Capabilities
What we are prepared to be held accountable for.
Six practices, each defined by the outcome it produces rather than the technology it uses. Where a problem sits outside them, we will say so and point you elsewhere.
01
AI Automation Consulting
We map where judgement-heavy, repetitive work sits inside your operation, then automate the parts that are safe to automate and instrument the rest.
Read the full practice →- Operational audit across support, finance, sales operations and back office
- Automation candidate scoring by volume, error cost and reversibility
- Human-in-the-loop design so nothing critical runs unsupervised
02
Custom AI / ML Development
Production systems, not prototypes — retrieval pipelines, agents, fine-tuned and evaluated models, shipped into your existing stack.
Read the full practice →- Retrieval-augmented systems over your own documents and data
- Model selection, evaluation harnesses and regression suites
- Deployment, monitoring, cost control and hand-over documentation
03
Digital Transformation Advisory
For leadership teams that need a defensible sequence rather than a list of tools. We produce the roadmap and stay accountable to it.
Read the full practice →- Current-state assessment and capability gap analysis
- Prioritised 12-month roadmap with owners, budgets and decision gates
- Ongoing advisory at board and executive level
04
Systems Implementation & Integration
Connecting the platforms you already pay for so data moves cleanly and AI has something reliable to work with.
Read the full practice →- CRM, ERP and data platform integration
- Event pipelines, sync logic and failure handling
- Post-launch maintenance under an agreed service window
05
Data Analytics & Decision Systems
Turning scattered operational data into decision surfaces leadership actually opens on a Monday morning.
Read the full practice →- Warehouse modelling and metric definitions agreed in writing
- Executive and operational dashboards
- Forecasting and anomaly detection where the data supports it
06
AI-Powered Growth Engineering
Applied AI across acquisition and retention for consumer and e-commerce brands — personalisation, lifecycle and creative operations.
Read the full practice →- Segmentation and personalisation infrastructure
- Lifecycle messaging systems with measurable lift
- Creative and content operations at scale, with review gates
/ Engagement models
How the work is structured.
Every engagement is scoped in writing before it begins, with a named lead and agreed decision gates.
AI Opportunity Assessment
2–3 weeksA structured review of where AI creates defensible value in your operation — and, just as usefully, where it does not.
- Prioritised opportunity register
- Feasibility and risk assessment
- Executive readout
Transformation Roadmap
4–6 weeksThe sequenced plan: what gets built, in what order, by whom, against what budget and which decision gates.
- 12-month roadmap
- Architecture and data strategy
- Build-versus-buy recommendations
Build Engagement
2–4 monthsA dedicated team designing, building, evaluating and deploying a production AI system inside your environment.
- Production system and source
- Evaluation and monitoring suite
- Hand-over and enablement
Advisory Retainer
OngoingContinuous senior input for teams executing their own roadmap, with a fixed monthly allocation and agreed response times.
- Standing weekly session
- Architecture and vendor review
- On-call escalation window
Fractional CTO / CDO
6–12 monthsEmbedded technical leadership for companies that need the function before they can justify the full-time hire.
- Technology strategy ownership
- Team structure and hiring input
- Board and investor reporting support
Which of these is your problem?
If you are not sure, that is usually the assessment. Tell us what is not working and we will tell you where it belongs.
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