AI Transformation · Intelligent Automation
Rules and bots handle the predictable work. Agents read the documents, resolve the exceptions and draft the next step, and a person approves what matters. We map your processes, automate them end to end and measure the time and errors saved.
Three layers of automation
Built on n8n, Power Automate, Zoho Flow, Make or your RPA platform
Written for
COOs, CFOs, CIOs and shared-services leaders carrying high-volume manual work
The question you came with
Which of our manual processes should we automate first, and where do agents fit?
Part of Enterprise AI Transformation
Where the work changes. Rules and bots take the routine steps, and agents take the exceptions, each with a person approving what matters.
See the whole programmeIf two of these are true, the rest of this page is about you.
What it costsSlow cycle times, errors and staff doing copy-paste.
What changesDocuments read and extracted automatically, with a person checking only the low-confidence fields.
Agentic OS · ContextWhat it costsNobody knows where a request is, and audit cannot see who approved what.
What changesApproval workflows with rules, deadlines, e-signature and a full trail.
Agentic OS · FlowWhat it costsAn RPA estate that needs more upkeep than it saves.
What changesAPIs where they exist, resilient bots where they do not, and monitoring on both.
Agentic OS · LoopWhat it costsThe exceptions take most of the time.
What changesAgents that resolve or draft the exceptions, with a person approving above a set risk.
Agentic OS · AgentsMost processes need all three. We use the simplest one that works for each step.
Routing, approvals, notifications and system updates that follow clear rules.
Data pulled from documents and entered into systems, including old ones without APIs.
The cases rules cannot decide: an agent investigates, drafts a resolution and asks a person to approve.
Every step, decision and approval recorded against the case, ready for audit.
The capability on the left, what your team would notice on the right.
Where time actually goes, from system logs rather than workshops, and which processes are worth automating first.
Approvals, onboarding, procurement and KYC flows with business rules and e-signature.
Invoices, contracts, claims and forms read with OCR and language models, checked against your rules.
Bots for systems without APIs, built, monitored and maintained as a managed service, so they keep working when screens change.
Invoice matching, reconciliation, payroll inputs and expense claims, with exceptions routed to the right person.
Tickets classified and routed, common IT requests resolved automatically, and a self-service assistant in Teams or the web.
Evidence collected as work happens, and regulatory reports produced from the same data.
The same four steps whatever we build. The first one is small, fixed-fee and useful on its own.
Fixed scope, a set timeline and a deliverable you keep. The quickest way to start.
Invoices read, matched and posted automatically, with exceptions resolved or drafted by an agent
The problem. Invoices are still keyed in by hand, matching takes days, and month-end reconciliation depends on a few people.
Measure volume, cycle time and error rate, and write down matching tolerances and approval limits with finance.
Invoices extracted with OCR and language models, matched to purchase orders and receipts in your ERP.
Mismatches investigated by an agent that drafts the resolution or supplier query for a person to approve.
The workflow switches over, with reconciliation reports and a results report against the baseline.
CFO or financial controller, and internal audit for the controls
ERP access, sample invoices, and a finance owner for weekly review
Common IT requests resolved automatically, in Teams, ServiceNow or the web
The problem. Password resets, access requests and how-to questions fill the queue, and the team has little time for real problems.
Ticket data analysed to find the requests that are frequent, simple and safe to automate.
Self-service assistant and automated fixes for the chosen requests, with approvals where access is involved.
A pilot group uses it for real requests, and gaps in answers and actions are fixed.
Live for all staff in Teams or your service portal, with deflection and resolution reported weekly.
CIO or IT service manager, and the CISO for access changes
Ticket history, admin access to the service desk, and a pilot group
A fact-based map of where time goes, and a ranked automation and agent roadmap
The problem. Automation plans are built from workshops and opinions, so the biggest wins are often missed.
Event logs extracted from your ERP, CRM, ticketing or workflow systems for two or three processes.
The real process mapped from the data: variants, delays, rework and handoffs.
Steps scored for automation, document processing or agents, with time and cost at stake.
A ranked roadmap with the first builds, expected savings and the foundations they need.
COO or process owner, with finance for the business case
Read access to system logs, and an hour with each process owner
Claims checked before submission, denials analysed and appeals drafted, with a person approving
The problem. Claims are denied for missing documents, codes or authorisations, and staff rework the same claims every month.
Denial rates measured by payer and reason, and payer rules and your coding policies loaded.
Each claim checked against the record and payer rules, with missing documents, codes or authorisations flagged to the coder.
Denials classified by root cause, and appeals drafted with evidence from the record for the billing team to approve.
Live for the chosen payers, with denial rate, rework and days to payment reported against the baseline.
CFO or revenue cycle lead, with compliance for patient data
Claims and denial history, payer rules, and access to billing and EMR systems
Not sure where to start? Begin with the AI Transformation Review: two to three weeks, $1,500, credited to month one.
Automation follows rules written in advance. Agents handle variation, such as an unusual invoice or a vague request, and decide the next step within limits. Most processes use both.
No. We review your bots, keep the ones that work, replace fragile ones with APIs where possible, and add agents for the exceptions.
n8n, Power Automate, Zoho Flow, Make and the major RPA platforms, chosen to fit your stack and licences.
Each process gets a baseline for time, volume and error rate before we start, and a monthly report after go-live.
Where Intelligent Automation fits your industry, what to read next, and the tools involved.
Start with a fixed-fee AI transformation review. We map your systems, data and teams against the six layers of Pegasus Agentic OS and name the first workflows to hand to agents. You keep the findings whether or not you work with us.