Private Markets Still Run on Group Chats. That Is a Data Problem

Private markets deal flow is structurally fragmented — terms shared over WhatsApp, availability tracked in Excel, and critical information living in message histories rather than any centralised system, meaning deals are routinely missed simply because the right person did not have the right information at the right moment. AI agents paired with structured, machine-readable deal infrastructure offer a way to close that gap — and that is precisely what EVIDENT is building.
Devanshee Kothari
Devanshee Kothari
Growth and Research Manager
April 28, 2026

Here is what private markets deal coordination looks like in practice.

A counterparty sends a message — WhatsApp, WeChat, or a direct chat — with supply available for a pre-IPO position. Layer one structure, specific valuation, closes in ten days. The terms are good. Someone notes it down, or forwards it to a colleague, or drops it in a group. Two days later, a different contact asks whether any exposure to the same company is available. The colleague does not immediately connect the two. By the time they do, the terms have changed. The deal may have moved.

This scenario plays out across the industry every day. It is not the result of negligence or poor process. It is the result of an information infrastructure problem. Private markets have no equivalent of the centralised order book that exists in public markets. Deal flow lives in private channels. Terms are informal, often verbal or conversational. There is no shared system where supply meets demand in real time.

The Fragmentation Is Structural

In public markets, standardisation is enforced by exchanges and regulatory requirements. Prices are transparent. Order routing is automated. Information is symmetrical by design.

Private markets operate differently by nature. Deals are negotiated bilaterally. Terms vary by counterparty. Availability is communicated informally and changes frequently. Some firms manage this with Excel files shared via email — a snapshot of a moment that becomes outdated as soon as it is sent. Others rely on relationship managers who carry the knowledge of what is available in their heads and their message histories.

Both approaches have the same core flaw: the information is not structured, not centralised, and not accessible in real time. When a new contact asks what is available, the honest answer is often: let me check with the team and come back to you.

The Cost of Latency

In a market where deals have closing windows of days or weeks, information latency has a direct cost. A deal that is available at a specific structure today may not be available at that structure tomorrow. A buyer who cannot get a quick answer about availability may find a different route. The delay between information existing somewhere and that information being accessible to the right person at the right moment is where value is lost.

This is not a new observation. The industry has been aware of this problem for years. The question has always been what the right infrastructure for solving it looks like — and whether the technology exists to build it.

AI Changes the Calculus

AI agents, combined with the kind of protocol infrastructure we explored in the previous two posts, offer a different approach. If deal information — supply, demand, terms, structure, closing timelines — exists in a structured, machine-readable system, an AI agent can query that system in real time and respond in natural language. The counterparty asks. The agent answers. Instantly, accurately, from live data.

The challenge is getting the information into that system in the first place. The industry communicates via messaging platforms because that is what is fast and familiar. Any solution that asks people to change that behaviour faces friction. The more viable path is to meet people where they are — on the channels they already use — and use AI to interpret and structure what they send.

That is the direction we have been working in. We are building a solution, which we have designed for exactly this problem — the gap between how private markets information actually flows today and what becomes possible when that information is structured, accessible, and AI-ready.

Watch this space.

 

DISCLAIMER

The information provided is for informational and analytical purposes only and should not be construed as financial advice or an offer or an invitation to buy or sell any securities or related financial instruments. It does not constitute a solicitation, recommendation, or endorsement of any particular security, investment product, or strategy. Investors should seek professional advice of their own before making any investment decisions. The views expressed do not necessarily reflect those of EVIDENT or its affiliates. Readers should independently verify any claims and seek appropriate professional advice before making decisions. For Professional Investors only, as defined under Cap.571 Securities and Futures Ordinance in the laws of Hong Kong Special Administrative Region of China.

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