A contract-risk assistant should do more than return a red badge. Reviewers need to know which clause triggered the concern, which internal rule applies, how the evidence connects to the conclusion, and what was actually written into the business system.
We built a local integration demo around that operating loop:
OCR → RAGFlow policy retrieval → risk reasoning → Semantica evidence graph → Astron RPA → ERP review draft
The demo uses synthetic contract data and a local ERP-style sandbox. It is an integration proof, not a claim that every component ships with this exact workflow out of the box.
What actually ran
The final step was executed through Astron RPA. The desktop application exposed a bounded contract-risk-to-ERP task, then launched the run and displayed the active execution log.
The run wrote six review fields into the ERP-style form and saved a draft. The result remained in Awaiting Human Review. Final Submit stayed disabled, so the automation could prepare the record without inheriting authority for the irreversible decision.
Why each layer exists
OCR restores structure
Contracts arrive as PDFs, scans, and mixed-layout documents. OCR is not only about extracting characters; the useful output preserves enough structure to reconnect clauses, headings, tables, and page references.
RAGFlow grounds the review in policy
A model can identify suspicious language, but enterprise review needs a policy basis. RAGFlow retrieves the relevant internal rules so the judgment can be traced to the organization’s actual controls instead of generic model memory.
Risk reasoning explains the conclusion
The reasoning layer compares the contract clause with the retrieved rule, names the conflict, and produces a review recommendation. The important output is not only a risk level—it is a compact argument that another reviewer can inspect.
Semantica makes provenance visible
A graph view turns the review into explicit relationships: contract clause → retrieved policy → risk finding → recommended action. That representation is useful for audit, debugging, and human review because each conclusion keeps its evidence path.
Astron RPA closes the system gap
Many ERP workflows still depend on browser forms, desktop clients, or interfaces with incomplete APIs. Astron RPA takes the structured review result and enters it into the system as an observable draft.
The safety boundary matters
The workflow intentionally separates preparation from authorization. OCR, retrieval, reasoning, graph construction, and draft entry can be automated. Final submission remains a human action.
That is a better enterprise pattern than a black-box agent that both decides and commits. It provides speed without erasing accountability.
Open-source building blocks
The short version: the AI finds the risk, explains the evidence chain, and prepares the ERP record—while a human keeps the final say.
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