Inveniam and Docugami have partnered to create a new framework that transforms private market documents into verifiable on chain data, aiming to strengthen trust in real world assets and AI driven finance.
Key Takeaways
- Inveniam and Docugami announced a partnership focused on verifiable data for real world assets (RWAs).
- Docugami is opening its Document Graph Markup Language (DGML) technology to the broader market.
- Inveniam will anchor DGML extracted data on its NVNM Chain Layer 2 network.
- The initiative seeks to improve transparency, auditability, and trust for AI systems, investors, auditors, and tokenized asset platforms.
What Happened?
Inveniam and Docugami have unveiled a new initiative designed to bring greater trust and verification to private market data. The partnership combines Docugami’s document intelligence technology with Inveniam’s blockchain-based data infrastructure, enabling information extracted from complex business documents to be anchored on chain and independently verified.
The companies believe the approach can address one of the biggest challenges facing both tokenized assets and AI-powered financial systems: ensuring that the underlying data used to make decisions can be traced back to trusted source documents.
Inveniam and Docugami Join Forces
Private market assets often rely on information stored in documents such as leases, loan agreements, operating statements, and valuation reports. While these documents contain critical information, much of the data remains locked in unstructured formats that are difficult for machines to process accurately.
To solve this issue, Docugami is opening access to its Document Graph Markup Language (DGML) technology. The platform converts unstructured business documents into structured, precisely labeled data elements that can be analyzed and verified more efficiently.
Inveniam will then anchor those extracted data elements on NVNM Chain, its purpose built Layer 2 blockchain network. By doing so, the information becomes time stamped, tamper evident, and easier to audit.
According to the companies, this creates a more reliable foundation for institutions that depend on accurate private market data.
Moving Verification Beyond Documents
A key aspect of the partnership is the ability to verify individual pieces of information rather than only validating an entire document.
Historically, organizations could often prove where a document originated, but verifying specific data points within that document was significantly more difficult. The new framework seeks to change that by allowing individual data elements extracted through DGML to be independently verified and anchored on chain.
This capability could prove particularly valuable as artificial intelligence becomes more deeply integrated into private markets. AI systems increasingly rely on large volumes of data to generate insights, valuations, and recommendations. Verifiable source data may help improve confidence in those outputs.
Patrick O’Meara, Chairman and CEO of Inveniam, said:
NVNM Chain’s Role in AI Driven Finance
The announcement also highlights the growing role of NVNM Chain, which launched on May 7 as Inveniam’s dedicated Layer 2 network.
The platform was developed as an attestation layer for agentic AI and is designed to anchor verifiable data and digital proofs on chain. These include Proof of Origin, Proof of State, and Proof of Process, allowing organizations to verify the information used in transactions and automated decision making.
By integrating DGML extracted data into NVNM Chain, the companies aim to create a transparent record that can support auditing, reporting, fundraising, valuation processes, and AI-powered workflows.
Jean Paoli, CEO of Docugami and XML co-creator, said:
Building a Transparent Data Layer for Private Markets
The companies describe the initiative as a step toward establishing a more transparent and trustworthy data layer for private markets. As tokenization and AI adoption continue to grow, demand for verifiable data is expected to increase.
Inveniam says it has already credentialed more than $200 billion in private market assets and holds more than 60 patents related to tokenization, blockchain anchored data validation, and attestation technologies.
The partners plan to demonstrate the complete workflow from source documents to verified on chain data, showcasing how extracted information can support institutional and AI driven use cases while maintaining traceability back to the original records.
CoinLaw’s Takeaway
In my experience, one of the biggest obstacles to scaling real world asset tokenization has never been the blockchain itself. The real challenge has been proving that the underlying data is accurate and trustworthy. I found this partnership interesting because it focuses on the source of the information rather than just the token representing an asset. If Inveniam and Docugami can reliably verify data at the individual field level, it could strengthen confidence in both AI-generated insights and tokenized private market assets. That is a meaningful development for an industry increasingly built on data driven decisions.
