Capable agents, contained by design.

An editorial line drawing of a robot working inside a small fenced workshop paddock, reaching for an approved tool on a peg-rack, with an inbox tray of incoming work resting outside the fence.

An agent without limits is a liability. We build systems that read messy inputs, use approved tools, and produce auditable outcomes — from request triage to AI-assisted quote drafts — inside a sandbox you control, against permissions you write down before anything ships.

Book the workshopResults in 2-4 weeks or money back
Rules don’t reach

The work depends on reading messy inputs, weighing context, and choosing the next move. Hard-coded logic gives up before it starts.

Context is scattered

Specialists spend their day stitching context across tools because no single system knows the whole picture, and the people who do become the bottleneck.

AI access is risky

Pointing a model at real systems with broad permissions is a non-starter for serious teams. The experiments stall before they ship.

Three phases. From scope to shipped agent.

The structure surfaces boundaries early and earns trust before any code lands in production. Each phase has a defined output you can hold us to.

Phase 01

Scope

What happens
  • Identify the workflow where manual effort is high and rules are fuzzy
  • Map the systems, data, and messy edges the agent has to handle
  • Write down what the agent can read, write, and call before any code lands
Phase 02

Build

What happens
  • Implement the task flow: gather context, call tools, decide, produce output
  • Expose internal systems through approved APIs and purpose-built tools
  • Run the agent against real cases inside a sandbox until reliability holds
Phase 03

Ship

What happens
  • Stabilise prompts, tools, and fallback paths against real traffic
  • Hand the system to your team with documentation and an ops runbook
  • Optional supervision, governance, and rollout to the next workflow

Running an agent inside a sandbox.

01Input

Instructions

Mission, scope, operational boundaries

02Input

Data Files

Briefs, prior runs, internal records

03Input

Acceptance criteria

Conditions the work must meet to be signed off

O1Observer

Observability

Trace every tool call to see the steps the agent took.

Sandbox
An AI agent running inside a sandbox, connected to allow-listed tools and observability
T1Tool

WebSearch

Allow-listed domains

T2Tool

Full computer access

Isolated from the host

T3Tool

Internal systems

Scoped to this workflow

03Output

Work done

Validated artefacts handed back to the person

A controlled run, from brief to signed-off outcome.

00PromptQueued

Complete a client intake record correctly and validate it before submission.

Delivered to the agent
01ReadPending

Reads the onboarding instructions to understand what a complete intake requires.

read_fileinstructions/onboarding.md
Awaiting
02ResearchPending

Checks current compliance rules in case requirements have changed.

web_searchlatest KYC field requirements 2026
Awaiting
03DraftPending

Writes a first draft of the client intake record.

write_filerecords/client-intake.json
Awaiting
04ValidatePending

Runs validation against the draft before anything is submitted.

run_scriptscripts/validate-intake.sh
Awaiting
05RecoverPending

Adds the missing field discovered during validation.

write_filerecords/client-intake.json
Awaiting
06ValidatePending

Re-runs validation to confirm the record is correct.

run_scriptscripts/validate-intake.sh
Awaiting
07OutcomePending

Intake complete and validated.

Awaiting

Start with a workshop.

A private session where we surface the workflow worth automating, score it against the feasibility scorecard, and decide together whether it is worth a pilot. If you have specific questions about systems, security, or fit, get in touch first.

Frequently asked questions.

What makes a workflow a good first pilot?

The best first pilots usually involve repeated manual work, multiple systems, messy inputs, and a clear business payoff if execution becomes faster or more consistent. AI-assisted quoting is a common fit when inbound requests need a margin-aware offer draft before a human sends anything.

Do we need mature internal APIs before this can work?

No, but existing APIs and structured data help. Part of the audit is understanding what interfaces already exist and where wrappers or purpose-built tools are needed.

Can write access be limited?

Yes. Workflows can be designed for read-only research, draft generation, approval before execution, or direct writes for lower-risk actions.

How do you handle private or sensitive internal data?

The systems are designed around explicit permissions, approved tools, bounded execution environments, and review paths. The goal is controlled access to a specific workflow, not unrestricted access to everything.

Is this only for large enterprises?

No. The strongest fit is usually a technically mature team with real workflow complexity, whether that sits in a mid-market company, a product organization, or an operations-heavy business.

Why start with an Agentic Automation Workshop instead of jumping straight into implementation?

The workshop is the low-risk first step. It identifies the one workflow worth piloting first, maps the relevant systems and safety boundaries at a practical level, and decides whether the next step is a fixed-scope pilot, a deeper workflow audit, or an honest no.

Find the workflow. Build the agent.

We identify the one workflow worth piloting first, backed by value math, feasibility scoring, and a 1-page written diagnostic within 48 hours.