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>Sacra estimates they hit $50M in annual recurring revenue (ARR) at the end of 2024, up 50x, with growing demand for high-skill experts for reinforcement learning with human feedback (RLHF).</li><li>As labs started building LLMs focused on complex math, science, and other reasoning tasks, frontier labs began doing RLHF with $50-100/hr medical doctors, lawyers and PhDs to improve their models’ capabilities.</li><li>On the back of growing demand from AI labs for human experts to train the next generation of models, Sacra estimates that Mercor hit $50M in annual recurring revenue (ARR) at the end of 2024, growing 50x from $1M at the beginning of the year.</li></ul>

Sacra estimates they hit $50M in annual recurring revenue (ARR) at the end of 2024, up 50x, with growing demand for high-skill experts for reinforcement learning with human feedback (RLHF).As labs started building LLMs focused on complex math, science, and other reasoning tasks, frontier labs began doing RLHF with $50-100/hr medical doctors, lawyers and PhDs to improve their models’ capabilities.On the back of growing demand from AI labs for human experts to train the next generation of models, Sacra estimates that Mercor hit $50M in annual recurring revenue (ARR) at the end of 2024, growing 50x from $1M at the beginning of the year.

<ul><li>H2O.ai found product-market fit as an open-source machine learning platform for data scientists and developers who needed industrial-strength ML capabilities without building everything from scratch.</li><li>H2O.ai operates a hybrid open-source/enterprise SaaS model focused on making artificial intelligence and machine learning accessible to businesses of all sizes.</li><li>The company&#39;s $1.7B valuation suggests investors see potential for H2O.ai to become a major enterprise AI platform, similar to how Snowflake emerged as the leader in cloud data warehousing.</li></ul>

H2O.ai found product-market fit as an open-source machine learning platform for data scientists and developers who needed industrial-strength ML capabilities without building everything from scratch.H2O.ai operates a hybrid open-source/enterprise SaaS model focused on making artificial intelligence and machine learning accessible to businesses of all sizes.The company&#39;s $1.7B valuation suggests investors see potential for H2O.ai to become a major enterprise AI platform, similar to how Snowflake emerged as the leader in cloud data warehousing.

<ul><li>The MLOps landscape has evolved from targeting researchers who preferred simple Python APIs and quick setup to serving DevOps professionals who need enterprise-grade telemetry, monitoring and deployment tools that can handle high-volume production workloads.</li><li>LLM deployment differs fundamentally from traditional software deployment because models are massive files (often 10-20GB) that must be loaded across CPU and GPU memory, creating new technical challenges around memory management, version control, and continuous deployment that existing DevOps tools weren't built to handle.</li><li>Building on microservices and serverless, compound AI systems merge together multiple custom AI models, LLMs and diffusion models with databases and external APIs—spawning a new generation of tools like Outerport and Modal ($32M raised) that let developers automatically deploy and run multi-LLM systems across CPU/GPU architectures without worrying about infrastructure.</li></ul>

The MLOps landscape has evolved from targeting researchers who preferred simple Python APIs and quick setup to serving DevOps professionals who need enterprise-grade telemetry, monitoring and deployment tools that can handle high-volume production workloads.LLM deployment differs fundamentally from traditional software deployment because models are massive files (often 10-20GB) that must be loaded across CPU and GPU memory, creating new technical challenges around memory management, version control, and continuous deployment that existing DevOps tools weren't built to handle.Building on microservices and serverless, compound AI systems merge together multiple custom AI models, LLMs and diffusion models with databases and external APIs—spawning a new generation of tools like Outerport and Modal ($32M raised) that let developers automatically deploy and run multi-LLM systems across CPU/GPU architectures without worrying about infrastructure.

Towaki Takikawa, CEO And co-founder Of Outerport, On The Rise Of DevOps For LLMs

<ul><li>Brex is directly integrated with Mastercard.</li><li>Going global shifts Brex’s competitive set to multinational banks like Citi and HSBC.</li><li>Our goal with having a global focus is to satisfy customer needs for one global limit for all of their employees around the world.</li></ul>

Brex is directly integrated with Mastercard.Going global shifts Brex’s competitive set to multinational banks like Citi and HSBC.Our goal with having a global focus is to satisfy customer needs for one global limit for all of their employees around the world.

Art Levy, Chief Business Officer At Brex, On The Strategy Of Brex Embedded

<ul><li>Sacra estimates that Dataiku hit $250M in annual recurring revenue (ARR) in 2023, up 25% year-over-year.</li><li>Founded in France in 2013, Dataiku bundled together Fivetran (data ingest), Alteryx (data prep), DataRobot (automated ML), and Tableau (data visualization) into a simple GUI for data science.</li><li>Dataiku is building a high-margin, collaborative user interface layer for AI/ML ala Amplitude (74% gross margins, $281M ARR) in product analytics or Tableau (90% gross margins) in BI.</li></ul>

Sacra estimates that Dataiku hit $250M in annual recurring revenue (ARR) in 2023, up 25% year-over-year.Founded in France in 2013, Dataiku bundled together Fivetran (data ingest), Alteryx (data prep), DataRobot (automated ML), and Tableau (data visualization) into a simple GUI for data science.Dataiku is building a high-margin, collaborative user interface layer for AI/ML ala Amplitude (74% gross margins, $281M ARR) in product analytics or Tableau (90% gross margins) in BI.

United States

Tooling suite for data labeling, model training, and deployment for enterprise ML teams

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LinkedIn For Data Labelers

TL;DR: The AI-powered Upwork, Mercor, is matching AI labs with pre-vetted domain experts from fields like law, medicine, and physics. Sacra...

Sacra

Primer: H2O.ai - 18 Nov 2024

Suite of no-code and AutoML tools for building and deploying enterprise AI models

Sacra

Towaki Takikawa, CEO And co-founder Of Outerport, On The Rise Of DevOps For LLMs

What does Outerport do...

Sacra

Art Levy, Chief Business Officer At Brex, On The Strategy Of Brex Embedded

What is Brex Embedded, who are its customers, how do they (and their end customers use it), and why did you build it...

Sacra

Dataiku At $250M ARR

TL;DR: Sacra estimates Dataiku hit $250M in annual recurring revenue (ARR) in 2023, up 25% YoY, with growing demand from enterprises for tools that...

Sacra

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