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>Perplexity plans to raise at an $8-9B valuation, up from $3B at the time of its August Series C.</li><li>Perplexity's upside case lies in being a product company with more degrees of freedom than either Google or OpenAI.</li><li>Perplexity focuses on the most complex queries (10-11 words), monetizing them at a higher ARPC through prosumer subscriptions ($20/month), enterprise seats ($40/seat/month), and premium-priced ads ($50 CPM to Facebook's ~$14).</li></ul>

Perplexity plans to raise at an $8-9B valuation, up from $3B at the time of its August Series C.Perplexity's upside case lies in being a product company with more degrees of freedom than either Google or OpenAI.Perplexity focuses on the most complex queries (10-11 words), monetizing them at a higher ARPC through prosumer subscriptions ($20/month), enterprise seats ($40/seat/month), and premium-priced ads ($50 CPM to Facebook's ~$14).

<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>Claude 3.5 Sonnet has blown the doors open for Anthropic's API business, growing 5x this year to date to $664M ARR.</li><li>OpenAI's ChatGPT continues to dominate, growing a Sacra-estimated 2.5x this year to date to $2.9B ARR.</li><li>OpenAI's 4x YoY growth to $4B matches and exceeds Meta, Google & AWS’s.</li></ul>

Claude 3.5 Sonnet has blown the doors open for Anthropic's API business, growing 5x this year to date to $664M ARR.OpenAI's ChatGPT continues to dominate, growing a Sacra-estimated 2.5x this year to date to $2.9B ARR.OpenAI's 4x YoY growth to $4B matches and exceeds Meta, Google & AWS’s.

<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.

Cerebras Systems / Private Capital Markets

<ul><li>Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI compute demand from big enterprises training models on their proprietary data.</li><li>Cerebras (2015) designed its Wafer-Scale Engine chip to vastly accelerate training on the compute-intensive BERT models used in scientific deep learning, finding product-market fit with national labs like Argonne and Livermore working on protein folding, climate prediction, and molecular dynamics.</li><li>With GPTs ascendant (vs BERT models), Cerebras and Groq are both repurposing their chips to move into the $150B and growing market of LLM and AI model training to take on Nvidia.</li></ul>

Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI compute demand from big enterprises training models on their proprietary data.Cerebras (2015) designed its Wafer-Scale Engine chip to vastly accelerate training on the compute-intensive BERT models used in scientific deep learning, finding product-market fit with national labs like Argonne and Livermore working on protein folding, climate prediction, and molecular dynamics.With GPTs ascendant (vs BERT models), Cerebras and Groq are both repurposing their chips to move into the $150B and growing market of LLM and AI model training to take on Nvidia.

Canada

API for fast, cost-effective large language models tailored to enterprise deployments

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Cohere (COHERE CA)

Perplexity At $51M ARR

TL;DR: Sacra estimates that Perplexity is at $51M ARR, up 1,600% year-over-year. Not a search company or an LLM company, Perplexity's upside case...

Sacra

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

What does Outerport do...

Sacra

Anthropic Vs. OpenAI

TL;DR: Claude 3.5 Sonnet has Anthropic's API business surging, hitting a Sacra-estimated $664M ARR this year (up 5x this year to date) and...

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

Cerebras At $250M

TL;DR: Sacra estimates that Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI...

Sacra

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