ERP Automation
The Deterministic AI Decision Layer for Your ERP
Your SOPs are the rules. Our agents follow them, and show their work.
The AI decision layer for your ERP. Driven by your SOPs, deployed in your environment, traceable end to end.
- Every action follows your approved SOP.
- Evidence, approvals, and ERP updates remain traceable.
Exceptions pile up when the answer isn’t in the ERP alone.
ERP workflows handle the clean cases. Exceptions need someone to read an email or PDF, check the SOP and match it to ERP records.
Getting data out of emails and attachments and into ERP-ready formats is where most automation breaks.
The result: queues grow, DSO rises, revenue is delayed, costs climb and SLAs slip.
- Custom ERP add-ons that break with every upgrade
- Bolt-on point products that add integration cost and complexity
- Large teams working the queue by hand, in-house or outsourced
A decision layer built from your SOPs
Karini AI agents follow your documented process step by step, within the guardrails you set. Here is how a case moves from queue to close.
- 01
Intake
Cases arrive from the ERP exception queue, a shared mailbox or another system. Agents extract the data from emails and documents into one standard format.
- 02
Classification
Agents identify which SOP applies to the case, and which rule in that SOP fits the facts.
- 03
Analysis
Agents pull the supporting evidence from the ERP through standard APIs and run the checks the SOP requires.
- 04
Decision and approval
The SOP sets the outcome and the approval level. Anything above threshold goes to a human reviewer, with the evidence and a recommendation.
- 05
ERP update and closure
Agents post the update through an approved interface. The case closes only when the SOP’s closure criteria are met.
Reach, governance, one platform.
Reach
APIs first. Screens only as a last resort.
Agents work through standard ERP APIs, so results are reliable and survive upgrades. Screen scraping breaks every time the UI changes.
OData, RFC, REST and MCP servers cover the ERP. Built-in document parsing turns emails, PDFs and scans into structured data.
What that looks like
- Reads and writes ERP data directly, not just what a screen shows.
- Cases from a shared inbox are handled like any other case.
- Where no API exists, agents can drive the screen, limited to that one task.
Four ways to tackle an exception queue.
Most teams have tried at least two of these. The queue survives because the rules end up somewhere other than the SOP the business maintains.
- Poor
- Partial
- Strong
| Dimension | Karini AI | Document capture and RPA | ERP native workflow | Custom build |
|---|---|---|---|---|
| Where the rules live | StrongIn your SOP, owned by the business. | PoorIn a bot script only its builder understands. | PartialIn ERP configuration, changed on IT’s release cycle. | PartialIn application code, owned by the team that wrote it. |
| When the policy changes | StrongUpdate the SOP. Agents follow the new version. | PoorThe bot breaks, or silently applies the old rule. | PartialA change request, a test cycle, a release. | PartialA ticket, a sprint, a deployment. |
| Access to ERP data | StrongAPI-first via OData, RFC, REST and MCP. Screens only as a fallback. | PoorOnly what the screen shows. | StrongComplete, but only inside one ERP. | PartialOnly what you paid to integrate. |
| Cases from email and attachments | StrongHandled in the same workflow, from intake to resolution. | PartialA separate capture product, and a separate queue. | PoorOut of scope. | PartialBuildable, at the cost of another project. |
| Explaining each decision | StrongThe SOP section and conditions behind every decision. | PoorA log of clicks. | PartialA workflow history, if the process was modeled. | PoorWhatever logging was specified at the time. |
| Who approves the hard cases | StrongNamed approval levels, supervisor to CFO, set by the SOP. | PoorNobody. It either ran or it failed. | PartialA configured approver, on modeled paths only. | PoorAs built, and rarely revisited. |
| Adding the next use case | StrongAnother SOP, same platform. | PoorAnother bot to build and another to maintain. | PartialAnother process to model. | PoorAnother project, and another backlog. |
Featured business processes.
A few of the standard ERP business processes Karini AI automates, each one following the SOP you already have.
- Cash ApplicationReadRemittances with no invoice reference, payments covering many invoices, and short pays that need a reason code before posting.
- Procure to PayReadInvoices blocked on three-way match, missing purchase orders, and vendor email threads that must be resolved before posting.
- Meter-to-CashReadMissing meter reads, delayed bills, and reconciliation gaps across SAP IS-U, the head-end system and field operations.
- Order and Quotes ProcessingReadOrders that arrive as email attachments, items that match more than one catalog entry, and fields that need clarification.
- Credit ManagementReadCustomers over their credit limit, aging that worsens period over period, and credit reviews coming due.
- SOX ReportingReadSOX reports run on schedule through APIs, with evidence captured straight from the ERP, validated and stored in a log that can’t be edited.
Proven on these ERPs. Ready for yours.
Any ERP with documented APIs, including homegrown systems, works the same API-first way. It's a scoping question, not a different product.
SAP
Supported editions
- SAP ECC
- SAP S/4HANA
- SAP Business One
Integration options
- OData
- RFC
- BAPI
- IDocs
Frequently asked questions
No. Karini AI sits on top of your ERP and works through its standard interfaces. Nothing is replaced or customized.
RPA hard-codes rules into scripts that click through screens. When the process changes, the bot breaks, or silently keeps applying the old rule. Karini AI agents follow your SOP and work through ERP APIs, so a policy change is a document edit, not a rebuild.
The process owner updates the SOP. The change is version-controlled and the agents follow the new version. No model to retrain, no agent to rewrite.
Every decision records the SOP section that governed it and the conditions that matched. The explanation is the actual decision trail, not an AI summary written after the fact.
The agents don’t blend them or guess. They determine which SOP has authority over the case, apply it, and record which one governed. If two SOPs genuinely conflict, the trace flags it for your process owners.
SAP, Dynamics 365 Finance and Operations and Epicor Prophet 21 are proven. Any ERP with documented APIs, including homegrown systems, can be added the same way.
In your own cloud infrastructure. Documents and ERP data stay inside your boundary.
Pick one exception type and the SOP that governs it. We run a proof of concept in your environment: one process, no platform commitment.
Are your SOPs ready for AI agents?
Agents are only as precise as the SOPs they follow.
Our SOP Readiness Assessment reviews the SOPs you already have and shows what agents can run as written, what is ambiguous, and which data gaps to close first.
The AI decision layer for your ERP. Driven by your SOPs, deployed in your environment, traceable end to end.
