Transformation That Shows Up on the P&L
Most transformation programmes drift between the consulting deck and the delivery team. Ours don’t – our diagnostic teams hand directly to our build teams under a single SMI MSA. AI-native delivery. Outcome-tied where you want it.
Why Most Transformations Fail
They start with a technology platform and look for a problem to apply it to. Ours start with a business metric and design backwards. Technology, AI, data, and process are means – not the message.
Every consultancy claims a five-phase framework. The thing buyers should pressure-test is what happens between the deck and the delivery.
- One firm, one MSA, one accountability chain. Our diagnostic teams hand off directly to our delivery teams – no second procurement, no second contract, no “we recommend you hire a build partner.” The people who write the roadmap are accountable for delivering it.
- AI-native build inside the programme. Most transformation consultancies recommend AI; we deliver it. The build phase uses the same Claude / Copilot / Cursor / autonomous-agent stack as our standalone bespoke and modernisation engagements.
- Outcome-tied commercials available. Up to 30% of fee tied to the financial KPI agreed at diagnostic. We carry execution risk where the metric is clean and measurable.
- Eval-driven governance. AI used inside the programme runs under eval gates, model cards, and audit-ready logging from day one – not added in year two when risk and legal escalate.
Human review is the final layer not the only one. The result: AI-suggested code carries the same provenance, attestation, and quality bar as code written by hand.
What the 30-Day Diagnostic Includes
- Value-stream mapping for the three highest-impact processes.
- AI maturity assessment across people, process, data, and tooling.
- Top 3 transformation lever recommendations with financial models.
- Governance, risk, and compliance baseline.
- Executive readout: written board-ready brief, plus a 90-minute working session.
What We Modernize
Mainframe & Midrange
COBOL, RPG, PL/I to cloud-native Java, Python, or .NET.
Refactor into modular monoliths or microservices on AWS, Azure, or GCP.
Aging Frameworks
Struts, JSF, Silverlight, WebForms migrated to React, Angular, or modern Spring Boot
Where AI Fits In
Every transformation we run has AI in three places – not because it is fashionable, but because it is the lowest-cost way to compress cycle time at each layer:
- In delivery: Claude, Copilot, Cursor, and autonomous coding agents (Claude Code-class) accelerate every build, refactor, and integration. Tool access via MCP for standardised, audited integrations.
- In the process: AI Agents, RAG systems, and Copilots reduce human time-per-task on operational workflows.
- In the management layer: Live digital cockpits give executives the same data engineers see.
Every transformation programme ships with a governance layer covering:
AI risk
Use-case classification, model approval, ongoing eval, kill-switch policy.
Data residency & compliance
GDPR, HIPAA, RBI / SEBI / DPDP where applicable.
Change management
Communication plan, training plan, adoption metrics - not afterthoughts.
Financial control
Quarterly programme P&L. Investment to outcome traceable.
Manufacturing
Plant-level transformations, OEE-led programmes, digital-twin pilots.
BFSI
Customer-acquisition, underwriting, and servicing transformations.
Healthcare
Patient-journey transformations, claims and prior-auth modernisation.
Retail
Omnichannel, customer-360, store-ops transformations.
Supply Chain
End-to-end visibility programmes, demand-sensing rollouts.
Baselines benchmarked against incumbent vendor quotes for equivalent scope, with independent advisory validation on engagements over $5M. Total programme TCO includes build, dual-running, training, change management, and 24 month run rate operations full methodology available on request.
FAQ
Frequently Asked Questions
How is your transformation work different from a Big-Four consultancy?
We do not stop at the slide deck. Our diagnostic teams hand off directly to delivery teams, all from SMI – same MSA, same accountability chain. The same people who recommend the programme are on the hook to deliver it, which keeps recommendations honest and removes the second procurement cycle most transformation programmes get stuck in.
Will you work alongside an incumbent consulting partner?
Yes. We often deliver inside programmes led by a Big-Four advisor. Our role is the engineering and AI-native execution layer.
What is the smallest transformation engagement you take?
The 30-day diagnostic is fixed-fee and right-sized to the scope. Programmes scale from there based on the business case, not a brochure tier.
How do you stop AI used inside the programme from creating new governance liabilities?
Every AI use-case classified up-front (prohibited / high-risk / limited-risk / minimal-risk per EU AI Act) with model cards, eval gates, and audit-ready logging in place from day one. AI Agent action audit by default. Model-risk governance is part of the programme governance layer, not a year-two add-on.
How do you handle AI inference cost as the programme scales?
FinOps for AI is part of the platform layer: token cost monitored per workflow, model routing tuned to cost-per-outcome, prompt caching and prefix reuse as standard. Per-tenant cost dashboards exposed to your CFO from month one.
Ready to Transform Around the Business, Not the Tech?
Book a 30-day diagnostic. We will baseline the three highest-impact levers, model the financial case, and put a governance-ready programme plan on the table.