The hourly fee business is changing rapidly

With A.I. scouring the internet for content to capture more information to embed in their models, the world of knowledge workers is rapidly changing. Talking to Lawyers and Notaries, the discussion quickly reaches the topics of Know-How and how to keep it relevant. But it is also relevant with engineers making designs or having to protect their IP.

Success and growth for a knowledge-driven organisation are no longer measured by the number of employees, but by the quality and internal capital they represent.

Jumping to the conclusion,
YES, know-how is relevant especially from very experienced people. A.I. helps them with productivity while they have the capability in their subject area to judge, correct and enhance the results from ever enhanced A.I. models.

And,
NO, this will not be replaced, as this know-how is often not formalised or even captured. It is the nuances of having lived and worked through all those situations. All having their contexts which is no where captured.

But,
HOW can you leverage and make it commercially relevant in order to thrive as an organisation built around knowledge-workers. When your clients plug everything in A.I. models and catch the simpler work themselves, you are left with complex stuff but where they do not value the effort it might take and there is no volume work to compensate for it. Your work is based on your hours, while you are now forced to find a way to scale that know-how that resides in the heads of experienced seniors.

Which brings us to the opportunity

Imagine how much more effective this senior employee could work if the necessary information were already gathered and processed, leaving them to focus on the final checks and key decisions.

This is now a reality.

You can unlock the know-how within your organisation in the way your organisation needs it — tailored to your specific needs.

How this would work? Turn know-how into a business process. Instead of giving people another tool to search with, using an Agentic Business Process brings knowledge directly into the work itself so it is put ready for review and adaptions by the people with the know-how. It combines different information sources, even with varying access levels, using specific AI agents to find, analyse, interpret and present the information exactly as you need it.

You can start small

And you don’t need to start with a massive AI transformation. In fact, the best place to start is usually a frustrating process where people spend too much time searching, asking, checking, or repeating work.

We take a simple three-step approach.

Step 1 — Define the Need and Outcome

Together, we identify the problem, the knowledge involved, and the outcome you want to achieve. We then turn that into a practical solution idea or mock-up, so you can see what the process could look like before building it. Based on this we turn it into skills for agents to prepare the work for the experts in your organisation.

Step 2 — Build and Fine-Tune

We select the right skills for the agents and data sources, build the process, and fine-tune it with your people. The technology adapts to your way of working — not the other way around.

Step 3 — Embed in Your Daily Business

The process becomes part of your workflow, delivering the right information and insights to the right people at the right time. This is not about buying another generic AI tool and hoping employees will find a use for it. This is about enhancing and leveraging the know-how of your experts.

Scale that know-how

It is time to change the way you operate the hourly fee business, before you become outdated. Create a key advantage by unlocking your know-how, at the right time for the right person. Kentivo combines AI agents, data, business rules, algorithms, and human expertise to create tailored solutions. Start with one process, prove the value, and build from there.

Not sure where to start, or already have a sense of where the biggest opportunity lies? Let’s discuss the possibilities within your organisation.

Contact us

DPG use case

Technology in service of clarity