Agents are software with judgement — powerful when governed, chaotic when not. We help you work out where they fit, set the guardrails, and build them.
Agents suit work that needs judgement and context across systems — triage, research, scheduling, qualification. Plenty of processes are better served by plain workflow automation, and we'll say so when yours is: it's cheaper, and it fails more predictably.
Every agent we design operates within defined parameters: what it may access, what it may spend, when it must hand off to a human, and a full audit trail of every decision. An agent you can't audit isn't an asset — it's a liability with API keys.
We treat agents like production software: monitored, measured and reviewed, with their decisions inspected and their prompts and tools tuned as your business changes. Not an experiment left running in the corner.
The same low-risk path as everything we build: find the case, prove it small, then scale.
A focused half-day mapping your processes and scoring the highest-payback opportunities.
One narrow build, end-to-end and live in weeks — proving value fast.
Once it's earning its keep, we extend and maintain it as an ongoing programme.
An AI agent is software that pursues a goal across your systems — reading context, deciding the next step, taking it, and escalating to a human when it's unsure. That's different from workflow automation, which follows a fixed path. AI agent consulting is the work of deciding where that autonomy helps, how much of it to grant, and how to deploy it safely.
A good agent consultant earns their fee mostly through judgement calls: which processes justify an agent at all, which model and orchestration approach fits, what the agent may and may not do, and how success gets measured. We've made those calls repeatedly in production — including multi-agent orchestration where several specialised agents work together on one process.
The agents we've shipped aren't chatbots. They research and qualify prospects into a sales pipeline, assemble and audit reports, schedule engineers against shifting constraints, and raise jobs from unstructured inbound requests — each one working inside a defined lane, with a human owning the outcome.
The pattern across all of them: the agent does the gathering, cross-referencing and drafting that used to eat someone's day, and a person makes the calls that matter. Your team doesn't get replaced — it gets the boring third of the job taken off its plate.
"Agentic" doesn't have to mean "unsupervised". In production, every agent runs with explicit permissions, spend and rate limits, escalation rules and full decision logs. We review what the agents actually did — not what we hoped they'd do — and tighten or extend their parameters based on the evidence.
That's also why agent projects start small. A pilot agent on one process, measured against the manual baseline, tells you more about your real risk and return than any framework evaluation. Scale follows proof.
Software that pursues a goal rather than following a script: it reads the context, chooses its next action, uses your systems to take it, and hands off to a human when it's outside its parameters. A workflow follows a fixed path; an agent decides the path.
Workflow automation is the right tool when the steps are known in advance — it's cheaper, faster to build and easier to test. Agents are for work where the steps depend on what's found along the way. A good consultant's first job is telling you which one your process actually needs.
Identifies which of your processes justify an agent, designs its scope and guardrails — permissions, escalation, audit trail — selects the model and orchestration approach, and defines how success is measured. With us, the same team then builds and runs it.
They can be, if they're governed like any other production integration: least-privilege access, explicit limits on actions and spend, human sign-off on consequential steps, and full logging. We design the guardrails before we design the capability, in that order.
The same shape as all our work: a fixed-scope audit first, priced up front, which identifies whether an agent is justified and what it should be allowed to do. The build is then quoted per use case — so you're never paying for autonomy you didn't ask for.
A first agent on a well-chosen process is a weeks-scale project, not a quarters-scale one — our first builds typically go live in under four weeks. The pilot runs against a manual baseline so the decision to scale is made on measured results.
That's the point of them. Agents act through your existing CRM, ERP, inbox and internal tools via their APIs — the work of consulting is largely deciding what access each agent gets, and proving it behaves inside it.
When the process has fixed steps, when errors are costly and hard to catch, or when the volume doesn't justify the build. Roughly half our agent conversations end with us recommending a plain workflow instead. The other half are why this page exists.
An agent doing exactly this, in production.
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A bespoke prospecting tool that takes one instruction — the kind of business you want to reach — and hands back a populated CRM of verified, sales-ready contacts. A 100+-company list that took most of a working day is now enriched and pushed in under ten minutes.