Leapfrogging Web 2 and Straight to Web 3

The global trading of Private Markets/Alternatives will be Digital, but as the WSJ says, this will include everything else as well. This will leapfrog Web 2 and go straight to Web 3. Everyone is talking about Real World Assets and Tokenization, and that is correct, but only the beginning, a distributed ledger, will be connected to distributed compute, but if you then rely on a centralized data solution, you leave the majority of the value on the table.

Every alternative asset, their capital stack, and the funds that hold them will be digitized. This will sit on a distributed ledger to see who owns what and to facilitate the global trading in a networked reality. These assets will be powered by distributed compute (cloud and IA on demand) and even compute from the edge to inform buyers and perform real time survellience of the underlying assets. This survellience will be of distributed data at the edge.

DLT, Automation (AI with attribution) and Data

Digital Markets will transform private markets with real-time valuation, liquidity, trading, and new forms of distribution. Traditional refinancing, acquisition, and distribution of data-rich, low frequency traded assets is expensive and time-consuming due to opaque, unauditable, infrequent data.

These assets are illiquid and undervalued, and they must have good data to trade.

1. Expensive and Inefficient: A lack of transparency, auditability, and infrequently updated data makes refinancing, acquiring, and distributing interests in real-world assets (RWA) costly & time-consuming.
2. Importance of Price Discovery: Private market assets, including Real Estate, Private Equity, Private Credit, and Infrastructure, require effective price discovery for efficient/optimal transactions.
3. Liquidity and Transparency Issues: The lack of readily available fundamental data in these asset classes limits transparency and consequently inhibits liquidity relative to public market assets.
4. Discounted Values: As a result, these assets frequently trade at a discount compared to public market counterparts and there is a very limited market for secondary trading.
5. Increasingly Alarming Solutions: The AI and Large Language Model (LLM) quick-fix will only exponentially compound the problem of AI hallucinations, making errors the rule and driving more public market data assumptions which is the only current attributable data set into private market insights, even though these comparisons may not be accurate or applicable.

Inveniam is the software framework for managing data at the edge and delivering proof of state of data, proof of origin of data, delivering AI solutions with attribution to a specific document and specific location on a page (bounded polygon), that is auditable, provable and can act as an oracle for off chain or on chain computation that drives a capital markets transaction.

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https://on.wsj.com/43ltNIG