Private Markets, Angel and Secondary Investing, Sacra

Sacra

Bringing transparency to private markets so investors, founders, and employees can build on conviction.

Sacra delivers deeply researched insights on the private companies shaping tomorrow's markets. By surfacing the data, context, and operator perspective that are missing from private markets today, we help secondary buyers and sellers price equity accurately and unlock liquidity for the people building these businesses.

Private Markets, Angel and Secondary Investing

Bringing transparency to private markets so investors, founders, and employees can build on conviction. Sacra delivers deeply researched insights on the private companies shaping tomorrow's markets. By surfacing the data, context, and operator perspective that are missing from private markets today, we help secondary buyers and sellers price equity accurately and unlock liquidity for the people building these businesses.

Private Capital Markets

<ul><li>SaaS in its current dashboard—and workflow-centric form—built on the 2010s UX pattern of buttons, views, and user-driven actions—is being eclipsed by AI agents, with buyers of software increasingly expecting ChatGPT-style systems that can integrate &amp; reason over their data across all their tools via existing APIs, synthesize it, and drive outcomes.</li><li>While unified APIs promised fast integration for human engineers between your SaaS app and entire categories of tools like sales &amp; CRM (Salesforce/HubSpot), HRIS (Workday), and ERP (NetSuite) by flattening 3rd-party systems into the most common fields via a single integration point, AI agents threaten to render this abstraction unnecessary, as they can go deep—parsing arbitrary data structures, mapping to tenant-specific fields, and covering all edge cases—by default.</li><li>As Ampersand, Finch, Merge, and others all move to launch MCP servers and agent-facing SDKs betting MCP will become the HTTP of agentic SaaS, they’re aligning around a shared protocol that gives AI agents access to 3rd-party systems via declarative “tools” for reading and writing data layered over existing APIs—enabling agents to retrieve the live customer context they need to reduce hallucinations and take the best actions.</li></ul>

SaaS in its current dashboard—and workflow-centric form—built on the 2010s UX pattern of buttons, views, and user-driven actions—is being eclipsed by AI agents, with buyers of software increasingly expecting ChatGPT-style systems that can integrate &amp; reason over their data across all their tools via existing APIs, synthesize it, and drive outcomes.While unified APIs promised fast integration for human engineers between your SaaS app and entire categories of tools like sales &amp; CRM (Salesforce/HubSpot), HRIS (Workday), and ERP (NetSuite) by flattening 3rd-party systems into the most common fields via a single integration point, AI agents threaten to render this abstraction unnecessary, as they can go deep—parsing arbitrary data structures, mapping to tenant-specific fields, and covering all edge cases—by default.As Ampersand, Finch, Merge, and others all move to launch MCP servers and agent-facing SDKs betting MCP will become the HTTP of agentic SaaS, they’re aligning around a shared protocol that gives AI agents access to 3rd-party systems via declarative “tools” for reading and writing data layered over existing APIs—enabling agents to retrieve the live customer context they need to reduce hallucinations and take the best actions.

Ayan Barua, CEO Of Ampersand, On Infra For AI Agent Integrations