Clear the Admin Queue. Get Paid Sooner.
AI back-office agents that match invoices, enter data once and close reconciliations, so volume grows without the admin team growing with it.
- 01Clarity on Where AI Can Create Value
- 02A Quantified Business Case
- 03A Practical Path to Implementation
What Is an AI Back-Office Agent?
It’s More Than a Script. It’s Running the Admin Process End to End.
An AI back-office agent is software that runs one defined administrative process end to end: it reads the inputs, checks them against your rules, completes the work in your systems and escalates anything outside those rules to a person.
AI back office agents differ from older back office automation because they handle variation. A rules-based script breaks when a supplier changes its invoice layout; an agent reads the new layout, checks the fields and flags what it can’t confirm. Every action is logged.
- Pick up jobs marked complete in your job system.System
- Read the job notes, timesheets and materials used.AI
- Check them against the quote and your billing rules.AI
- Raise the invoice in your accounting software.System
- Send invoices outside the rules to a person to approve.Human
- Log every action against the job.System
The result is completed work invoiced without re-keying, so jobs stop waiting for someone to find a spare hour.
The Saving Isn’t in Replacing Admin Staff. It’s in the Exceptions.
Most businesses assume the business case for AI back-office agents is a role they no longer need to fill.
In practice, the saving comes from the exceptions: the invoice without a purchase order, the claim missing a signoff, the payment that doesn’t match.
About 20% of a finance unit’s record-to-report tasks are fully automatable, and nearly 50% are mostly automatable, with technology doing most of the work.
That second half is where the hours go. An agent that clears the routine items and hands a person a short, well-documented exception list returns more time than one built to remove the person entirely. It is also where the cash waits: the invoice on hold, the claim sent back, the job nobody billed.
Your People Should Be Focused on Work
That Moves Your Business Forward.
As businesses grow, operational complexity grows with them.
More customers mean more enquiries, more documents, more transactions, more follow-ups, and more coordination between teams and systems.
Much of this work is necessary. But not all of it requires a person to perform every step manually.
Your team may be spending valuable time on:
- Manually entering information across multiple systems.
- Reviewing documents and extracting relevant data.
- Responding to repetitive customer enquiries.
- Qualifying leads and coordinating follow-ups.
- Chasing approvals, information, and outstanding tasks.
- Reconciling records and preparing reports.
- Moving work between departments and software platforms.
Individually, these activities may seem manageable. Collectively, they create operating costs, delays, administrative bottlenecks, and constraints on growth.
The opportunity is not simply to do the same work faster. It is to redesign how that work gets done.
Where AI Back-Office Agents Create Value
AI back-office agents put AI to work inside the back-office processes your business already runs.
They connect the systems a process already runs through, such as your CRM, accounting software and inbox, then use AI to read inputs, decide the next step and act, so a repeatable process runs from start to finish.
- 01Choosing the process
- 02Integrating your systems
- 03Setting guardrails
- 04Measuring the result
- 05Running it in production after go-live
What’s Included
- Workflow mapping, with every hand-off timed and counted
- Integration build across your systems via APIs
- AI steps for reading, sorting and drafting
- Exception routing to the right person
- Monitoring and logs for every automated step
- Handover documentation your team can use
Which Tools Can Be Connected?
We Use n8n Automation to
Connect Your Existing Stack
Any tool with an API or a ready-made connector can be connected, which covers most CRM, finance, field-service and design platforms. We build in n8n, and write custom API connections where a connector doesn’t exist. n8n can run on infrastructure you control or in the cloud, depending on where your data needs to stay.
Traditional Automation vs AI Back-Office Agents
From Rule-Based Automation to Intelligent Execution.
Traditional automation is effective for predictable, structured tasks. AI back-office agents extend those capabilities to processes involving documents, language, variable inputs, and decisions within defined parameters.
The distinction is not that AI removes the need for rules or people. It expands what can be automated, while introducing the controls needed to operate reliably.
What AI Back-Office Agents Change in the Numbers
The question is not whether an agent can do the task. It is which queue costs you most in hours, errors and days to cash. Three capabilities have become practical for AI finance automation in the past two years:
Three-way matching across formats.
Agents can now match a supplier invoice to its purchase order and delivery docket and flag variances before anyone opens the email. Next: approval runs that close the same day.
