AmuraAMURA Software
Integration · SAP Business One

AI on top of SAP Business One without breaking the close.

Order extraction into the ERP, 3-way match for delivery notes and invoices, sales agents that read Business Partner history — always with idempotent writes, validation against the catalogue and full respect for B1 User Authorizations.

What we solve

B1 is the source of truth and you don’t touch it lightly.

SAP Business One holds the inventory, the catalogue, the price lists and the accounting. An AI that writes without understanding the Business Partner, Item and marketing document model breaks the close, inflates stock or duplicates an order on a timeout. Anything that happens in B1 ends up on the balance sheet — and that is audited by the tax authority, not by a dashboard.

We work by the rule of reading a lot and writing little — and only when the operation has been validated against the catalogue, the active price lists and the User Authorizations of the user triggering it. Every write carries an idempotency key, a dry-run mode for review before commit, and an auditable log. The test company exists for a reason: that is where we validate the flow before touching production.

Use cases with this tool

What we build on top of your instance.

Orders

Order extraction into B1 with validation

PDF, email or Excel from the customer — the agent extracts lines, cross-checks them against Items and the Business Partner’s active price list, and creates the Sales Order in B1 via Service Layer. Anything that doesn’t match lands in a queue for review; the agent doesn’t make codes up.

0 orders written without a match
AP

3-way match (PO / GR / Invoice)

Reads the purchase order, the goods receipt and the supplier invoice, reconciles them at the line and quantity level, and flags deviations. Only what matches automatically is proposed for posting — the rest goes to the reviewer with the reason.

Line-level 3-way match
Sales

Sales agent over Business Partner

Reads order history, applied price lists, payment terms and customer rotation directly from B1 and prepares a draft quote with real product, price and lead time. The sales rep reviews and signs off — the agent doesn’t set off-policy prices.

Quote in < 5 min
Stock

Stock monitoring by SKU and warehouse

Watches Item levels per Warehouse, cross-references historical rotation and supplier lead time, and proposes replenishment — the proposal stays as a draft so the purchasing lead can convert it into a Purchase Order if they agree.

Alerts per warehouse and SKU
Analytics

Analytical assistant over B1 Analytics

Ask in natural language about sales, margins, rotation or receivables — the agent generates the query, runs it against HANA or MSSQL and returns the answer citing the exact SQL. If it isn’t sure, it says so and doesn’t invent the figure.

Cites the SQL query
How we wire it up

How we wire it into B1 with no surprises.

Service Layer as the preferred path, DI API only when a legacy operation requires it. We validate in the test company, respect user authorizations and leave a trace of every operation.
  • 01

    Service Layer (REST) + DI API when needed

    Service Layer is the standard path for Sales Orders, Business Partners, Items and most marketing documents. For operations only exposed by DI API (some legacy or partner-customised action) we run DI through a dedicated service, never mixed into the same agent process.

  • 02

    User Authorizations respected

    The agent acts as a B1 user you authorize the same way you would a person — no permission bypass, no superuser. If the user can’t create a Credit Memo, neither can the agent. The ERP owner audits that, not us.

  • 03

    Business Partner and Item integrity

    Before writing, the connector resolves the CardCode of the Business Partner and the ItemCode against the real catalogue. We don’t auto-create new customers or items by default: anything that doesn’t resolve lands in a supervised queue. We work with messy master data, but we don’t silently fix it.

  • 04

    Idempotency via UDF or external reference

    Every write carries a unique key that we persist either in a document UDF or in an auxiliary table. If the agent retries on a timeout, we check the key before executing and the operation is applied exactly once — no duplicate orders, no double invoices.

  • 05

    HANA or MSSQL, sandbox first

    We support both engines — semantic reports differ between HANA and MSSQL and we account for that. Any new flow is tested first against a test company that mirrors your real UDFs and authorizations before touching production.

Frequently asked

What clients ask us

  • 01

    Do you work with HANA or MSSQL?

    Both. The orchestration layer is the same; what changes is the analytic query dialect and a few Service Layer details. If you’re on HANA we also expose the semantic views; if you’re on MSSQL we work with the equivalent views and stored procedures. We confirm it during initial discovery.

  • 02

    How do you avoid duplicate orders if the agent retries?

    Every write carries a unique idempotency key that we store in a document UDF or an external table. Before creating a Sales Order, the connector checks that key; if it already exists, it returns the original document without writing again. A network timeout does not produce a duplicate order.

  • 03

    Do you touch our existing UDFs or SDK add-ons?

    Not by default. We read your UDFs if they’re part of the model (for example, an external key or a process flag) and we only write to UDFs you explicitly authorize. Any SDK add-on you already have keeps working — the agent operates above the Service Layer, it doesn’t compete with it.

  • 04

    What happens when an incoming document doesn’t match the catalogue?

    It lands in a review queue with the reason: unresolved ItemCode, unknown CardCode, price out of range, inconsistent quantity. The owner sees it, decides whether to create the item, assign manually or reject, and the agent learns from the pattern for similar cases. We never write to the ERP with a made-up code.

Trust

Safe, traceable AI,
enterprise-ready.

We design for privacy from the start, human control, traceability, usage limits, permissioning and documentation. For sensitive processes, we help assess risk and applicable obligations under GDPR and the EU AI Act.

  • 01We never train models on your data without explicit authorization.
  • 02Human review built-in for processes where risk demands it.
  • 03Traceability: prompts, sources, permissions, errors and metrics — documented.
  • 04Privacy, security and control integrated from day one.
  • 05Solutions engineered to be maintained, audited and improved over time.
GDPREU AI ActAEPDISO 27001 readyEU data residency
Personal diagnosis

We work with
few clients.

Every engagement is led personally by one of the partners. If there's a fit, you get a personal first read of your case within one business day — not a canned demo.

How we work
  1. 01Tell us which process eats your time
  2. 02Personal reply within one business day
  3. 0320-minute call — no demo, no pitch
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