HOW WE DELIVER
Engineered in four phases. Proven before it goes live.
Every engagement follows the same discipline: measure the process, build against your real systems, prove accuracy in parallel with your team, then run it with clear ownership.
- PHASE 01
Process mapping
We sit with the people who do the work and trace every step, system and decision. We record volumes, cycle times and error rates so the result can be measured against a real baseline.
YOU RECEIVE
- Process map with every system touchpoint
- Measured baseline: volume, time, errors
- Prioritised scope with a business case
- PHASE 02
Build on your stack
We connect directly to the tools you already run: your ERP, CRM, inbox, helpdesk or database. Rules, validations and approval thresholds are agreed with your team before anything is written.
YOU RECEIVE
- Working pipeline connected to your systems
- Validation rules and approval thresholds
- Exception queue designed with your team
- PHASE 03
Parallel run
The workflow runs alongside your team on live volume without writing into your systems. Every output is compared with what your people produced, until accuracy is confirmed.
YOU RECEIVE
- Side by side accuracy report
- Edge cases found and resolved
- Go live decision based on evidence
- PHASE 04
Production and ownership
Once live, every action is logged and every exception has an owner. We monitor performance, adapt to changes in your documents or systems and report against the original baseline.
YOU RECEIVE
- Audit trail for every record
- Monitoring and change process
- Results reported against the baseline
Built for the questions your CFO and IT will ask.
People approve
Payments, financial decisions and sensitive changes always go through a named person.
Every action logged
What came in, what was extracted, who approved and what was written back.
Your systems stay yours
We integrate with your stack. No forced migration, no new platform to learn.
Data handled deliberately
Access, retention and processing are agreed per workflow before work starts.
The questions worth asking.
Do we need to replace our existing systems?+
Not necessarily. We start by checking your existing tools, data access and integration options. If a limitation changes the scope, we make that clear before implementation.
How do you manage data and AI risk?+
Data access, processing arrangements, retention, human approvals and escalation need to be agreed for the specific workflow. The diagnostic is not a compliance assessment or a guarantee that a system can run without errors.
How long does implementation take and what does it cost?+
That depends on the scope, system access and controls required. The first conversation is about confirming feasibility. A timeline and commercial proposal follow a defined scope, not a generic promise.
What do we get from the diagnostic?+
A suggested first intervention, a workflow outline, the decisions that should remain human and the measures to track. Any time or cost figure uses only the values you provide. It is not a forecast of guaranteed savings.