AGMM & PartnersAI training for teamsCustom AI systems
AI for business
We teach teams how to use AI with purpose, and we build custom systems for work that has become outdated, repetitive or disconnected. The starting point is the job that needs doing, not a fashionable tool.
Choose a useful route
Most conversations begin in one of two places. People either need the confidence and ability to use the tools already available, or the workflow itself needs a better system.
For organisations that want staff to understand where AI helps, use it responsibly and apply it to recognisable tasks without getting lost in technical noise.
For organisations where people are retyping information, working around old software, chasing handoffs or relying on a patchwork of spreadsheets and disconnected tools.
Practical AI training
The aim is not to turn everyone into an AI specialist. It is to help people understand the tools, make sound decisions and use them in ways that improve their own work.
A training engagement can include
A short discovery session to understand the team, its work and the most useful starting points
A practical agenda shaped around the agreed goals and the level of the people in the room
Live demonstrations that connect AI tools to recognisable business tasks
Guided exercises so the team can practise, ask questions and test what is genuinely useful
A clear set of next actions and learning resources for the team to continue with
Custom AI systems
A custom build can replace an outdated system, connect tools that do not talk to each other or remove a repeated manual step. The right answer might use AI, automation, conventional software or a careful combination.
Common starting points
These are examples, not a fixed menu. We examine the workflow before proposing what should be built.
A custom system engagement can include
A map of the current workflow, including handoffs, repeated work and points where information gets stuck
A written scope explaining what should stay, what should connect and what may need replacing
A working version that lets the people who do the job test the idea before a larger build
The agreed system, integrations and interfaces required for day to day use
Handover information and an agreed plan for introduction, support and future improvements
Built around the workflow
AGMM is not limited to one trade or type of company. We work from the process backwards, which makes the same approach useful wherever people are held back by old software, repeated admin or disconnected information.
These are workflow examples, not claims that every business needs the same system. The first job is to understand what is actually happening.
Reduce the administration between a new role, the right candidate and a confirmed interview.
Give teams a clearer route through bookings, supplier information, enquiries and shift handovers.
Connect product, order and support information so routine exceptions need less copying and chasing.
Make the work around appointments more dependable without making the client experience feel automated.
Turn document-heavy work, reporting and internal knowledge into a process the whole team can follow.
Improve quoting, job information and customer follow-up while keeping the practical workflow intact.
How we work
This keeps the decision connected to people, operations and a clear business need. It also creates a point where an idea can be changed or stopped before a wider implementation.
We begin with the people doing the work. We look at the steps, systems, decisions, data and constraints before deciding that AI is the answer.
We separate useful parts of the current process from repeated work and broken handoffs, then agree a focused first scope.
The people who will use the system can test a working version against realistic tasks. Their feedback shows what is ready and what still needs work.
Once the direction is proven, we complete the agreed build, introduce it carefully, document it and decide how support and improvements will work.
Data, access and trust
You can discuss the problem without handing over live systems or customer data. If later work needs access, the purpose and practical controls should be agreed before it is provided.
Early discovery can often use a walkthrough, redacted examples or representative test information.
We document why access is required, who needs it and which part of the work it supports.
Hosting, permissions, retention, deletion and handover arrangements depend on the systems and your requirements.
See the work
The portfolio brings the challenge, the build and the outcome together so you can see the kind of work behind the service description.
Explore the portfolioFrequently asked questions
Start here if you are deciding between training, a custom build or simply learning more before doing either.
Ask something elseWe help in two practical ways. We train teams to use AI well in their existing work, and we design custom systems for workflows that are outdated, repetitive or disconnected. If neither route is right yet, our events and free learning materials are a useful place to begin.
No particular level is required to start a conversation. We establish what the team already knows and shape the scope accordingly. A useful session should make sense to the people attending, not assume they are developers.
Yes. Generic examples can introduce an idea, but the useful work is connecting it to the tasks your team actually carries out. We agree in advance which workflows can be discussed and what information is appropriate to use in the room.
Yes. The Learn hub contains free guides, courses, tools and quizzes, and our events give people a hands on introduction. Both routes help you decide what your team needs before discussing a private session.
The right system depends on the workflow. Common starting points include handling enquiries, preparing information, quoting, reporting, scheduling, searching internal knowledge and moving information between tools. We only recommend a build after understanding the job it needs to do.
No. Replacement is only one option. Sometimes the sensible answer is to connect existing tools, remove one manual step or improve the interface around a dependable system. The workflow review is designed to make that choice clear.
That is often the safest way to test a new direction. A focused working version lets real users check whether the idea fits the task before everyone commits to a wider implementation.
Not necessarily. The level of internal technical involvement depends on your current systems, access requirements and the final scope. We identify who needs to be involved before work begins so there are no hidden responsibilities.
No live data is needed for the first conversation. Later work may require examples or controlled access, but only when it has a clear purpose. Redacted, representative or test information may be suitable for early exploration, depending on the project.
We agree what information is needed, why it is needed and how it will be handled before access is provided. Hosting, permissions, retention and deletion requirements are documented for the particular project. The final controls depend on your requirements and the technology selected.
It depends on the workflow, the systems involved and the depth of the change. We first establish the problem and the proposed scope, then provide a written commercial proposal. We do not publish a generic figure that would be misleading for a different project.
If you want to explore, attend an event or start in the Learn hub. If you already have a team to train or a workflow that needs attention, contact us with a short description of the situation. We can then recommend the most useful next conversation.
Choose your next step
See practical AI in the room and ask questions face to face.
View events 02Use the free guides, courses, tools and quizzes whenever you are ready.
Open the Learn hub 03Describe the team or workflow and we will help identify a sensible next conversation.
Contact AGMM