AI Implementation
Workflow Development
The firm’s leading practice. One discipline, not a menu: finding the work a business does by hand out of habit, redesigning it, building the thing that runs it, and leaving it with the team that owns it.
Overview
The question is never whether a business could use AI. It is which specific hour of the week it should take back first, and what has to be true for the result to be trusted.
Most organizations meet AI as a tool: a subscription, a pilot, a capable assistant that a few people use well and everyone else forgets. Very little changes, because the work itself was never redesigned. The reporting cycle still runs the way it ran, with a faster way to draft the commentary bolted onto the side of it.
Workflow development starts from the other end. It treats a process as the unit of work: the whole path from where data originates to where a decision gets made, including the review steps, the exceptions, and the person who has to sign their name to the output. The firm maps that path, redesigns it around what the technology genuinely does well, builds the system that runs it, and stays through the handover.
The work sits close to finance and operations, because that is where the manual effort concentrates and where the standard of accuracy is unambiguous. A number is right or it is not. That constraint is a feature: it forces automation to be verifiable rather than merely impressive.
There is no tiering to this practice and no partner ecosystem behind it. Engagements are scoped in writing, run by the principal, and priced against a defined deliverable.
Engagement Process
Assess. Design. Build. Embed.
Four steps, run in order. Nothing gets built before the process it serves is settled, and nothing is called finished until someone other than the firm can run it.
01
Assess
Find the work that is actually expensive.
- Sit with the team through a real cycle, whether a close, a reporting week, or a diligence request, and record where the hours go.
- Separate work that is genuinely judgment-bound from work that is only manual by habit.
- Name the constraints up front: systems, data quality, review requirements, who has to sign off.
02
Design
Design the process, then the automation.
- Redraw the workflow as it should run, including the human review points that stay human.
- Decide what the system must never do on its own, and what happens when it is uncertain.
- Agree the definition of done before anything is built.
03
Build
Build the smallest thing that carries real work.
- Working software against live data, not a demonstration on a curated sample.
- Outputs traceable to source, so a reviewer can check the result rather than trust it.
- Run it in parallel with the existing process until it earns the handoff.
04
Embed
Leave it in hands that can run it.
- Documentation written for the person who inherits it, not for the person who built it.
- Training on the exception cases, which is where the value and the risk both sit.
- A defined end to the engagement. The workflow belongs to the team.
Representative Workflows
The kind of work this is
Illustrative examples of the categories engagements fall into. Not client engagements or case studies.
01
Reporting automation
Assembly of a recurring management, board, or lender package (consolidation, variance commentary drafting, and formatting) reduced to a review step rather than a build step.
02
Document processing
Extraction of structured data from invoices, statements, contracts, and credit agreements, with confidence flags routing the uncertain items to a person.
03
Reconciliation and exception handling
Routine matching handled automatically so the finance team spends its attention on the exceptions rather than on producing them.
04
Forecasting support
Automated data pulls and scenario refreshes behind a planning or thirteen-week cash model, so the forecast stays current without a weekly manual rebuild.
05
Research synthesis
Structured summarization of filings, market material, and internal documents into a consistent format, with every claim linked back to its source.
06
Internal knowledge retrieval
A searchable layer over the policies, contracts, and prior work a team already has, so answers come from the record instead of from memory.
How the Practice Is Run
Four commitments
Tool-agnostic
The firm resells nothing and receives no vendor compensation. The right model or platform is whichever one fits the constraint, and it is expected to change.
Human review stays
Automation handles assembly. Judgment, approval, and anything going to a board, a lender, or a counterparty stays with a named person.
Traceable by design
Every output is built to be checked: inputs sourced, logic documented, and the limits of the workflow stated plainly.
Built to be handed over
The engagement is designed to end. A workflow that only the firm can operate is a failed deliverable.
Outputs produced with AI assistance are reviewed before they are relied upon, and the firm does not represent automated output as a substitute for professional judgment. See our disclosures.
If there is a week in your calendar that costs more attention than it should, that is the conversation.
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