AI Agents
Develop task-focused agents that use approved information and tools to work towards a defined outcome.
AI Agents & Agentic Automation
Move work forward.
Keep people in control.
Connect AI agents, business tools and approval steps to handle multi-step work within clear operational boundaries.
The business case
Start with a useful outcome.
Some tasks follow a fixed sequence. Others need a system to choose the next step based on what it finds. We distinguish between the two before introducing an agent. Tool permissions, stopping conditions, approvals and a record of actions are part of the design from the beginning.
Discuss your requirementCapabilities
What we can help you build.
The scope is shaped around your systems, your information and the work you need to do.
Multi-Agent Systems
Coordinate specialised agents where separating responsibilities offers a clear operational benefit.
Autonomous Workflows
Run agreed sequences with explicit boundaries, exception handling and approval points for consequential actions.
Intelligent Task Automation
Combine business rules and AI assistance to reduce repetitive handling of documents, requests or records.
AI Orchestration
Manage the flow of information and actions between models, tools, services and human reviewers.
Practical applications
Where this can help.
Examples of suitable use cases, to help you think through your own requirements and decide whether there is a worthwhile starting point.
Request handling
Classify a request, gather relevant context and prepare a proposed response for review.
Internal operations
Coordinate routine information gathering across approved business systems.
Research and synthesis
Collect material from permitted sources and organise it into a reviewable output.
A clear working agreement
Know what you are
working towards.
Deliverables are agreed before work begins. A typical engagement may include the following, adjusted to the scope and complexity of your project:
- A workflow map with ownership and approval points
- An agreed tool and permission model
- A working automation with logs and exception handling
- Evaluation of task completion, failures and operating cost
Before we begin
A useful first conversation.
Pick a repeatable process and describe its normal path, common exceptions and the actions that need approval. This makes it easier to judge whether an agent is useful or a simpler workflow would suffice.
Talk through your ideaCommon questions about getting started
What to expect before and during a project.
An agent may help when the next action depends on information discovered during the task. If the steps are predictable, a defined workflow can be easier to test and operate.
They can be connected to tools that perform those actions, but only within the permissions and approval rules agreed for the application. Higher-impact actions need deliberate safeguards.
Measure completed tasks, error patterns, unintended actions, time taken and cost. A convincing demonstration is a starting point; repeated evaluation is needed before operational use.
Connected expertise
Bring the pieces together.
Generative AI & LLMs
Build assistants, copilots and language model applications that help people find information, draft work and use approved business knowledge.
Explore serviceArtificial intelligence
Build AI applications around a clear business task, with the right data, practical controls and a useful place in your existing workflow.
Explore serviceCybersecurity
Understand where your applications, networks and working practices are exposed, then turn the findings into a clear plan of action.
Explore serviceStart a conversation
What would you like to build?
Tell us what is slowing you down, or what you want to do next. A short description of your business question is all it takes to begin.