Banks and financial firms have to ship continuously while proving, release by release, who approved what and why. We bring AI, consulting pods and a delivery platform built so that evidence is a by-product of the work, not a project of its own.
The question we hear most
Most banks still treat audit evidence as a project that starts when the review is announced: weeks of reconstructing who approved what, from tickets, emails and spreadsheets. The work was controlled. The record of it was not.
We think the record should be a by-product of the work. When approvals, tests and releases are captured as they happen, the same trail that satisfies an auditor also shows delivery leads where risk is building — and the bank can change faster precisely because it can prove what changed.
The shifts changing what good delivery looks like here, and what each one asks of the teams doing the work.
DORA in the EU, the RBI’s IT governance directions and the MAS technology risk guidelines put ICT risk, incident handling and third-party oversight under direct supervisory review.
What it means for deliveryResilience has to be designed, tested and evidenced, not asserted in a policy document.
Instant rails such as UPI, FedNow and SEPA Instant, and always-on digital channels, remove the overnight window in which change used to be absorbed.
What it means for deliveryRelease risk has to be known before deployment, because there is no quiet hour to recover in.
Generative AI is moving from pilots into operations, and supervisors expect it inside the same model-risk, privacy and outsourcing controls as any other model.
What it means for deliveryEach model needs an owner, an evaluation set and an audit trail before it reaches a customer.
Legacy cores carry decades of product logic, and boards no longer accept replacement programmes that depend on a single cut-over.
What it means for deliveryChange around the core in increments, each with reconciliation and a way back.
The pressures differ inside an industry too. These are the parts of it our teams work in, and what sets each one apart.
Digital channels, onboarding and lending journeys built on cores that cannot stop.
Real-time rails, frequent releases and scheme rules that change on a fixed calendar.
Policy administration and claims modernisation, with document-heavy work that suits assisted automation.
Trading, advisory and reporting platforms where latency, suitability and record-keeping all carry rules.
Fast-growing loan books, co-lending partnerships and regulators asking for bank-grade IT controls.
Bank-owned engineering centres that need delivery governance their headquarters will sign off.
Each offering runs on its own or as part of a wider programme, and draws on the AI services, consulting practices and products listed with it.
Segregation of duties, approvals and evidence built into how change ships, so an audit draws on the delivery record instead of a reconstruction.
An integration layer in front of the core, so channels can change every week while the core changes on its own, slower clock.
Assistants and document processing grounded in your own policies, with a reviewer in the loop and models that stay inside your boundary.
Service mapping, resilience testing and incident readiness for the services supervisors now treat as critical.
One delivery model, one set of quality gates and shared telemetry across every vendor in the programme.
Client storyTier-2 bank
Client name withheld under NDA. Figures are from the client’s own reporting.
We do not certify compliance — your auditors and assessors do. We make sure the evidence each framework asks for is produced by the delivery process itself.
Common first engagements in this sector. Most begin with a two-week, fixed-price discovery that leaves you with a costed plan whatever you decide next.
Yes. Our approach is zero training on your data, with private model routing for hosted models. Where the data cannot leave your control at all, we build the whole stack on your own hardware, air-gapped if required.
It is enforced in the workflow itself — who can raise, approve and release a change — rather than left to a policy document, and every step is recorded in an audit trail.
Routinely. We are often brought in to make a multi-vendor programme cohere, with shared interfaces, quality gates and telemetry so accountability stops falling between contracts.
The ones your auditors test against — typically DORA, the RBI and MAS technology risk rules, PCI DSS and SOX IT general controls. We do not certify compliance; we make sure the evidence each framework asks for is produced by the delivery process itself.
Yes. A capability centre needs delivery governance that headquarters and its regulators will both accept. We set that up, and can run pods alongside the centre’s own engineers.
The EU’s Digital Operational Resilience Act has applied since 17 January 2025. Most of what it asks lands on the teams that build, test and run software. Here is what that means in practice.
An assistant that answers from your own documents is only useful if people can check it. What it takes to build one that grounds every answer, respects permissions and says when it does not know.
Most of what the AI Act asks of high-risk systems is engineering work — logging, documentation, human oversight, data governance. Building it in now costs far less than retrofitting it.
Tell us the constraint and the systems behind it. We will put an engineer who has worked with both on the call, not the nearest salesperson.
What the first call covers
