Private Markets, Angel and Secondary Investing, Sacra

Sacra

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>Foundation model companies OpenAI & Anthropic commoditized the first wave of vertical AI companies that reasoned over public data—like web PDFs, patents and earnings calls—with agentic products that browse the web, do deep research and build datasets, spurring the next wave of vertical AI companies that focus on integrating frontier models with vertical-specific workflows, embedded with proprietary telemetry that captures document diffs, user corrections & tool calls.</li><li>In highly-regulated, risk-averse industries, less than 1% of manual workflows have been replaced with AI as companies fear IP exposure through third-party models, unauditable changes to high-stakes documents, and AI-generated content they can't verify or trace back to source material, creating the opportunity for companies like Raycaster for biotech (Seed, Y Combinator) alongside bigger players like Harvey for law ($21M Series A, Sequoia) and Hebbia for finance ($30M Series A, Index Ventures).</li><li>Today&#39;s emerging vertical AI playbook: 1) embed engineers a la Palantir&#39;s forward-deployed model to build AI workflows and automate away manual processes, 2) hire domain experts as internal evaluators through a Mercor-like contractor network to tune &amp; improve outputs, and 3) capture customers’ usage data to continually improve the system.</li></ul>

Foundation model companies OpenAI & Anthropic commoditized the first wave of vertical AI companies that reasoned over public data—like web PDFs, patents and earnings calls—with agentic products that browse the web, do deep research and build datasets, spurring the next wave of vertical AI companies that focus on integrating frontier models with vertical-specific workflows, embedded with proprietary telemetry that captures document diffs, user corrections & tool calls.In highly-regulated, risk-averse industries, less than 1% of manual workflows have been replaced with AI as companies fear IP exposure through third-party models, unauditable changes to high-stakes documents, and AI-generated content they can't verify or trace back to source material, creating the opportunity for companies like Raycaster for biotech (Seed, Y Combinator) alongside bigger players like Harvey for law ($21M Series A, Sequoia) and Hebbia for finance ($30M Series A, Index Ventures).Today&#39;s emerging vertical AI playbook: 1) embed engineers a la Palantir&#39;s forward-deployed model to build AI workflows and automate away manual processes, 2) hire domain experts as internal evaluators through a Mercor-like contractor network to tune &amp; improve outputs, and 3) capture customers’ usage data to continually improve the system.

Levi Lian, CEO Of Raycaster, On Why Vertical AI Is Workflows First & Chat Last

<ul><li>Handshake (2013) grew its campus recruiting portal & job marketplace to 18M students, ending 2024 at ~$190M in revenue (up 6% YoY) but with growth decelerating.</li><li>COVID dramatically accelerated Handshake's growth as remote recruiting exploded and in-person career fairs disappeared, driving revenue from $36M in 2020 to $75M in 2021 (108% YoY) and $120M in 2022 (60% YoY).</li><li>In 2023, frontier model companies drove massive demand for academically credentialed data labelers to power reasoning models and benchmarks in math, law & physics—driving the growth of companies like Mercor (Mercor $500M annualized revenue in August 2025)—with Handshake specifically well positioned to capitalize.</li></ul>

Handshake (2013) grew its campus recruiting portal & job marketplace to 18M students, ending 2024 at ~$190M in revenue (up 6% YoY) but with growth decelerating.COVID dramatically accelerated Handshake's growth as remote recruiting exploded and in-person career fairs disappeared, driving revenue from $36M in 2020 to $75M in 2021 (108% YoY) and $120M in 2022 (60% YoY).In 2023, frontier model companies drove massive demand for academically credentialed data labelers to power reasoning models and benchmarks in math, law & physics—driving the growth of companies like Mercor (Mercor $500M annualized revenue in August 2025)—with Handshake specifically well positioned to capitalize.

<ul><li>In 5 years regulation will be a defining force in AI safety and compliance work requiring human validation.</li><li>What really matters is net revenue and margins for durability.</li><li>Models are already reaching a point where they surpass the knowledge of the experts who trained them.</li></ul>

In 5 years regulation will be a defining force in AI safety and compliance work requiring human validation.What really matters is net revenue and margins for durability.Models are already reaching a point where they surpass the knowledge of the experts who trained them.