MetricTouch time per invoice
Evidence checks before submission.
An agent confirms every required document is present before a claim or compliance pack goes out. Next: rejections become rare.
MetricRework rate
Cross-system data entry.
One entry flows to CRM, job management and accounting. Next: a faster month-end close.
MetricRekeying errors
The commercial question is simple:
What would it mean for your business if repetitive work took less time, processes moved faster, and your existing team could handle more volume?
That is the value we aim to quantify before recommending an automation.
How Much Is Manual Work Really Costing You?
A few minutes of repetitive work can add up to thousands of dollars in annual operating costs. Calculate the cost of manual processing in your business.
3 people on the process × $90,000 fully loaded cost per person = $270,000 a year.
If repetitive, manual work takes up 25% of their week, that equates to $67,500 a year—around 28 hours of work every week, based on a 38-hour week.
That’s the potential cost of repetitive work in just one process, before accounting for delays, errors, or the opportunity cost of time your team could spend on higher-value work.
Put your own numbers into the calculator below to see what manual work could be costing your business.
Where Back-Office Automation Goes Wrong
- Automating only the happy path. Exceptions pile up unowned. Hidden cost: staff review time. The fixDesign the exception route first.
- Skipping the data clean-up. Duplicate supplier records mean the agent repeats your errors faster. The fixClean master data before go-live.
- Ignoring run costs. Per-task platform and model fees grow with volume. The fixModel them at peak, not pilot, volume.
- No baseline. Without a starting cost per item, nobody can prove the saving. The fixMeasure before building.The first call starts that baseline.
What Back-Office Tasks Can AI Agents Do?
AI admin automation suits high-volume, rule-based work with clear evidence.
Billing & Cash
Find completed jobs that were never invoiced and get them billed.
- Completed-job checks
- Unbilled work flagged
- Invoice drafts
- Payment reminders
- Credit note requests
- Days-to-invoice reporting
Accounts Payable
Match supplier invoices to purchase orders and flag the variances.
- Invoice data capture
- Invoice-to-PO matching
- Variance flags
- Approval routing
- Duplicate invoice checks
- Payment run preparation
Reconciliation & Data
Keep one record in sync across CRM, job management and accounting.
- Bank matching
- Payment matching
- Supplier statement matching
- Month-end unmatched lists
- CRM-to-accounting sync
- Rekeying error checks
Compliance & Claims
Assemble and check evidence packs before anything is lodged, including for renewable energy businesses.
- Evidence pack assembly
- Missing-document checks
- Sign-off tracking
- STC claim packs
- Connection applications
- Rework and rejection tracking
Back-office work is the easiest to measure. Every task has a count, a cycle time and an error rate before you start.
Described Example: An Energy Claims Workflow
This is a described workflow, not a case study. For a solar installer, the agent assembles each STC claim and connection application pack from the job record, checks every required document and signoff is present, and routes anything missing to the person who can fix it before lodgement. The numbers it is judged on are first-time acceptance and days to certificate cash. See AI for Solar & BESS Installers
- Job record
- Claim pack assembled
- Documents + sign-offs checked
- Gaps routed to owner
- Claim lodged
Judged on · first-time acceptance + days to cash
From Automation Opportunity to Measurable Business Outcome.
We begin by understanding your business, identifying where work is being lost to manual effort, and establishing whether automation makes commercial sense.
Step 1: Discover & Diagnose
Understand how your processes operate today.
We map workflows, identify repetitive activities, examine existing systems, and establish a baseline for time, cost, volume, and performance.
Step 2: Assess & Prioritise
Identify where automation can create the greatest economic value.
We assess each opportunity against potential value, technical feasibility, process readiness, implementation effort, and risk.
Step 3: Design the Future-State Workflow
Redesign the process before automating it.
We define workflow logic, AI agent responsibilities, system integrations, decision boundaries, human approvals, exception handling, and performance measures.
Step 4: Build & Integrate
Develop the automation within your existing technology environment.
We configure AI agents, connect relevant applications, implement business rules, and establish the controls required for reliable execution.
Step 5: Test & Validate
Prove performance before expanding autonomy.
We test against representative scenarios, measure accuracy and exception rates, validate integrations, and run supervised pilots before production release.
