Much back-office work is reading something, deciding what it is, keying data into a system and routing it on. Traditional automation broke on anything unstructured. AI handles the reading and classifying, so automation can reach the work that used to need a person for every item.
We automate document-heavy and queue-heavy processes with AI, and keep people in charge of the exceptions and the decisions that matter.
Invoices, orders, emails, forms and tickets.
Low-confidence items routed to a person.
Built by the team that operates our BPO services.
Your data is not used to train public models, and access follows your permissions.
Six common patterns. Most processes combine two or three of them.
Invoices, purchase orders, bills of lading, claims, KYC documents and forms read, classified and extracted into structured data.
Validated against business rules and master data before posting.
Data keyed once, by the system.
Inbound emails and tickets classified, prioritised, enriched with context and routed or answered.
Standard requests resolved, the rest sent to the right person with a summary.
Queues sorted before anyone opens them.
Approval, onboarding and exception workflows where AI prepares, checks and summarises, and a person decides.
Built in Power Automate, OIC, Salesforce Flow or custom services.
Decisions made faster with the facts in front of the decider.
Existing RPA bots extended with AI for unstructured inputs, or replaced with API-based automation where systems allow.
APIs first, screen automation only where nothing else works.
Bots that break less often.
Bank, invoice, shipment and order matching with AI for fuzzy matches and explanations for mismatches.
Exceptions explained, not just flagged.
Fewer items left for month-end.
Volumes, accuracy, exceptions and savings monitored, with models retrained as documents and rules change.
Run as a managed service, alongside our BPO teams where needed.
Automation that keeps working.
How an automation project runs
Typical AI automation scope.
| Process | Inputs | Systems | Measure |
|---|---|---|---|
| Accounts payable | Invoices, statements | Oracle, Dynamics, NetSuite | Straight-through rate |
| Order entry | Emails, PDFs, EDI exceptions | ERP, CRM | Time to order |
| Logistics documents | Bills of lading, PODs, rate confirmations | TMS, ERP | Documents per hour |
| Service desk | Emails, tickets, chats | ITSM, CRM | Resolution time |
| Onboarding | Forms, IDs, contracts | HR, CRM | Cycle time |
Automation projects promise straight-through processing and then stall on the items that do not fit. Those items are where the cost and the risk sit.
We design the exception queue, confidence thresholds and human review first, then automate the routine around them. Because we run back-office operations ourselves, we know where the exceptions come from.
Automate a processScope and savings estimate follow the process baseline.
RPA follows fixed rules on structured screens. AI automation can read unstructured documents and emails, classify them and extract data, which lets automation reach work RPA could not.
It depends on document quality and variety. We measure on your samples, agree thresholds, and route anything below them to a person.
Not necessarily. Many can be extended with AI. Where systems offer APIs, we often replace screen automation with something more reliable.
Yes. Our Managed Business Services teams can handle exceptions and quality checks, so you buy the outcome rather than the software.
Oracle, Microsoft Dynamics, NetSuite, Salesforce, TMS and most systems with an API or integration layer.
A week of invoices, orders or emails is enough to estimate what automation would handle and what it would leave for people.