Intelligence · AI Agents
A team that works while you do
AI agents with a job each: a chief of staff that takes your request and hands it to the right specialist, agents that check, chase and draft on a schedule, and one approvals queue so nothing goes out without you.
First, an honest question
Agents, a chatbot, or simple automation?
A chatbot talks to your customers. Automation follows fixed steps. Agents sit in between: they work behind the scenes for your team, handle tasks that need judgement, and use your tools to get them done.
If a task is the same every time, plain automation is cheaper and more predictable, and we'll tell you so.
Agents are right when
- Work needs reading and judgement: replies, quotes, summaries, follow-ups.
- Things slip between the cracks: renewals, chasers, unanswered enquiries.
- Your admin is the same kind of work, but never quite the same twice.
- You'd hire an assistant if you could justify the cost.
- You want help, not autopilot: drafts you approve, not messages sent for you.
The Journey
From "I can't do it all" to a team that does the legwork
Each agent gets a job description, the right tools and firm limits, just like a new hire.
We find the jobs worth handing over
We look at where your hours go: the replies, chasers, quotes, reports and checks that fill the week. Then we pick the ones where an agent can save real time without taking risks with your customers.
- An inventory of repeat work
- Hours estimated per task
- What must always stay with a person
Specialists, not one do-everything bot
Each agent gets a clear role, such as estimator, compliance, marketing or accounts, with the tools it may use and the lines it must never cross. A chief of staff sits on top, reading your request and handing it to the right specialist.
- One role per agent
- Tools and limits written down
- A chief of staff to route the work
Agents that work from your facts
The agents read from your AI brain: your prices, processes and notes. They use real tools to look things up and prepare work, rather than guessing.
- Answers from your own content
- Tools to look up, calculate and draft
- Rules-based fallback if AI is unavailable
One queue for everything going out
Replies, quotes, reminders and posts all land in a single approvals queue. Approve, edit or discard. Every action an agent takes is logged, so you can always see what it did and why.
- Nothing customer-facing sent automatically
- A full log of every agent action
- Spending limits on AI usage
Switched on one at a time, reviewed regularly
Agents start on request, then move to scheduled daily checks once they've proved themselves. We review what they produced with you and adjust their instructions, so the drafts need less editing over time.
- One agent live at a time
- Scheduled checks once trusted
- Reviewed against drafts kept versus rewritten
How we work
Three frameworks holding the team up
One for how we engage, one for how agents are built to be useful and safe, one for how they're proven before they get more responsibility.
Engagement
We start from the work your team actually does. Every agent's role, tools and limits are agreed in writing before it runs, and you name who approves its work.
- Work inventory first
- Written role and limits per agent
- A named approver on your side
- Regular reviews of agent output
Architecture
A chief of staff routes requests to specialist agents, each with only the tools its job needs. Answers come from your own content, outputs go to an approvals queue, and everything is logged.
- Least-privilege tools per agent
- Grounded in your own content
- Approvals queue and audit log
- Rules fallback and cost limits
Delivery
Agents go live one at a time, on request first, then on a schedule once you trust their work. Each is tested on your real tasks before it touches anything live.
- Tested on your real work
- On request before scheduled
- One agent at a time
- Instructions tuned from feedback
The process
Seven phases, first agent to full team
Durations are typical, not promises: the number of agents and the systems they connect to move them most. Discovery gives you a version of this table with your own numbers in it.
| Phase | Focus | What you get | Typical |
|---|---|---|---|
| 1. Discovery | Where your hours go, what can be handed over | Work inventory, shortlist of agents | 1–2 weeks |
| 2. Agent design | Roles, tools, limits, who approves | A job description for each agent | 1 week |
| 3. Build & ground | Agents, chief of staff, your knowledge base | Working agents on a private link | 2–5 weeks |
| 4. Connect | Email, calendar, CRM and the tools they need | Integration map, tool permissions | Overlaps build |
| 5. Test | Real tasks, awkward cases, attempts to push past limits | Test log, fixes, sign-off per agent | 1–2 weeks |
| 6. Launch | First agent live, approvals queue in daily use | Live agent, monitoring, training | A few days |
| 7. Grow | More agents, scheduled checks, tuned instructions | Regular review, roadmap | Ongoing |
What we build
Agents with a real job
Chief of staff
Takes a request in plain English, splits it into tasks and hands each to the right specialist, then brings the results back together.
Executive assistant
Prepares your morning brief and evening summary, drafts replies and keeps track of what's waiting on you.
Estimator
Turns notes, measurements or a voice memo into a priced draft quote from your own price book, ready for you to check.
Compliance
Watches certificates, renewals and deadlines, and raises the task and the reminder before anything lapses.
Marketing
Plans and drafts posts from your real work, watches what performs, and suggests what to post next.
Accounts & chasers
Spots overdue invoices and unanswered enquiries, and drafts a polite chaser for you to approve.
These are examples. Your agents are designed around your business: a property firm might want a lettings agent, a training company a bookings agent.
Why Digenixa
Agents you can actually trust with your business
- Approval first: agents prepare, people approve. Nothing customer-facing goes out on its own.
- Every action logged: you can always see what an agent did, when, and why.
- Only the tools they need: each agent gets the narrowest access its job allows.
- Working from your facts: grounded in your own content, not the internet's best guess.
- Built to keep going: rules-based fallbacks and spending limits, so a bad day for the AI service isn't a bad day for you.
Handover
What you actually walk away with
A project ends properly or it doesn't end at all. This is what "finished" means with us.
You receive
- Your agents, live
- A written job description for each
- The approvals queue and action log
- Connections to the tools they use
- Training for whoever approves their work
- A runbook, including fallback mode
How it's delivered
- Built from your real workload
- Tested on your real tasks
- One agent at a time
- On request before scheduled
- Close support after launch
- Instructions tuned from your feedback
How we measure it
- Hours of work taken off your team
- Drafts approved versus rewritten
- Renewals and chasers that no longer slip
- Time from request to ready
- AI usage costs against your limit
- Anything an agent got wrong, and the fix
Commercials
Priced so the risk sits with us
Every project is quoted individually, but the shape is always the same.
Discovery
Fixed fee. You keep the work inventory and agent designs whether or not you go ahead.
Build
A fixed price for the core and each agent priced on its own, so you add agents as they earn their place.
Run
Monthly hosting, monitoring and tuning, with AI usage costs shown plainly and capped.
Changes are normal: you'll learn things partway through that you couldn't have known at the start. Each one gets a short written note on cost, time and knock-on effects, and nothing starts until you approve it.
Straight answers
What clients ask before they commit
Will an agent ever email a customer on its own?
Not unless you decide it should. By default everything customer-facing goes to your approvals queue first. Some low-risk internal jobs, like creating a reminder task, can run on their own if you choose.
How is this different from a chatbot?
A chatbot talks to your customers. Agents work behind the scenes for your team, preparing quotes, chasing renewals and drafting replies for a person to approve.
What stops an agent doing something it shouldn't?
Each agent only has the tools its job needs, works within written limits, and logs everything it does. Anything going out passes through approval.
What happens if the AI service is down?
Agents fall back to rules-based behaviour, and your approvals queue and data are unaffected. Nothing is lost while it's unavailable.
How much will the AI cost to run?
Usage is measured and capped, and shown plainly in your monthly costs. Agents that run on a schedule are sized so there are no surprise bills.
Can we start with just one agent?
Yes, and we'd recommend it. Prove one agent on real work, then add the next.
Find the work worth handing over
Book a free demo. We'll show you agents at work and help you spot the first job yours could take off your plate.
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