Automation for business operations
We build agents that sort requests, prepare documents, and update records, with people approving the steps that matter. Your team gets more time for customers, difficult decisions, and work that keeps getting pushed aside.
Where agents can help
A useful first project has a repeatable input, a clear result, and someone who knows whether it was done correctly. Use these examples to identify a task worth testing.
The agent reads a shared inbox, identifies each request, gathers the relevant records, and drafts a response or routes it to the right person.
Your teamHandles sensitive conversations, unusual requests, and commitments to customers.
MeasureHandling time, correct routing, and reopened requests.
The agent extracts fields, compares them with an order or record, flags missing information, and prepares an entry for approval.
Your teamResolves mismatches and approves payments or other consequential changes.
MeasureReview minutes, field accuracy, and correction rates.
The agent summarizes a call, drafts a follow-up, and prepares CRM updates from the conversation.
Your teamOwns the relationship, confirms promises, and approves prices and proposals.
MeasureAdmin time per opportunity and accuracy of saved records.
The agent pulls approved data, assembles the regular report, and flags changes that need an explanation.
Your teamChecks the numbers, investigates causes, and decides what to do next.
MeasurePreparation time, reconciled totals, and corrections after delivery.
The agent searches an approved document collection, collects source passages, and drafts a comparison for a reviewer.
Your teamWeighs conflicting evidence, verifies claims, and makes the recommendation.
MeasureReview time, source coverage, and unsupported claims.
The agent moves approved records, checks whether each update succeeded, and queues incomplete work for follow-up.
Your teamResolves exceptions and decides when a process or rule needs to change.
MeasureCompleted updates, duplicate records, and time spent on exceptions.
Build around your people
A team can use the time it gets back to serve more customers, clear a backlog, improve quality, or take on work it never had time to do.
The people doing the job know the exceptions. Involve them in choosing the task, testing the agent, and deciding what deserves their attention. Give them training and time to learn the new process.
Be specific about what changes: who reviews a draft, who approves an action, and who fixes a failed run. More output only helps if employees can trust and use it.
See what freed time could be worthWhat 10× and 100× output means
Large gains can make sense for a narrow, repetitive step. They do not mean every employee will do 10 or 100 times as much useful work.
If preparing and checking an accepted record falls from 20 human minutes to 2, the same human time can cover ten times as many records.
If a batch once needed 100 human minutes and now needs 1, including its share of review and corrections, that step uses one hundredth of the human time.
Illustrative arithmetic, not Permadyn results or promised performance. A 100× case would require exceptionally low review overhead. Machine processing time, downstream work, demand, and quality can still limit completed output.
For perspective, a published study of 5,172 customer-support agents found a 15% average increase in issues resolved per hour with AI assistance, with substantial differences across workers. That is one setting, not a forecast for your business. Read the study
Automation in practice
An agent can produce a convincing answer and still update the wrong record. We build and test the connections, permissions, approvals, and recovery steps alongside the model.
Fixed rules suit fixed steps. Agents are useful when a step involves interpreting varied messages or documents. A workflow can use both.
A missing attachment, a changed screen, or a conflicting record may require a person. Include that work in the average handling time.
We give the agent only the records and actions it needs, require approval where appropriate, and keep a history of changes.
Models, business rules, and connected software change. Agree up front who handles errors, updates, and costs, and who decides to pause the automation.
Try your own numbers
Estimate the effect of automating one recurring workflow. Freed time has value even when payroll stays the same, so the calculator shows it separately from cash savings.
Illustrative inputs, not a quote or a measured customer result. Your entries stay on this page and are not sent to us.
View current estimateCount completed items, such as invoices or requests.
People’s working time, including checks and corrections.
Leave out cases that must stay entirely manual.
Average time people still spend per task after automation, across all runs, including review, exceptions, and rework.
Staff time for monitoring and upkeep, beyond individual tasks.
Wages plus benefits and other employment costs.
Model usage, hosting, licenses, and outside support. Don’t repeat staff time already counted above.
Development, integration, testing, training, and rollout.
200 to 128 human hours/month
At the same task volume, including oversight.
Time freed can go toward customer work, difficult cases, or a backlog. Its dollar value is capacity, not money removed from payroll.
Estimated spending reduction: $0/month, less $500/month in ongoing costs. Negative cash impact means extra spending.
Cash payback: Not reached under these assumptions.
Assumes steady volume and performance for 12 months. Excludes rollout delays, taxes, financing, and unmeasured revenue or quality gains. Any added human work is shown above. If it requires extra paid hours, add that expense to ongoing costs.
Suitable tasks = tasks per month × percentage suitable for the agent. Human time after automation = current time for the tasks that stay manual + remaining human time for suitable tasks + extra oversight. Hours freed = current human time − human time after automation.
Capacity value = hours freed × loaded labor cost. Spending reduction = positive capacity value × the share of freed time that reduces spending. Net monthly cash impact = spending reduction − ongoing costs. First-year cash impact = 12 × net monthly cash impact − setup cost. Cash payback = setup cost ÷ positive net monthly cash impact.
The estimate does not assume that freed time creates new revenue or reduces headcount. Before making a spending decision, replace these inputs with averages observed in a trial, including failures.
From idea to daily use
We collect representative examples with your team and record volume, handling time, errors, and the exceptions employees already manage.
We build a small version and compare its results with the current process, including the review it needs. It starts with drafts or read-only access where appropriate.
We connect the approved actions, train the people who will use it, and set up monitoring, support, and a fallback.
We compare completed work, quality, human time, and total costs with the old process. We expand only when the results justify it.
A group of agents, each assigned to specific tasks, with defined access and people responsible for their work. The useful questions are which tasks they complete reliably, how much review they need, and what happens when they cannot finish.
No. A fixed rule, scheduled script, or ordinary API integration is often simpler when the steps are known. We use a model where interpreting a document, message, or changing situation adds value. The rest can remain conventional software.
Yes, within an agreed scope. A routine internal update might run automatically after testing. Payments, external commitments, access changes, and other consequential actions can require approval. Those limits belong in the software, not just in the prompt.
A person handles it, using a record of what the agent did. We build in that record and a safe way to stop or retry, and we agree with you who handles exceptions. Before giving an agent more authority, we test missing data, conflicting instructions, denied access, failed connections, and duplicate requests.
Often, yes. It depends on the APIs, permissions, and data each system offers, so we inspect those first. Browser automation may work when an API is missing, but it needs extra testing and upkeep when screens change. Some systems limit what can be automated.
By testing a small version against the current process. We measure the current work, run the small version on representative cases, and compare accepted results. The comparison includes review, failures, integration work, staff training, model usage, hosting, and maintenance. If the benefit does not cover the effort, keep the existing process or simplify it first.
Tell us what comes in, what needs to happen, and where your team gets stuck. We’ll tell you whether an agent, a simpler automation, or a process change fits best.