Home/Capabilities/Digital innovation
Capability
Digital innovation, held to regulatory standards.
Our name says digital innovation for regulatory compliance, in that order and for a reason. The innovation only counts if the output survives an inspection.
Our position
Most regulatory automation fails for the same reason
It automates a process that was never agreed, using data nobody trusts, in a system that cannot evidence what it did. The technology works. The output is unusable.
Regulated work has a constraint that ordinary business automation does not: you must be able to demonstrate afterwards how a result was produced, from what inputs, under whose control. A tool that improves speed but cannot answer that question has not saved time — it has moved the cost to the audit.
So we start from the regulatory obligation and work backwards to the technology, rather than the other way round. Sometimes the honest answer is that a process should be fixed before it is automated, or that the right intervention is not software at all.
Where it works
Four places automation reliably earns its keep
These share a shape: high volume, high repetition, clear right answers, and a heavy human cost to doing them by hand.
Document comparison
Comparing labelling documents against approved source across languages and formats. Machines find differences reliably; people decide which differences matter. Our clearest example is labelling.
Extraction and structuring
Pulling defined data out of documents that were never designed to be queried — legacy dossiers, approval letters, commitment lists — and turning it into something a system can report on.
Gap and impact analysis
Assessing a change against a portfolio to identify what it touches. Manual analysis across many markets and presentations is slow and, past a certain size, unreliable.
Requirement monitoring
Tracking guidance and requirement changes across target markets and surfacing the subset that affects your products, rather than a digest nobody reads.
How we work
Evidence before scale
Frame the regulatory problem
Define what decision or obligation is being served, and what a correct output looks like. If that cannot be stated precisely, the process is not ready to be automated.
Fix the process first
Automating an unagreed process encodes the disagreement. Where the process is unclear, we redesign it before adding technology to it.
Prove it on real material
A bounded proof of concept on your actual documents, measured against a known-good answer, with the failure modes documented rather than hidden.
Build the control framework
Validation approach, data integrity expectations, access and audit trail, records retention, and the human review point. Designed with the solution, not retrofitted to it.
Deploy into the operating model
Roles, ownership, training and escalation, so the capability survives the departure of the people who built it.
Monitor and re-qualify
Performance monitoring after go-live, with defined triggers for re-qualification when inputs, models or requirements change.
Responsible use
The questions we expect to be asked
Any serious client will ask these, and any serious partner should have answers before the first workshop.
How is it validated?
What the intended use is, how fitness for that use was demonstrated, and what evidence exists — proportionate to the risk the tool carries.
Can you show what it did?
Attributable, legible, contemporaneous, original and accurate records of inputs, outputs and the people who reviewed them.
Where does the human decide?
Automation should narrow what a person examines, not replace the judgment. We define the review point explicitly and design the workflow around it.
What happens to your data?
Where content is processed and stored, who can access it, what is retained, and whether anything is used for model training. Defaults set conservatively.
How do you know it still works?
Monitoring, drift detection where models are involved, and defined triggers for re-assessment when the inputs or requirements change.
What if it is wrong?
Known failure modes documented, detection designed in, and a defined route for handling an error that reaches a regulatory deliverable.
Related
Connected routes
Bring us the challenge
Bring us the process you are told cannot be automated.
Often that is correct, and the reason is worth understanding. Sometimes it is only true of the process as it currently stands.