The back office runs on repetitive work that AI is finally good enough to do.
Most back offices are held together by manual effort. Someone keys invoice data into the finance system. Someone reads a supplier document and copies fields into a spreadsheet. Someone reconciles two reports that never quite match. The work is necessary, repetitive, and expensive, and it scales only by hiring.
AI changed what is automatable. Tasks that need reading, classifying, extracting, or matching, the work that defeated traditional rule-based automation, are now within reach. Document understanding, structured extraction, reconciliation, triage, and routing can run with AI in the loop, with audit trails and human review at the steps that need them.
That is the work we target. We identify a bounded back-office task, define the baseline and review gates, integrate the automation with your finance and operations systems, and measure it against agreed acceptance criteria before expansion.
AI across the back-office tasks that drain time
Repetitive, language-heavy, judgement-light tasks that can be measured against a real baseline and integrated with your stack.
Document processing and data entry
Invoices, purchase orders, contracts, forms, and statements read and extracted into your systems. AI data entry automation that replaces manual keying, with a reviewer queue for low-confidence cases.
Finance and accounting operations
Invoice processing, reconciliation, expense classification, supplier onboarding, and anomaly review. The control design specifies which inputs, outputs, confidence signals, approvals, and exceptions must be logged.
Inbox and request triage
Inbound email, tickets, and internal requests classified, prioritised, and routed automatically. Draft responses prepared for the repetitive cases, escalation preserved for the rest.
Reporting and data consolidation
Pulling figures from multiple systems, reconciling mismatches, and assembling the recurring reports your team rebuilds by hand every week or month.
Records, compliance, and admin
Filing, tagging, status updates, and record-keeping across CRM, ERP, and internal tools. The administrative glue work that nobody owns and everybody does.
Integration with your back-office stack
Wiring AI into the systems you already run. Xero, QuickBooks, Sage, NetSuite, Salesforce, HubSpot, and internal databases. We automate inside your stack, not alongside it.
Find it, build it, roll it out
Productized phases with named deliverables and exit ramps. Timing is confirmed after workflow, integration, document, and review requirements are understood.
Published package window: one to two weeks. We map workflows, score candidates against time, complexity, evidence, and risk, and produce a phased recommendation. The output is a testable business case, not a guaranteed payback period.
Published package window: four to eight weeks for a suitably bounded workflow. The scope defines integration, evaluation against representative documents, reviewer queues, and decision logging; complexity can extend the schedule.
Scope-dependent rollout and stabilisation alongside your team, with quality and exception monitoring, alert thresholds, runbook review, and comparison with the pre-automation baseline.
Full handover with documented architecture and runbooks, or a retainer where we automate the next task in the queue while your team learns the patterns.
Less manual work, measured
The engagement scope names the working automation, release gates, and operational artifacts your team must accept before production rollout.
Back-office automation that holds up under audit
AI-first delivery, productized engagements, and a team built around automation that finance and operations can actually trust.
Accuracy you can measure
We baseline your current process in Discovery and measure the automation against it. Extraction accuracy, exception rate, and time saved are tracked, not assumed. You see the numbers before and after.
Audit trails by default
Logging requirements are defined at the decision level: inputs, model output, confidence signals, outcome, and human review where required. The design is tested against your audit and operational needs.
Built into your systems
We integrate with the finance and operations tools you already run rather than asking you to adopt a new platform. The automation feels like a capability inside your back office, not another system to maintain.
Augmentation, not just headcount cuts
Most automations take repetitive load off your team so they spend time on the work that needs judgement. We automate the tasks that are safe to automate, and keep humans on the rest.
Where to look next
Deeper detail on the engagements and approach behind this work.
Common questions
What is AI back office automation?
AI back office automation uses AI to handle the repetitive administrative work behind a business: reading and extracting documents, entering data, reconciling figures, classifying and routing requests, and maintaining records. Unlike traditional rule-based automation, AI handles tasks that involve reading, judgement, or unstructured inputs, with human review on the steps that need it.
Which back-office tasks are worth automating first?
The best first candidates are high-volume, repetitive, and language-heavy: invoice and document processing, data entry, inbox triage, and recurring report assembly. A Discovery Sprint can score your workflows against the current baseline, complexity, evidence, and risk so the first pilot has clear acceptance criteria. Workflows outside the back office, in support and wider operations, sit under AI workflow automation consulting.
How is this different from RPA?
Traditional RPA follows fixed rules and breaks when a document layout changes or an input is unstructured. AI back office automation reads and understands the content, so it handles variation that defeats rule-based bots. The two often work together: AI for the reading and judgement, deterministic automation for the structured steps.
Will we lose control or auditability?
No. Audit trails are part of every automation we build. Each automated decision is logged with its inputs and output, and reviewer queues catch low-confidence cases before they ship. Finance and operations keep full visibility and control over what the automation does.
Does AI back office automation work for small businesses?
It can, when a small operation has enough repeated volume and a measurable baseline. Low volume, high exception rates, or expensive review can make automation uneconomic. The drivers behind that arithmetic, including operating and review cost, are set out in the AI product cost guide. We scope one bounded workflow first and test the business case before recommending expansion.
Do you publish pricing?
Yes. Starting figures for all three engagements are published on our pricing page, together with what moves the number. Scope still drives the final cost, so a fixed figure is agreed in writing against the agreed scope before build work starts.
Ready to reduce the manual work in your back office?
Book a free 15-minute feasibility triage. We will find the back-office tasks worth automating, estimate the time you could save, and give you an honest read on what shipping looks like.