AI Automation & RPA
Back-office work that finishes itself — the intake, the data entry, the follow-ups, the reconciliation.
In one line
Key takeaways
- AI automation combines RPA (for fixed, rules-based steps) with AI (for the steps that need reading and judgment) into one workflow.
- The best first targets are high-volume, repetitive processes: intake, data entry, invoice handling, status chasing, and reconciliation.
- A human stays in the loop on exceptions — the system handles the bulk and routes only the uncertain cases to a person.
- You own the whole workflow — no per-seat automation fees, no locked platform.
Every business runs on a layer of invisible manual work: someone rekeys an emailed order into the ERP, someone copies invoice totals into the accounting system, someone chases a supplier for a missing document, someone matches payments against statements at month-end. None of it needs a human brain, but all of it needs human hours — and those hours scale straight up with volume. The result is a team spending its day on data entry and status-chasing instead of the judgment calls only people can make. This is the work Plenaura hands off to software.
The reason this stays manual isn't that the tools don't exist — it's that most automation stops at the first messy input. Connector tools like Zapier and n8n move clean, structured data between apps beautifully, but they fall over the moment a process needs to read a scanned PDF, interpret a free-text email, or decide what to do with an exception. So the tedious middle — the reading, the judgment, the re-keying — stays with your team. Real automation has to cover both halves: the deterministic clicking and the reading-and-deciding.
Plenaura builds workflows that combine both. Robotic process automation (RPA) handles the fixed, rules-based steps — logging into a system, moving a file, updating a field — while AI handles the parts that need reading and judgment: pulling the right numbers off an invoice, classifying a request, catching a mismatch a rule would miss. A human-in-the-loop review queue sits over the top, so the system runs the confident bulk unattended and routes only genuine exceptions to a person. It's real process engineering, not a chatbot bolted onto your inbox.
The business outcome is capacity that stops scaling with headcount. The same team handles far more volume because they only touch the cases that need them, work gets done accurately around the clock instead of in business-hours batches, and the error rate on repetitive tasks drops because software doesn't get tired at 5pm. You own the entire workflow — every line of it — with no per-seat automation licences and no platform holding your process hostage. And where an off-the-shelf tool genuinely solves your problem, we'll tell you to use it.
What we can build for you
Document intake and data capture
We turn the emailed PDFs, scanned forms, and photographed documents that pile up in an inbox into clean, structured data in your systems. Document AI and LLM extraction read the unstructured input and pull the fields you actually need, so intake stops being a person typing from one screen into another.
System-to-system data entry and sync
We automate the rekeying between tools that don't talk — an order from email into the ERP, a lead from a form into the CRM, a record kept in step across two systems. RPA drives the deterministic clicks and field updates, so the same data stops being entered three times by three people.
Invoice and accounts-payable automation
We read incoming invoices, extract line items, totals, and vendor details, match them against purchase orders, and stage them for approval — no manual keying into the accounting system. Document AI handles the varied formats and layouts, while workflow orchestration moves each invoice through its steps and flags mismatches for a person.
Follow-up and status-chasing automation
We automate the polite nagging that eats a team's day — chasing a missing document, reminding a client of an overdue payment, requesting the next piece of an application. The system tracks what's outstanding, sends the right follow-up at the right time, and escalates the cases that go quiet, so nothing stalls because a person forgot to check.
Reconciliation and exception handling
We match transactions against statements, orders against deliveries, and records across systems, surfacing only the discrepancies that need a human eye. The routine matches clear themselves automatically; AI catches the near-misses a rigid rule would either wave through or wrongly reject, so month-end stops being a manual line-by-line hunt.
Approval routing with human-in-the-loop
We build the review queues and routing logic that send each item to the right person with the context already gathered — and hold the ones that need sign-off rather than acting blindly. You set the confidence threshold: the system clears the obvious cases unattended and routes the uncertain ones to a human, so scale never means silent mistakes.
Reporting and notification automation
We automate the recurring pull-and-compile work behind daily reports, alerts, and dashboards — gathering data from across your systems and delivering it where your team already looks. Workflow orchestration runs it on schedule or on a trigger, so the weekly report writes itself and the alert fires the moment a threshold is crossed, not the next time someone checks.
