An agent with a defined job
A scoped assistant or integrated agent with a clear audience, approved sources, and explicitly permitted tool actions.
AI agents & knowledge
AI agents for your business. A defined job. Clear limits.
Build an AI agent that answers from approved company knowledge, prepares useful work, and uses agreed tools. Define its users, permissions, and evaluation cases before expanding what it can do.
Assistant workspace
A useful handoff
An answer with its context.
| Request | Assistant prepares | Review route |
|---|---|---|
| How do I claim travel? | Answer linked to the travel policy | Colleague checks the source |
| Can I make an exception? | Question and relevant policy passage | Policy owner decides |
| What if no policy covers it? | Missing guidance clearly flagged | Ask the policy owner |
The role includes finding and preparing information. An unsupported answer has a route to a person.
Built around your work
When this makes senseRecognize
Recognize
the friction?
A convincing answer is not the same as a correct answer. A useful business agent needs trusted sources, limited permissions, and a way to stop when context is missing. Otherwise your team is left checking both the answer and the trail of actions behind it.
A good fit when…
Your team answers recurring questions using information scattered across approved documents.
A useful reply or work draft requires finding context before anyone can begin writing.
You need an assistant with a defined role, permission limits, and a clear handoff when it is unsure.
Tangible work
What you take away.
A reviewable answer trail
Source references where applicable, visible uncertainty, and records of proposed or executed actions appropriate to the project.
An evaluation and handoff
Representative questions, difficult cases, permission tests, and guidance for maintaining knowledge and reviewing failures.
Put it to workReal tasks.
Real tasks.
A more useful way through.
Find a starting point for your team.
01
Give support the right context
Retrieve relevant guidance and prepare a source-linked reply alongside the ticket.
Explore the workflow 02Prepare an executive brief
Pull requests and commitments into a review list with links back to their original threads.
Explore the workflow 03Draft from approved scope
Assemble a proposal from agreed inputs, flagging missing pricing or terms for its commercial owner.
Explore the workflowOne possible workflow
From input to a clear next step- 01 / The starting point
A colleague asks how to handle a travel expense.
- 02 / The right context
Retrieve the current policy from an approved knowledge source.
- 03 / Prepared for review
Draft an answer with the relevant passage and flag missing context.
- 04 / A person decides
The policy owner checks an ambiguous exception; no booking or payment occurs.
From first conversation to handoffA clear start.
A clear start.
An agreed finish.
- 01
Define the role
Specify the users, knowledge sources, permitted actions, and the situations that should go to a person.
- 02
Build and challenge it
Test source retrieval, incomplete information, conflicting policies, and attempts to push beyond its permissions.
- 03
Introduce it with an owner
Start with an agreed audience and a review process. Decide who updates sources and investigates unexpected behavior.
Agree the scopeAgree the scope
Agree the scope
and the limits.
An agent is not unrestricted autonomy. Sending messages, updating important records, and making consequential decisions require the approval rules you choose. It should decline or escalate unsupported requests rather than fabricate an answer.
Security and data questions ↗A few useful answers
Before we begin.
What does a first AI agent project include?
A useful first scope defines one job, an initial audience, approved knowledge sources, and permitted tool actions. Deliverables can include the assistant, source references, a representative evaluation set, and a handoff guide. Knowledge search, draft preparation, and record updates have different requirements and should be scoped explicitly.
How do you test an AI agent before launch?
Agree expected behavior on ordinary questions, missing information, conflicting sources, and requests outside the user's permissions. Check the evidence behind an answer and whether the agent stops or escalates correctly. Acceptance depends on the agreed test results and remaining failures, followed by monitoring during the initial rollout.
What determines AI agent development cost?
Cost depends on knowledge preparation, integrations, permission complexity, interface needs, and the depth of evaluation. Operating costs can include model requests, retrieval infrastructure, hosting, and source maintenance. Estimate these using the expected tasks and usage rather than model token price alone.
How long does it take to build an AI agent?
Source readiness, tool access, user permissions, and review availability shape the schedule. A knowledge assistant with one approved source has a different scope from an agent that updates several systems. Set a project timeline after testing the uncertain parts and agreeing acceptance criteria.
Can the agent use private company documents?
Private documents can be considered once access permissions, provider handling, retention, and the intended audience are agreed. Retrieval must respect the user's access to the underlying information. Test permission boundaries and use redacted examples while the data-sharing arrangements are being established.
Who keeps the agent accurate after launch?
Name an owner for source updates, evaluation cases, access changes, and unexpected behavior. Changes to models, prompts, tools, or documents can affect previous results and should trigger relevant checks. The handoff must distinguish the client's operating responsibilities from any separately agreed maintenance or support.