Step 6: Deploy, Manage & Optimise
Keep automation performing after launch.
We monitor execution, manage exceptions, measure outcomes, identify performance drift, and continuously improve the workflow.
What We Need From Your Team
- One process owner
- Access to the tools involved (your team sets up the credentials)
- A sample of recent jobs to test against
Commercial Thinking. Practical Implementation. Measurable Outcomes.
We combine commercial advisory with hands-on AI automation delivery. We learn your processes, priorities and operating constraints first, then design, build and run automation that works reliably in production.
We Start With Business Value
We identify the operational problem and establish the economic case before recommending a solution.
We Design the Process, Not Just the Technology
We redesign workflows around how your business needs to operate, including people, systems, approvals, and exceptions.
We Implement Across Your Existing Systems
We connect AI agents and automation to your business applications, rather than treating technology replacement as the default answer.
We Build for Production
We test, validate, and deploy against agreed performance criteria, with human oversight and operational controls built in.
We Stay Accountable for Performance
We support ongoing monitoring, exception management, and optimisation so the automation continues to deliver value beyond implementation.
Built for the Long Run
We don’t just deploy AI automations. We help businesses continuously improve how they operate.
AI automation designed by operators.
Governed by humans.
Measured by outcomes.
Case study title
One-paragraph summary: problem, what was built, the measured result.
AI Back-Office Agents: Common Questions
01Can AI automate administrative tasks?
Yes. AI automates administrative tasks that are high-volume and rule-based, such as invoice matching, data entry, reconciliation and document checks. Tasks that need judgement, accredited signoff or negotiation stay with people, and the agent routes those to them.
02How long does a pilot take?
Timing depends on how many systems the agent connects to and how clean the data is. We give you a timeline for your process at the end of step 2, once the shortlist is scored and the first process chosen.
03Is our financial data secure?
The agent works only with the access you grant. Every read, check and decision is logged against the record, and approval points stop it acting on items above your thresholds.
04What happens to our admin staff?
Administrative automation usually changes the job rather than removes it. Staff stop rekeying and start reviewing exceptions, which is better use of their knowledge.
05How much can AI back-office automation save?
It depends on your cost per item today. Processing a PDF invoice is estimated to cost $27.67 and an e-invoice $9.18, across sender and receiver (Deloitte Access Economics 2016 estimates, cited by the ATO).
Illustrative example. Assumptions: 1,500 invoices a month × 8 minutes each = 200 hours. If an agent clears 70% straight through and staff still spend 8 minutes on each exception, hours drop to 60: 140 hours a month back, before platform and run costs.
A more conservative case: if only 50% clear straight through and staff spend 1 minute reviewing each approved item, hours drop to 112.5 (100 on exceptions, 12.5 on review): 87.5 hours a month back.
The second number is days to invoice. We measure how long completed work waits before it is billed, because that delay is cash you have earned but cannot use.
Hours released are not cash saved until they avoid a hire, remove overtime or move to revenue work. Find your own number.
06What does it cost to run?
Two parts: platform and model fees, which grow with volume, and the time spent reviewing exceptions and maintaining the rules. We model both at your peak volume, not pilot volume, before you commit, and report them monthly against the saving.
07What happens when the agent gets it wrong?
Items the agent can’t confirm go to a person rather than through. Approval thresholds stop it acting on anything above your limits, every action is logged so an error can be traced and corrected, and each error found becomes a new rule or exception route.
08Do we need to change our accounting software?
No. The agent works inside the systems you already use, such as your accounting platform, job management and CRM, with only the access you grant. Where your platform already captures bills or receives Peppol e-invoices, we build around that rather than replace it.
09Who works the exceptions?
Your team, ours, or both. We name the owner of each exception type in step 3, before go-live, so nothing waits unowned. Either way, each exception arrives with its evidence attached and the reason it didn’t go through.
Still have a question? Ask us on a Discovery Call.
Book a Discovery CallFind the Back-Office Queue Costing You the Most
On the first call we walk through your longest admin queues and estimate what each costs per item, in hours, and in days to cash.
- 01Clarity on Where AI Can Create Value
- 02A Quantified Business Case
- 03A Practical Path to Implementation
- A Focus on Your Commercial Opportunity
- A Confidential, No-Obligation Conversation
- We Reply Within One Business Day