Most of what a business runs on a computer can be automated — anywhere information moves between people and systems by hand, on rules a person could write down. The three patterns below are common shapes we see, not a list of what we do. If your expensive process looks nothing like them, it is still worth describing.
A strong candidate usually has
Recurring volume. A measurable cost or delay. Stable inputs and outputs. Rules a person can describe. Systems we can reach. Exceptions someone can recognise. A person accountable for the process. And economics that clear the service cost.
We’ll usually say no when
The volume is too low to pay for itself. The process changes shape constantly. Nobody owns it. The inputs can’t be reached. The outcome can’t be tested. Most of the work is genuinely novel human judgment. Or the numbers don’t support managed operation.
These are illustrative patterns, not client case studies — your process gets its own map in the assessment.
Invoice and supporting-document handling
The pattern for project-based businesses.
Before. Invoices arrive by email. Staff hunt for the supporting documents. Details are checked by eye against the job or order. Exceptions get chased by phone. The results are typed into the accounting or project system. Approvals are followed up manually.
After. Documents are captured automatically on arrival. Fixed, tested rules validate the predictable fields — the same result every time. AI reads only the unstructured material, and its output passes checks before anything is written anywhere. Exceptions route to a named person instead of a pile. Approved records enter your system without retyping. Every action is logged, and Elry monitors the process as part of the managed service.
For your team: the chasing stops; the judgment calls remain theirs.
Compliance packs
Before. Every submission means gathering certificates, insurances, licences, and forms from folders, inboxes, and suppliers. Someone checks currency and completeness by hand. Expiry dates are tracked in a spreadsheet, when they’re tracked. A missing document is discovered at the worst moment.
After. The pack assembles itself from watched sources. Fixed rules check currency, completeness, and format. Expiring documents are flagged weeks ahead and chased automatically. A person reviews the assembled pack before anything is submitted. Every version is logged.
For your team: the deadline panic goes; the accountability stays visible.
Debtor and customer follow-up
Before. Overdue invoices sit in an ageing report someone has to remember to read. Follow-ups depend on who has time. The tone and timing vary by mood. Escalations happen late. Nobody can say at a glance who was contacted, when, or what they said.
After. The ageing report is read automatically on schedule. Reminders go out on fixed rules — timing, sequence, and escalation thresholds you set. AI drafts only the messages that need judgment, and a person approves anything sensitive before it leaves. Responses and promises-to-pay are logged against the account. The exceptions — disputes, hardship, silence past the threshold — route to a person.
For your team: consistent follow-up without the awkward-call lottery.
Where else this applies
Quoting and estimating. Scheduling and work allocation. Approvals and sign-offs. Employee and customer onboarding. Operational reporting. Inbound request triage. Records kept in step between systems.
Does one of these cost you real money every month? Describe it in four answers.
These patterns run in our own company too — one of our own automations, documented.