Manual steps take time
Information is moved, checked or compiled the same way over and over again.
Practical AI and automation for business
Farbar
We help you move from a workflow that takes unnecessary time to a bounded solution you can try, measure and take responsibility for. The technology is chosen only once the problem, the people and the goal are clear.
The workflow first
A small, measurable pilot
People stay responsible
When technology is not the question
Start with the work that actually needs to get better.
AI is not a goal in itself. Value appears when technology solves a clear problem for the right people, with usable data, an accountable owner and reasonable controls.
Knowledge gets stuck with people
The right answer exists, but it is hard to find when someone needs it or when a colleague is away.
Handoffs create waiting
Cases, documents and decisions pass through several people or systems without a clear picture of where things stand.
Ideas get stuck as pilots
The technology looks promising, but ownership, risks, measures and the path into everyday work are unclear.
For organisations with real friction
For those who see the opportunity but need a sensible place to start.
Farbar suits organisations that already use digital tools, but where work between people, documents and systems still takes too much time or becomes unnecessarily hard.
Business leaders
You see where time, quality or customer experience is being lost and need a concrete basis for decisions.
Team and process owners
You know the exceptions, the handoffs and the everyday problems that a generic AI demo never captures.
IT and systems owners
You need solutions that respect existing systems, permissions, data, operations and support.
From an unclear problem to a working pilot
Map. Prioritise. Deliver.
A structured approach makes it possible to start small, learn fast and still keep the whole picture.
Understand the current state
We follow the workflow, the roles, the systems, the data, the waiting times and the exceptions. The problem is defined before the solution is chosen.
Result: a shared picture of the current state and clear problems to address.
Choose the right starting point
Opportunities are weighed against value, feasibility, data readiness, risk and measurability. Not everything that can be automated should be automated first.
Result: a well-founded pilot choice with a goal, an owner and a clear scope.
Test it in reality
We carry out what has been decided and try it with real users. Effects, errors and exceptions are followed up before anything is allowed to grow.
Result: learning from a working workflow, not just a demo.
Clear first deliverables
Start at the level that matches where you are today.
Every step should give you something you can decide on, use or test. You do not need to commission a large change programme to get a useful next decision.
AI and automation review
A focused review of one business area and the workflows with the greatest potential for improvement.
You get: a concrete basis for deciding the next step.
Pilot design
A workable plan for the first solution, designed around use and effect rather than a technology demo.
You get: a pilot plan that can be built, tried and assessed.
Build and implement
Hands-on support from prototype to a solution that works in day-to-day operations.
You get: real evidence for adjusting, scaling or stopping.
Already using AI? We can also assess what you already use, as a separate assignment. About the assessment of AI and agents
Typical starting points
Common tasks that can be examined in practice.
These are examples of problem types, not claims about previous customer results. The right solution always depends on your situation.
Sort, summarise and suggest the next step
Reduce reading and data entry while a person keeps the decision.
Extract, check and route information
Turn invoices, forms, contracts or reports into a traceable flow.
Make the right information easier to find
Give source-grounded answers with permissions and a clear path for uncertain cases.
60-second value check
Where might your best first candidate be?
Tick what fits best. The result is a direction for further mapping, not an automatic answer or a technology choice.
Frequently asked questions
Good questions before you start.
Do we already need to know what we want to automate?
No. It is enough that you can describe a workflow that takes unnecessary time, creates waiting or produces uneven quality. The review should help you tell a real need apart from a solution idea.
How do we know whether the problem needs AI?
We do not know in advance. Clear rules and stable data flows are often a good fit for conventional automation. AI can be relevant when the work requires interpretation, summarising or searching in text. Sometimes a process change is better than both.
Can we use our existing systems?
That is the starting point. We first explore what can be done with the systems, data and permissions you already have. You can then decide whether anything new is needed.
How are sensitive information and risk handled?
Data, access, storage, suppliers, human control and failure paths need to be described as part of the solution. Which controls are needed depends on the workflow's data and consequences.
What happens if the pilot does not have the intended effect?
That is also a useful result. A bounded pilot should provide enough evidence to adjust, choose a different starting point or stop before more time and money are committed.
First conversation