Employee assistance
Bring the right context into the work.
Find policy, account or case information, cite the source and prepare a useful answer for a person to review.
Where to start
Start with a bounded job, not a broad AI programme.
The right first use case is valuable enough to matter, narrow enough to evaluate and grounded in data your people already trust.
01
High-frequency work
A repeated task where faster preparation or better context creates visible value.
02
Reliable context
The records, knowledge and permissions the agent needs are understood and available.
03
A clear human hand-off
The agent knows when to ask for approval, escalate or stop.
Useful before impressive
Where an agent can earn its place.
Agentforce is most useful when it brings trusted context into a repeated decision, while keeping accountability with the person doing the work.
Case work
Prepare the next step without losing judgement.
Summarise records, identify missing information and route exceptions to the right person with the context intact.
Controlled actions
Let the agent act inside clear limits.
Create or update records, call approved tools and log what happened, within the user’s permissions and approval rules.
The readiness gate
The agent is the last layer, not the first.
Before we recommend a build, we test the idea against four foundations. Weakness in one does not always stop the work, but it changes what should happen next.
The output is a decision:
build a pilot, strengthen the foundations first, or do not automate this workflow yet.
- 01
A job to improve
One task, one owner and a result that can be measured.
- 02
Data the agent can trust
Known sources, clear ownership and enough quality for the decision at hand.
- 03
Boundaries it cannot cross
Least-privilege access, approval points, escalation and safe failure behaviour.
- 04
A way to prove it works
Test cases, pass criteria and monitoring before the agent reaches real work.
How we work
From one use case to a controlled rollout.
- 01
Frame
Choose the workflow, the user and the outcome. Remove ideas that are broad, vague or hard to measure.
- 02
Design
Map the data, permissions, tools, instructions, approval points and human hand-offs.
- 03
Prove
Build the smallest useful version and evaluate it against realistic examples, including failure cases.
- 04
Roll out
Introduce it to a controlled group, monitor the evidence and expand only when the results support it.
Proof
Built in public. Measured in the real world.
All case studies →
We have built and shipped an Agentforce experience of our own. Our first commercial client implementations are in progress, and we will publish them when they are live.
What is Agentic AI?
Agentic AI describes systems that can pursue a defined goal, use approved data and tools, take actions within clear limits and report what happened. The important difference is agency: an agent can act, so permissions, evaluation and human oversight must be designed into the solution.
How can Agentforce support our organisation?
Agentforce can support repeated work across sales, service and internal operations. Useful examples include preparing a case response, finding trusted context, updating approved records or routing an exception. We start with one bounded job whose value and failure conditions can be measured.
How do we know whether we are ready for AI agents?
You need a clear job to improve, data the agent can trust, boundaries it cannot cross and a way to prove that it works. If one of those is missing, the right next step may be to strengthen the foundation before building the agent.
How do you address AI security and governance?
We design around least-privilege access, trusted sources, approved actions, test cases, monitoring, escalation and human oversight. The controls depend on the use case, the sensitivity of the data and the consequences of a wrong action.
A practical first step
Bring us one workflow. Leave with a decision.
Apply for a free three-hour working session using the processes and information you share. Within five working days, you receive a written use-case recommendation and preliminary architecture sketch, with assumptions and verification gaps recorded. No org access or implementation is included.