How we deliver it
Map where the hours actually go
We start by watching how the work really flows — the manual steps, the copy-paste, the handoffs, the waiting — and quantify where time and errors leak today. That baseline is what tells us which process is worth automating, rather than guessing from a job description or an org chart.
Pick the highest-ROI process and design the workflow
We choose the process with the clearest payback — usually something high-volume and repetitive — and design the full workflow on paper before building: which steps are fixed rules, which need reading and judgment, and where a person should stay in the loop. You approve the design and the expected impact before development starts.
Build with RPA, AI, and human-in-the-loop review
We build the deterministic steps as RPA and the reading-and-judgment steps with document AI or LLM extraction, wired together into one workflow with a review queue over the top. The system is built to run the confident cases unattended and hand exceptions to a person, with the confidence threshold set to your risk tolerance.
Integrate with your systems and test on real data
We connect the workflow into the tools you already run — ERP, CRM, accounting, helpdesk — so it acts inside your operation instead of becoming another dashboard. Then we test it against your real documents and edge cases, tuning it on the messy inputs that break demos, before it touches anything live.
Deploy, monitor, and hand over ownership
We put the workflow into production on infrastructure you control, with monitoring so you can see what it's handling, what it's escalating, and where it's uncertain. Then we hand over the full workflow and documentation — you own it outright, and your team can run and extend it without us. Work is scoped and quoted per project, on a clear timeline agreed up front.
The outcome
The repetitive work that quietly consumes your team's hours runs on its own — accurately, around the clock — with people freed for the judgment calls that actually need them.
This is for you if
- Your team spends its day rekeying data between systems that don't talk
- Invoices, forms, or documents pile up waiting for manual handling
- You've hit the ceiling of Zapier/n8n and need real reading-and-judgment logic
- You want to grow volume without growing headcount in the same proportion
What you get
- A mapped, automated workflow for a high-volume process — built to run end to end
- RPA for the deterministic steps, AI for the reading-and-judgment steps, in one system
- A human-in-the-loop review queue so exceptions get a person, not a silent failure
- Integration with the tools you already run — not another disconnected dashboard
- The full workflow handed over — you own it, with no per-seat automation fees
However we build it, you own it
AI Automation & RPA — answered
The best first target is a process that's high-volume, repetitive, and follows a recognizable pattern — intake, data entry between systems, invoice handling, follow-ups, or reconciliation. We map where your team's hours actually go and pick the one with the clearest payback, so you see real time back early rather than boiling the ocean. A focused first workflow that works and earns trust beats a sweeping rollout that stalls.
We separate the parts that change from the parts that don't, and build so the changeable parts are easy to adjust rather than hard-coded throughout. For steps that genuinely shift case to case, AI handles the reading and judgment instead of a brittle rule that breaks the moment a format changes. If a process is changing constantly because it isn't settled yet, we'll tell you honestly that it's too early to automate and worth stabilizing first.
It escalates instead of guessing. Anything the system is uncertain about is routed to a human review queue with the context already gathered, so a person handles the edge case rather than the automation silently getting it wrong. You set the confidence threshold, and as the system proves itself on your data you can widen what it handles unattended. The design goal is that scale never means silent mistakes.
No — dealing with messy, unstructured input is exactly the point. Connector tools need clean data to work; we build the layer that reads emailed PDFs, scanned forms, and free-text and turns them into structured data your systems can use. If foundational data work is needed to make a workflow reliable, we scope it honestly as part of the project rather than assuming a tidy dataset you don't have.
A person you hire adds a fixed amount of capacity, works business hours, and has to be re-hired and re-trained when they leave — and the cost scales straight up with volume. An automated workflow runs around the clock, handles the confident bulk without tiring, and lets your existing team focus on the judgment calls only people can make. It's not about replacing your team; it's about not needing to grow headcount in proportion to volume.
Yes. When a system has no API to connect to, RPA operates it the way a person would — logging in, navigating screens, reading fields, and entering data through the interface itself. That's precisely where robotic process automation earns its place, and it means old, closed, or in-house software that can't be integrated any other way can still be part of an automated workflow. We assess your specific systems up front so there are no surprises.
Related use cases
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Ready to scope it? Let's talk.
A short call, then a clear, agreed scope in writing. No obligation, and an honest no if it isn't a fit.