prioritised initiative roadmap and the business case for each phase.

02

Process automation

Workflow redesign, RPA and API-driven automation, document processing and integration across ERP, CRM and legacy systems.

03

Generative AI & agents

Copilots, retrieval-augmented assistants over your own knowledge, and agentic workflows using Claude, GPT or open models — with evaluation suites and guardrails.

04

Predictive AI & analytics

Forecasting, anomaly detection, recommendation and risk scoring built on clean data with MLOps for retraining and monitoring.

05

Data platform modernisation

Warehouses and lakehouses, streaming, data quality, governance and the semantic layer that makes AI trustworthy.

06

Legacy modernisation & change

Incremental replacement of legacy systems, cloud adoption, and the training and adoption metrics that make change stick.

Prioritisation

How we score candidate use cases.

Every idea is scored on the same four axes before it gets budget. Illustrative example below.

Business valueData readinessFeasibilityRisk (lower = better)
Support copilot over knowledge base
Invoice extraction & matching
Demand forecasting
Autonomous procurement agent
Marketing content generation

How it runs

Assess, design, pilot, scale, embed.

  1. 01

    Assess

    Where value leaks today — processes, systems, data and skills — with a quantified opportunity map.

    3–4 wks
  2. 02

    Design

    Target operating model, architecture and a use-case portfolio ranked by value, feasibility and risk.

    3–4 wks
  3. 03

    Pilot

    Two to three high-value use cases delivered in weeks with real users, real data and measured results.

    6–10 wks
  4. 04

    Scale

    Platform, data foundations, governance and security so pilots become production capabilities.

    quarters
  5. 05

    Embed

    Enablement, adoption tracking and a continuous improvement rhythm.

    ongoing

Operations

Start where the numbers are.

We instrument the process before automating it, so the baseline is real and the improvement is provable to a CFO.

  • Process mining on real logs
  • Baseline cycle time and cost
  • Value tracked per initiative

Automation

Humans in the loop, by design.

Agents and automations get confidence thresholds, review queues and audit trails — so speed never comes at the cost of control.

  • Confidence-based routing
  • Reviewer queues and audit logs
  • Kill switches and rollback

Adoption

What we track.

  • Process cycle time−65%
  • Manual touches per case−80%
  • Active weekly users of new tools85%
  • AI answers accepted without edit78%
BeforeAfter

Illustrative programme dashboard — every initiative reports on the same four numbers.

Governance

Guardrails that ship with every AI feature.

  • Evaluation suite with golden test sets
  • Prompt and model version control
  • PII detection and redaction
  • Access control and audit logging
  • Human review thresholds
  • Cost and latency budgets
  • Model fallback and rollback
  • Usage and quality monitoring

Industries

Where we've applied it.

FAQ

Transformation & AI questions.

  1. 01

    Where should we start with AI?

    With a use-case portfolio. We map candidate workflows, score them on value, data readiness and risk, and pilot the top two or three before investing in platform.

  2. 02

    How do you keep our data private?

    Models run inside your cloud tenancy or via enterprise APIs with no training on your data, with access controls, audit logging and retention policies designed in.

  3. 03

    Can you help with adoption, not just technology?

    Yes. Change management, training and adoption metrics are part of every transformation roadmap we deliver.

  4. 04

    Which models do you use?

    Whichever fits the task, cost and data constraints — Claude, GPT, Gemini or open-weight models — behind an abstraction so you can switch.

  5. 05

    How do you measure ROI?

    A baseline before the pilot, a value tracker per initiative and a programme dashboard reviewed with your sponsors.

Let's build

Ready to map your opportunities?

A four-week assessment gives you a quantified opportunity map and a ranked use-case portfolio — with or without us for the next step.