Map workflows and design playbooks
We map how the work actually flows, pinpoint the high-impact repeatable tasks, and write the agent playbooks: what it does, what it must never do, and when a human takes over.
Give the repetitive work to something that never forgets a step.
An AI agent is an autonomous assistant that runs your repeatable tasks — finding leads, sending outreach, answering support questions, processing documents — behind the scenes, in your brand voice, around the clock. Your team keeps the judgement calls.
Workflow mapping first
Learns your brand voice
Connected to your systems
Monitored with guardrails
THE SITUATION
Your most capable people are doing the most repeatable work.
Somewhere in the business, a competent person spends hours each week on work that follows an entirely predictable pattern. Building the prospect list. Chasing the same follow-up. Answering the policy question that has been answered forty times. Retyping what a document already says.
None of that needs judgement — it needs consistency. An agent never skips a step, never forgets to follow up, and does not stop at six o'clock. The point is not replacing the person. It is giving them back the hours the pattern was eating.
SYMPTOMS WE HEAR MOST
Enquiries arrive at night and are answered the next working day The same internal questions are asked and re-answered every week Follow-up happens when someone remembers, not when it should Skilled staff spend hours on list-building, copying and data entryHOW THE WORK RUNS
Map the work first. Build the agent second.
Agents fail when they are pointed at vague work. We define the playbook — the exact steps, the decision points, the escalation rules — before anything is built.
Connect to your systems
The agent is wired into CRM, chat, ticketing and document systems — in days, not months — so it acts on real data instead of a copy of it.
Train on your voice and your answers
We feed it your FAQs, scripts, policies and product data until responses read like your team wrote them, then test the edge cases before anyone external sees it.
Go live, monitor, fine-tune
Launch with monitoring in place, review what it handled well and what it escalated, and tune continuously. Performance is reported, not assumed.
BEFORE AND AFTER
The same work, minus the hours.
Three patterns we see constantly, and what changes once an agent owns the repeatable part.
BEFORE
The team builds prospect lists by hand — roughly 20 hours a week of searching, verifying and copying.
AFTER
The agent finds, verifies and imports around 250 qualified target leads every week.
≈ 20 HOURS A WEEK RETURNED
BEFORE
Enquiries arriving at night and over the weekend sit unanswered, and the warm ones go cold by Monday.
AFTER
The agent engages visitors, answers, books the demo, and hands over the hot leads by morning.
NOTHING WAITS FOR OFFICE HOURS
BEFORE
Staff wait two days or more for an answer on policy, process or product detail.
AFTER
The agent answers instantly from your own approved documents, and cites where the answer came from.
TWO DAYS DOWN TO SECONDS
SEE IT RUN
Watch an agent work a real job.
This is not a video. Pick a job and the agent runs its playbook step by step — including the point where it stops and asks you. Nothing here is hidden from the operator.
TRIGGER · SCHEDULED · MONDAY 06:00
- Read the target profile and exclusion rules CRM
- Search four sources for matching companies Web
- 312 candidates found — checking against existing records CRM
- Discarded 74 duplicates, 12 competitors
- Enriched 226 records with contact name and role Enrichment
- Import 226 new leads into the CRM?
- Written to CRM, tagged to this week's source CRM
- Posted the summary to the sales channel Chat
WORKING
≈ 20 HOURS OF MANUAL WORK REMOVED
226 verified leads in the CRM before anyone opened a laptop.
SYSTEMS TOUCHED
CRM
Web
Enrichment
Chat
Every action is logged, scoped to permissions you set, and reversible.
WHAT YOU ACTUALLY GET
A working agent, documented — not a demo.
- Workflow map and task prioritisation
- Written agent playbooks with escalation rules
- Agent build and brand-voice tuning
- Connection to CRM, chat, ticketing and document systems
- Knowledge ingestion from your own approved sources
- Human handover and approval gates
- Guardrails, permissions and access control
- Monitoring dashboard and performance reporting
- Edge-case testing before launch
- Ongoing tuning and review cycle
HONEST SCOPE
Is this the right thing to buy?
GOOD FIT WHEN
A capable person spends hours each week on work that follows a predictable pattern The information the agent needs already exists in writing somewhere Someone internally can review its output during the first weeksWAIT, OR DO SOMETHING ELSE FIRST
The process changes every time and nobody can describe the steps The work needs judgement or negotiation on every case — that is not agent work There is no appetite for human oversight; unmonitored agents become a liabilityCOMMON QUESTIONS
The things people ask first.
What is an AI agent, and how is it different from a chatbot?
A chatbot answers when spoken to. An agent takes an objective and works through the steps to reach it — searching, checking, writing, updating a record, following up — without being prompted at each stage. A chatbot is one thing an agent can do.
Will it sound like us, or like a robot?
We tune it on your own scripts, FAQs and past responses until the tone matches your team's, then review real output before anything goes customer-facing. If it cannot answer in your voice, it escalates rather than improvising.
What happens when it does not know the answer?
It hands over to a person. Confidence thresholds and escalation rules are set during the playbook stage, so low-confidence cases reach a human with the context attached instead of being guessed at.
Is our data safe, and where does it go?
Access is scoped to only the systems and records the agent needs, permissions are enforced per source, and activity is logged. We define what it may read and write before it is connected to anything.
How long before it is doing useful work?
Typically weeks. Mapping and playbooks take about a week, system connection a few days, then training and testing. The first version does the narrow task well and widens from there.
Does this replace people on our team?
It replaces a pattern, not a person. The work agents take on is the work nobody wanted: list-building, chasing, retyping, answering the same question. The judgement, relationships and decisions stay human.
Tell us what your team keeps doing twice.
Describe the task that eats the most time for the least judgement. We will tell you plainly whether an agent handles it well today — or whether it needs a process fix first.