Order to Cash
OTC Agent in Microsoft Teams
Sales and service teams ask about orders, deliveries, credit and invoices in plain English inside Teams. The answers come back from live S/4HANA data.
I'm a Senior Managing Consultant at IBM with 14+ years of SAP S/4HANA work. These days I spend most of it building AI agents that run against live ERP data. They answer the questions finance, sales and procurement teams ask every day, find revenue leakage, and act on what they find. Nothing gets written back to SAP until a person approves it.
I built these for IBM's SAP practice and for global clients in consumer goods, med-tech and manufacturing. Each one runs against a real S/4HANA system rather than mocked-up screens. Client names are left out on purpose.
Sales and service teams ask about orders, deliveries, credit and invoices in plain English inside Teams. The answers come back from live S/4HANA data.
One screen for every order, delivery and invoice. AI sorts out which orders need attention, works out how much value is at risk, and explains why each one is stuck.
Reads unstructured customer emails and purchase orders and turns them into SAP sales orders. This takes manual keying out of order entry.
Checks sales orders and invoices against the contracted price book and finds revenue leakage. It explains each gap and proposes a correction for a person to approve.
Finds revenue in open orders that could be pulled forward. It comes with a dashboard and a conversational agent that explains the reasoning behind each opportunity.
Shows margin and pricing insight for each product and customer combination, so commercial teams can price with evidence. A related customer-scoring assistant guides upsell and discount decisions.
Answers the finance desk's daily questions: Where is my payment? Why is this invoice blocked? Which customers are overdue? It grounds each answer in company policy and live accounting data.
A record-to-report proof of concept that speeds up period-end work by having an agent investigate, reconcile and explain entries.
An observability tower for supplier invoices. Five agents analyse real SAP documents for blocks, mismatches and risk, and every fix goes back to SAP only after a person approves it.
A procurement assistant that answers questions about purchase orders, suppliers and invoices for buyers and AP teams. It is published to Microsoft Teams.
Explains in plain language why an order was confirmed late or partially, by working through advanced available-to-promise (aATP) results.
A read-only audit agent on BTP for regulated (GxP) environments. It needs no custom code in SAP, which keeps the validation scope small.
Turns hundreds of manual order-to-cash test scripts into automated tests. Natural-language test steps are converted into repeatable checks.
A proof that a person signed in to Teams reaches SAP as their own SAP user. Every agent action then respects that person's own authorizations. No shared technical user is involved.
A secure microsite on SAP BTP that collects every AI accelerator above. Each guest gets a scoped, time-limited view of the demos that are relevant to them.
My entry for IBM's 2026 watsonx Challenge: four cooperating agents that score a consulting pipeline from CRM and ERP data so teams can focus on the deals most likely to win.
Most of these agents share one secure architecture. People work where they already are, the agent reasons over live data, and SAP stays clean.
Every number on screen comes from a real SAP document, so business users can trust what they see.
Agents investigate and propose. A person approves before anything changes in SAP.
Extensions live side-by-side on BTP, which keeps upgrades simple and validation scope small.
I know how order-to-cash actually runs in large companies, and I bring that to every AI build.
I co-lead the GenAI asset pipeline for the practice: I run ideation workshops, assess feasibility, and architect reusable AI agents that we deploy across clients.
I am enterprise architect for Lead-to-Cash on a global S/4HANA template for a Fortune-100 consumer goods company. I advise the design authority on clean-core standards and lead a 20+ person delivery organization.
I led solution design for a greenfield SAP implementation that replaced a mainframe serving 150,000+ customers a day. I also architected an RFID + IoT garment-tracking system and a B2B/B2C e-commerce platform. SAP recognized my design contributions to S/4HANA Fashion.
Greenfield SAP SD and GRC programs across North America and Latin America, covering EDI, e-invoicing and trade promotion.
Open to conversations about agentic AI, S/4HANA transformation and clean-core architecture.