For automation that acts, inside limits you set
AI Agent Development
An agent that can act is only as safe as the boundary around what it can act on. This practice builds that boundary alongside the agent itself: scoped tools, tested permissions, a full action log. Autonomy expands on evidence, whether the agent is new or already proving itself.
How a bounded agent earns wider permissions
Tool access, a tested permission boundary and the evidence that justifies more autonomy.
90 secSample frame · video pending01Before any permission is granted
The permission decision worth making explicit
An agent that can act carries different risk from one that only answers. Three checks decide how tightly its permissions should be scoped before anyone builds it.
Does the task require action, or just an answer?
A question-answering feature is a simpler build than one that changes a record or sends a message on its own.
What is the worst action the agent could take?
Permission boundaries are sized to the worst case, not the average one, because the average case rarely causes damage.
Who reviews the audit trail, and how often?
An agent nobody watches drifts into behaviour nobody approved. A review cadence is agreed before the agent goes live.
02Agreed before any agent runs
The ledger that keeps autonomy honest
Every agent engagement is scoped before a line of code runs: which workflow you bring, what gets engineered around it, what you receive, and what stays under your approval throughout.
- Your side
You bring
- The workflow and the steps it repeats today
- The tools and systems the agent needs access to
- The outcome that counts as the task done right
- Our side
We build
- An agent scoped to a defined set of tools
- Permission boundaries for what the agent can touch
- Logging so every action the agent takes is traceable
- Your side
You receive
- A working agent operating inside its permission set
- An audit trail of every action it has taken
- A dashboard showing what it did and why
Never leaves you
- Which tools and systems the agent can reach
- Approval authority over any permission expansion
- The workflow and its ownership after handover
Where the line sitsWe build the agent and its permission boundary together. Expanding what it can touch is always your call.
03Three drivers, not a rate card
What actually drives agent build cost
Agent work is priced against the assessment, not a template, because these three factors change the effort involved by multiples.
Number and sensitivity of tools
An agent reading one internal system is simpler than one writing across several systems with real consequences.
Coordination across multiple agents
A single agent on one task is straightforward. Coordinating several agents across a process adds a layer of its own.
Autonomy level required at launch
A cautious agent that escalates often ships faster than one expected to act independently from day one.
04Evidence and proof
Agents still operating inside their original permission set.
Agent proof is a permission boundary that held under real use, not a clever demo of one successful task. Every record here is a preview awaiting the client's written approval to publish.
Explore case studies
A bounded agent cleared an approvals backlog without one unauthorised action.
Orra Systems had a manual approvals queue nobody could keep pace with. A permissioned agent cleared the backlog while every action stayed inside its defined limits.
- Backlog cleared
- Within the first month live
- Actions outside its permission set
- Zero, by design
A support-routing agent earned wider autonomy after one proven quarter.
Aster North started a routing agent with heavy human review. Evidence from its first quarter justified expanding its autonomy without expanding the risk.
- Human review at launch
- Every action, by design
- Autonomy expanded after
- One evidenced quarter
We could see exactly what the agent touched and why, from day one. That visibility is what let us trust it faster.
Sample · pending client approval
05Read this first
When agent engineering is the wrong starting point
Engineering bespoke permissions for a task that only needs a conversation would cost more than it earns us in trust. Alternative starting points are marked before any pitch.
- Chatbot Development
You need a conversation, not an action
A chatbot that answers questions is a lighter build than an agent that changes something on a user's behalf.
A packaged support experience would fit faster
A ready-made customer support build can beat engineering bespoke agent permissions from a blank page.
- AI Consulting
The workflow itself is still undefined
Rank and test the case first, so the agent gets built around a workflow that has already earned it.
| Shape | Best when | You direct | We carry |
|---|---|---|---|
| Scoped build | The workflow and permissions are settled | Priorities and sign-off | Agent design, permissions, logging |
| Delivery pod | Autonomy expands as evidence accumulates | Product decisions each cycle | Engineering, evaluation, releases |
| Team extension | Your leads already run agent delivery well | Architecture and standards | Named engineers and continuity |
06Straight answers
Asked before an agent gets its first permission.
01How is an agent different from a chatbot?
A chatbot answers; an agent acts. Agent development builds tool access, permission boundaries and logging for a system that changes something, not just responds to a question. Chatbot builds skip most of that machinery because nothing changes as a result.
02How do you decide what an agent is allowed to do?
Against the worst plausible action, not the average one. Permissions are scoped to the specific tools and systems a task requires, and anything beyond that scope is refused by design, not by convention.
03What happens if an agent makes a mistake?
It is logged, escalated where the situation warrants it, and reviewed on a set cadence. Because every action is traceable, a mistake becomes evidence for tightening the boundary, not a mystery to investigate.
04Can agents work together on one process?
Yes, with a coordination layer that hands work between them and defined escalation points back to a human. Multi-agent systems raise the stakes of a permission mistake, so those points are agreed before launch.
05What does an agent build cost?
Scoped work is priced against tool access, coordination complexity and the autonomy level required, from the assessment. Ongoing delivery is billed monthly against a scope that moves with evidenced autonomy.
06How fast can autonomy increase after launch?
Only as fast as the evidence justifies. A cautious agent earns wider permissions in reviewed steps, each one reversible, rather than through a single large expansion nobody can fully evaluate.
07Do you build on our existing tools and systems?
Yes, agent access is engineered against the tools and systems you already run, with the same permission and logging discipline applied regardless of which platform sits underneath.