Services
Agentforce and artificial intelligence
We build on Salesforce’s AI layer for a measurable business result, not for the demo. Let an assistant handle the repetitive questions so your team can spend its time on the work that needs judgement.
Use cases
Where it genuinely pays off
We say plainly that AI does not suit every process. These are the four areas where it delivers most reliably.
Customer assistant
An assistant that answers recurring questions — order status, shipment tracking, return conditions, product compatibility. It builds answers from your own product and order data rather than inventing them, and hands over to a person when it cannot resolve something.
Record summarisation
Long customer histories, open cases and meeting notes condensed into a single paragraph. Handovers and pre-meeting prep take seconds instead of minutes.
Visit and call analysis
Free-text notes written by the field team turned into structured data: product discussed, competitor named, objection raised, next step agreed. Managers get a weekly synthesis report out of it.
Next-step suggestions
Opportunities that have gone quiet, accounts ordering less often, customers showing risk signals. The system does not wait to be asked — it opens a task for the right rep.
Approach
How we build it
The most common mistake in AI projects is starting with the technology. We start with the outcome: which task gets faster, which errors reduce, who saves how much time. If there is no measurable target, we do not take the work on.
The data foundation
An assistant’s answer is only as good as the data behind it. Before setup we decide which sources will be used and clean out missing or contradictory content. Skip this step and the assistant answers wrongly with complete confidence — which is the worst possible outcome.
Drawing the boundaries
- Which topics the assistant answers and which it hands over
- What data it can reach and which records stay invisible to it
- Behaviour rules for sensitive areas such as pricing, discounts and contracts
- What happens when no answer can be found
Testing and measurement
Before go-live we test against real question sets. After launch we keep monitoring, reporting which questions get handed over and where the assistant is weak. It is a system that improves over time, not a box that gets installed and forgotten.
Cost control
Salesforce AI usage runs on a credit model, and flows configured carelessly can burn through consumption unexpectedly. We cap how often each flow can run and monitor usage from day one.
Start small
We recommend beginning with a single use case and a narrow question set. Seeing something working in four weeks teaches you more than a six-month design exercise.
Licence requirements
Agentforce is licensed separately and is not included in every Salesforce edition. We check whether your current licensing covers it during discovery, before any work is scoped.
FAQ
About AI
What if the assistant gives wrong information?
Does our customer data leave our systems?
Which languages does it handle well?
Will it replace our team?
Let us find the process worth automating
We will work out together where AI adds real value in your operation. If no suitable use case emerges, we will tell you that too.