Bespoke agents
AI agents tailored to your business.
We design and build AI agents for clearly defined business tasks. An agent can work with approved information, interact with connected tools and move a workflow forward — but only within the permissions and controls designed for it.
The goal is not to create an autonomous system for the sake of it. It is to remove useful work from a queue while keeping your team in control.
What is an AI agent?
Software that can decide between permitted next steps.
An AI agent is software that can interpret information, decide between permitted next steps and use connected tools to complete part of a task. Unlike a simple chatbot, an agent can participate in a workflow. For example, it might read an incoming request, retrieve relevant information, prepare a response and ask a person to approve it before anything is sent.
Where an agent can help
Potential use cases.
- ✓ triaging incoming enquiries
- ✓ searching internal knowledge
- ✓ preparing draft responses for review
- ✓ summarising and classifying documents
- ✓ gathering information from approved systems
- ✓ creating or updating records through permitted integrations
- ✓ supporting repetitive back-office workflows
- ✓ coordinating multi-step tasks that currently move between people and systems
These are examples, not promises that every workflow should be automated. We assess feasibility, data access and risk before recommending an agent.
Designed with boundaries
Useful agents need clear boundaries.
We define what the agent can see, which tools it can use, which actions require approval and what it should do when information is missing or uncertain.
- ✓ scoped permissions
- ✓ approved data sources
- ✓ human-in-the-loop approval
- ✓ activity logging
- ✓ explicit action limits
- ✓ fallback/escalation paths
- ✓ testing against realistic scenarios
Agent or automation?
Not every process needs an AI agent.
If a task follows fixed rules, conventional automation can be cheaper and more predictable. Agents are more useful where the workflow involves interpreting unstructured information, selecting between several permitted paths or working with natural-language requests. We will recommend the simpler approach where it solves the problem.
Our agent development process
From workflow mapping to pilot.
- ✓ Identify a repetitive, valuable workflow.
- ✓ Map the current process and systems.
- ✓ Define permitted data and actions.
- ✓ Prototype the agent.
- ✓ Test with realistic scenarios.
- ✓ Add approval, logging and fallback controls.
- ✓ Pilot with a small group.
- ✓ Measure the result before expanding.
FAQs
Frequently asked questions about bespoke AI agents.
Can an AI agent access our existing systems?
Potentially. This depends on whether the relevant systems provide suitable APIs or other secure integration methods. Access should be limited to what the agent genuinely needs.
Can we approve actions before they happen?
Yes. Human approval can be included at defined points so the agent prepares or proposes an action without completing it automatically.
Is an agent the same as a chatbot?
No. A chatbot primarily handles a conversation. An agent can participate in a wider workflow and, where permitted, use connected tools or data to move a task forward.
How do we know whether an agent is worth building?
Start with the current cost or friction of the workflow. A pilot should have a measurable outcome such as time saved, reduced handling effort or faster access to information.
Contact
Have a workflow that might suit an AI agent?
Show us how the work happens today. We will help you decide whether an agent, conventional automation or a different application is the most sensible solution.
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