Practical AI
Find a useful place to start with AI.
Curious about AI, but unsure where it would help? We look at everyday work with your team, compare a few useful ideas, and help you decide what to try, what to leave alone, and what needs a person in charge.
The decision stage
Map. Measure. Check. Decide.
We start with how work happens today and what would make a useful difference to the people doing it.
AI assistance / Human judgement
AI spots patterns.
You see the context.
AI can help organise information and draft a first pass. Your team brings the experience, checks the details, and makes the decisions.
Start with how work happens today.
Walk through an everyday task with the people who know it best. Notice what repeats, what takes time, and where someone needs to make a decision.
Choose what would make a difference.
Agree what a useful improvement would look like, whether that means less waiting, fewer repeated steps, or better answers.
Check the idea before committing.
Look at the tools, information, and permissions involved. Agree where a person stays in charge and what needs extra care.
Leave with a clear next step.
We may recommend trying a small improvement, using an existing tool, or leaving things as they are. We explain why and what comes next.
Scope and fit
Bring one everyday task you would like to improve.
A useful starting point is a repeated task, someone who can help make decisions, and access to the people who know the work.
Small changes / More room to work
Useful starts
in the everyday.
Make room for the work that matters.
Repeated copying and chasing are useful places to start a conversation. We look at what could be simpler, and where a person still needs to make the call.
Original Radius campaign films. Starting points for a conversation.
- The current workflow and its handoffs
- Up to three candidate opportunities
- Value, feasibility, and dependencies
- Data sensitivity and operating risk
- Adoption, ownership, and measurement
Someone who can make decisions, the people who know the task, and a few examples of how it works today. We agree written permission before any client data is used in an AI tool.
Do not send confidential, regulated, personal, or sensitive information through the public inquiry form.
What you leave with
Leave with a clear recommendation.
Inside the recommendationWhere time goes.A simple map of the task and the parts that need attention.
- A simple map of the task and the parts that need attention
- A comparison of up to three useful ideas
- A recommended place to start
- An outline of the next steps
- A way to check whether the change helps
- A walkthrough of the findings and one round of revisions
Production software, integrations, data migration, legal or compliance opinions, security certification, custom model training, guaranteed savings, and unlimited revisions.
Timing, commercial terms, workshop length, and payment terms are intentionally not published while the offer is being operationally approved.
Questions
Before the first decision.
What if we do not know which workflow to choose?
That is a reason to begin with this initial work. We compare a small set of candidate workflows and make the decision criteria visible before recommending a build.
Could an existing tool solve the problem?
Possibly. If a suitable tool fits the workflow, data, team, economics, and risk, buying it may be the better decision. The goal is a useful outcome, not a custom build by default.
Will this initial work produce production software?
No. Production software, integrations, data migration, custom model training, and security certification are outside this initial work. A build is considered only after the case and boundaries are clear.
How is our data handled?
The answer depends on the workflow and tools. Before representative data is used, the engagement should document the data flow, access, retention, human review, and contractual requirements.
Can Radius guarantee savings or revenue?
No general outcome guarantee is offered. This initial work can define assumptions, a baseline, a measurement plan, and a clear recommendation; business outcomes also depend on implementation and adoption.