Agents that do the work. With a human holding the keys.
Agentic AI goes beyond answering questions: agents plan steps, call tools and act across your systems. We design multi-agent workflows with clear orchestration, bounded permissions and human approval gates, so automation moves work forward without taking decisions it should not.
You're in the right place if…
- Operations teams running multi-step processes that span several systems and handoffs
- Organisations that have a working assistant and want it to take action, not just answer
- Technology leaders who need agent behaviour to be observable, reviewable and reversible
What gets in the way.
Agents that wander
Open-ended agents can loop, take unexpected paths and run up cost without finishing the task.
Too much access
An agent with broad credentials can do broad damage. Permissions need to be as narrow as the job.
No clear point of accountability
When an agent acts, someone must be able to see what it did, why, and who approved it.
Hard to test
Behaviour that varies between runs is difficult to verify with conventional testing alone.
Agentic AI, end to end.
Multi-agent workflow design
Breaking a process into specialised agents with defined roles, inputs and outputs.
Orchestration
Coordinating agents, tools and deterministic steps, with retries, limits and clear stopping conditions.
Human approval gates
Review and approval steps placed where decisions carry risk, so people stay in control of what matters.
Tool and system integration
Giving agents safe, least-privilege access to the APIs, data and applications they need.
Agent observability
Traces of every step, tool call and decision, so behaviour can be reviewed, debugged and audited.
A delivery approach you can plan around.
Map the workflow
Walk through the process with the people who run it and decide which steps suit an agent, which suit code and which need a person.
Design the boundaries
Define each agent's role, tools, permissions, limits and the approval points before writing prompts.
Build and test
Build the agents and orchestration, then test against realistic scenarios, including the failure cases.
Run with oversight
Launch with approvals and tracing in place, and loosen or tighten oversight based on observed behaviour.
Ways to work with us.
Workflow pilot
One bounded workflow, built end to end with approvals, to prove the model before expanding.
Production programme
A phased rollout of agentic workflows across a process area, with shared tooling and governance.
Technologies we work with
- OpenAI and Anthropic models
- Agent orchestration frameworks
- Tool calling and Model Context Protocol (MCP)
- Workflow and queue infrastructure
- Tracing and observability tooling
Agentic AI: common questions.
What is the difference between an assistant and an agent?
An assistant answers questions. An agent can plan a sequence of steps and use tools to act, such as updating a record or raising a ticket. That extra power is why agents need tighter boundaries and oversight.
Do agents act without human review?
Only where you decide they should. We place approval gates on steps that carry risk, and many workflows start with a person approving every action before any autonomy is granted.
Have you built agentic systems yourselves?
Yes. ADIS, our AI software factory, runs agentic AI across requirements, design, build and test with human approval gates between stages. The same design principles go into the workflows we build for clients.
When is an agent the wrong choice?
When a process is well defined and repeatable, deterministic code is usually cheaper and more predictable. We'll tell you when that is the better answer.
Let's talk about your agentic ai needs.
Someone from our Data & AI practice will reply within one business day to talk through the use case.