SAP AI Analytics for ECC and S/4HANA
Get a sovereign natural language conversational analytics system for your enterprise. Chat with SAP ERP data, contextualized with your CRM, emails, and spreadsheets to unlock access to enterprise-wide intelligence.
Trusted AI systems partner for startups to enterprise leaders
Why does SAP ERP data stay out of reach?
SAP data models are archaic and built for posting transactions. The legacy architecture means your data is locked behind technical keys, objects, extraction rules, and reporting that never leaves SAP.
Keys instead of business meaning
One purchase order can span EKKO, EKPO and EKET, keyed on codes that business users do not read.
Objects move at conversion
BSEG and COEP transform into ACDOCA, MKPF and MSEG into MATDOC, customers and vendors into Business Partner.
Extraction follows SAP's rules
Bulk access runs through endorsed routes only, so the path out of the system must be explicitly designed.
Built-in analytics stays inside SAP
Embedded reporting answer on SAP data alone. In the real-world, enterprise data lives across diverse systems. SAP reporting cannot answer queries on data that exist outside the ERP.
Queries need reports
Every user query is, essentially, a report request. Enterprises relying on SAP-based reporting are operating slower than competitors who have built an AI powered query engine.
How does GoML's Natural Language AI Analytics for SAP work?
GoML builds a two-layer system than spans your SAP instance and your other key enterprise systems. A governed data layer gives every entity one meaning across SAP and everything around it, and a natural language analytics engine to chat with SAP data.
Data governance
One view of the entities your business runs on, reconciled across SAP ERP and your other enterprise systems.
- ReadsECC, S/4HANA, BW, CRM, email, files
- Modelsorders, suppliers, materials, deliveries
- Contextdata across every system
- Reconcilescontrol totals tied to your ledger
- Writesnothing, by design
SAP conversational analytics
Enables natural language queries for enterprise users. A user question returns an answer along with the source.
- Takesnatural language query or voice
- Returnsan answer with the records behind it
- Respectseach person's existing SAP roles
- Measuresaccuracy against a tested set
- Runs inyour own environment
The data landscape assessment process
Every SAP ERP implementation is different. So, we begin every engagement with a 3-week assessment across five workstreams. You get a validated picture of your data and an implementation plan.
Data landscape
An inventory of every source that will feed the analytics: SAP modules, CRM objects, mailboxes, and documents in your environment.
You get a source-by-source inventory, with volume, refresh rates, and a map of how entities relate across systems.
Tool landscape
How each source is reached technically: SAP interfaces, CRM extraction, document access, single sign-on and read-only credentials.
You get a connectivity matrix per source, with every blocker and the approach to resolve it.
Technical architecture
Your current environment measured against the target: storage, pipeline, governance, guardrails, and the conversational engine.
You get a target architecture reviewed with your IT and security teams. Every assumption is documented.
User landscape
The people behind each use: what data they open every day, which modules they work in, where systems disagree and what they reconcile by hand.
You get a user and access map per department, with source-system roles mapped to data domains and verified by teams that own them.
Use case definition
Sample queries from each function, the expected output, data sources, and the context needed for accurate replies.
You get defined use cases signed off by their function lead, ranked by build complexity, each with a readiness verdict.
Unlock value across the enterprise: Chat with SAP data
Consider a common scenario where your ERP and CRM data do not match. Here is an illustration of how our SAP AI data analytics system will reconcile the conflict into a provable answer.
Any POs pending with delayed suppliers?
Fourteen open orders match. Eleven of them have delay notifications received in the last 28 days.
Stock for next months's production plan
We are on schedule. Two have a goods receipt booked for Thursday, and four have inbound movements scheduled for December.
Where Salesforce and billing don't match in Canada?
Nine accounts do not match. The gap traces to partial deliveries billed across two periods, and every one of them is listed with its documents.
What do you own?
A sovereign natural language data analytics system for your enterprise data that runs inside your own environment or cloud. The AI analytics system is owned by you and can be used, managed, and maintained by your own team.
A governed data layer
Modeled entities, crosswalks and control totals tied back to your records.
A read-only connection
Nothing writes back into SAP, so your system of record stays exactly as it is.
Your cloud, your environment
Data stays where your policies require, with encryption, audit and access control.
An AI-first path onward
A ranked list of AI agent use cases that you can build, now that your data landscape is fully analyzed for readiness.
Frequently asked questions
Common questions about SAP Data Analytics AI and Natural Language Analytics for SAP.
Which SAP systems does this support?
ECC 6.0, S/4HANA on-premise, S/4HANA private cloud under RISE and S/4HANA public cloud under GROW. BW and BW/4HANA are read as sources alongside them, and an estate running several of these at once is normal.
How can this help our enterprise?
Your teams get answers in seconds instead of raising a report request and waiting. Questions that cross SAP, your CRM and email come back as one reconciled answer, so the matching your teams do manually are no lomger needed.
Does anything write back into SAP?
No. The data analytics engine we build is read-only by design, so your system of record stays untouched and the analytics carry no risk of a bad posting. Write paths stay off unless you ask for them and agree the route in writing.
How is this different from SAP's own analytics?
Embedded reporting and BW access only SAP data. AI-powered SAP reporting from GoML reconciles SAP with CRM, email and spreadsheets to answer questions that span system boundaries.
We already use Tableau. How is this different?
Tableau visualizes data that someone has already modeled, and each new question needs a dashboard built for it. GoML builds the reconciled layer underneath and answers in plain language without a dashboard, and that same layer can feed your existing Tableau reports.
What happens when we convert from ECC to S/4HANA?
The mapping is designed to accommodate it. The analytics reads business entities.
Can it answer across SAP and our HubSpot?
Yes, and that is the point of the layer. Crosswalks join an order, a customer, a material or a delivery wherever it appears, so a natural language query for SAP data also reaches your CRM and other systems beside it.
Who can see what?
Each person's existing SAP and CRM roles decide which slice of the modeled layer their questions may retrieve. An answer never reaches someone who does not have source-system access.
What does a 'sovereign' natural language analytics system mean?
It runs inside your own environment or cloud, and the modeled layer, and the code belong to you. Your SAP data never leaves your boundary to reach a vendor, and your own team can operate, change and extend the system without us.
Why does this start with an assessment?
Quite simply, each SAP implementation is different. A 3-week assessment is the best way to get started on building out an AI-powered enterprise intelligence system. That's when our AI FDEs and experts understand the nature of your implementation, your systems, and your data.
What happens after the assessment?
After the assessment, you get a fully fleshed out roadmap to build the engine. Typically, the build takes 4 - 6 weeks because it is built with our proven AI Matic platform and AI Data Analytics blueprints.
Start SAP AI Analytics with an assessment
Two to three weeks on site with your SAP, CRM and function teams gives you a validated picture of your data and a costed plan. The build decision comes after that, with the numbers in hand.
3 weeks · Read-only access · Your data stays in your account
