Solution area
AI Automation
Redesign how work gets done, then automate what should be automated. In that order, because the reverse rarely holds.
Automating a broken process makes it fail faster
This is the most common and most expensive mistake in this domain.
Most disappointing automation projects were technically successful. The workflow ran, the integration held, the tool did what it promised. The disappointment came from automating a process that should have been simplified, merged with another, or removed altogether.
The same applies to AI, with the volume turned up. A capable model applied to an unclear process produces confident output that nobody trusts enough to act on, which is worse than no output at all.
The question is not what could be automated. It is what the work should look like, and what role automation and AI should play in it.
Business problems this addresses
The symptoms that usually bring organisations to this domain.
- Work depends on manual effort, rekeying and workarounds between systems.
- Knowledge sits with particular people rather than being available to the business.
- Throughput is limited by coordination and handoffs rather than capability.
- Quality and turnaround vary depending on who happens to do the work.
- Decisions wait on information that exists but is hard to assemble.
- Volume cannot grow without adding people in proportion.
Where automation and AI create value
Patterns that recur across organisations, independent of sector.
Process and workflow
Removing handoffs, approvals and coordination overhead from work that crosses teams and systems.
Knowledge-intensive work
Making organisational knowledge findable and usable where the work happens, rather than locked in documents and individuals.
Decision support
Assembling the information a decision needs, so judgement is applied to a complete picture rather than a partial one.
Document and information handling
Capture, extraction and routing of information that currently arrives as unstructured documents and email.
Operational consistency
Making the quality and turnaround of routine work independent of who performs it.
Integration
Connecting systems so information moves without a person acting as the interface between them.
How we approach it
The consulting model applies here without modification.
We start by understanding how work actually happens, which is usually not how it is documented. We then determine what the work should look like, and only then decide which parts warrant automation, which warrant AI, which warrant better use of systems already in place, and which simply warrant removal.
That sequence matters because it is the only one that reliably produces change worth keeping. It also means some engagements conclude that the right answer involves very little new technology.
We are not an AI agency. AI is one option among several, chosen when it is the right one.
Packaged offers
Packaged work within this area.
Bid & Pursuit Transformation
Bidding is a process problem before it is a writing problem.
Work across four dimensions together: the pursuit process, the knowledge behind it, the technology that supports it and the adoption that makes it stick. AI accelerates analysis, retrieval, workflow and first drafts while people keep the judgement and the accountability.
Two stages of engagement: a Bid & Pursuit Diagnostic and a Bid & Pursuit Transformation.
Advisory work in this area is not limited to what is packaged. If your problem does not match an offer, the conversation is the same either way.
Where does work slow down in your organisation?
You do not need an AI strategy to start. A clear description of where work is slow, inconsistent or dependent on particular people is a better starting point.
Discuss your challenge