Jemma White, COO Of Prolific, On Why Humans Ensure AI Safety

<ul><li>The demand from frontier AI labs for expert data labeling has driven the growth of companies like Mercor ($100M annualized revenue in February 2025) to Invisible ($134M in 2024) to Handshake ($50M from AI data labeling).</li><li>Traditional boundaries between expert calls (GLG, AlphaSights, Tegus), market surveys (Gartner, Forrester) and user interviews (UserTesting, User Interviews) are collapsing into a single "primary research" category worth tens of billions—with life sciences consulting alone at $50B+—as AI abstracts away specific formats into agents that can run voice interviews & surveys, generate & extract content & data and produce completions & reports.</li><li>As foundation model labs have moved towards reasoning models which require PhD-level evaluation and fine-tuning, aggregating the supply side of verified & highly-credentialed domain experts across finance, legal, healthcare & other verticals has become key to serving demand—versus low-cost annotations from crowdsourced Mechanical Turk-style overseas workers.</li></ul>

The demand from frontier AI labs for expert data labeling has driven the growth of companies like Mercor ($100M annualized revenue in February 2025) to Invisible ($134M in 2024) to Handshake ($50M from AI data labeling).Traditional boundaries between expert calls (GLG, AlphaSights, Tegus), market surveys (Gartner, Forrester) and user interviews (UserTesting, User Interviews) are collapsing into a single "primary research" category worth tens of billions—with life sciences consulting alone at $50B+—as AI abstracts away specific formats into agents that can run voice interviews & surveys, generate & extract content & data and produce completions & reports.As foundation model labs have moved towards reasoning models which require PhD-level evaluation and fine-tuning, aggregating the supply side of verified & highly-credentialed domain experts across finance, legal, healthcare & other verticals has become key to serving demand—versus low-cost annotations from crowdsourced Mechanical Turk-style overseas workers.

Joe Kim, CEO Of Office Hours, On The End Of Crowdwork

<ul><li>Office Hours raised a $5M seed round in February 2021, led by CRV, with participation from Susa Ventures, BoxGroup, Greenoaks, Manresa Ventures, and AirAngels.</li><li>The company generates revenue by taking a percentage of each consultation fee, following a model similar to other marketplaces.</li><li>Office Hours has diversified its customer base beyond venture capital and consulting firms to include corporate strategy teams, product management organizations, and early-stage startups.</li></ul>

Office Hours raised a $5M seed round in February 2021, led by CRV, with participation from Susa Ventures, BoxGroup, Greenoaks, Manresa Ventures, and AirAngels.The company generates revenue by taking a percentage of each consultation fee, following a model similar to other marketplaces.Office Hours has diversified its customer base beyond venture capital and consulting firms to include corporate strategy teams, product management organizations, and early-stage startups.

United States

Marketplace matching AI labs with pre-vetted domain experts for RLHF tasks

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Mercor (MERCOR US)

Levi Lian, CEO Of Raycaster, On Why Vertical AI Is Workflows First & Chat Last

What is Raycaster in short and what inspired you to start the company...

Sacra

Handshake Vs Mercor

TL;DR: Handshake (2013) grew its campus recruiting portal & job marketplace to 18M students, ending 2024 at ~$190M in revenue (up 6% YoY) but with...

Sacra

Jemma White, COO Of Prolific, On Why Humans Ensure AI Safety

Like a lot of companies in this space, when Prolific started it was working on a slightly different use case. How did Prolific evolve to meet AI...

Sacra

Joe Kim, CEO Of Office Hours, On The End Of Crowdwork

I'll start with the origin story. You were at AlphaSights for a while. What were the experiences and insights you had that led you to start Office...

Sacra

Primer: Office Hours - 31 Aug 2025

Platform connecting clients with advisors for expert knowledge-sharing across various industries

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