Chalk raises $50M at $500M valuation to empower AI inference

Chalk AI Inc., a data platform for AI inference, announced Wednesday it has raised $50 million in early-stage funding led by Felicis at a $500 million valuation to accelerate the development of its platform.

Triatomic Capital participated in the Series A round alongside existing investors General Catalyst, Unusual Ventures and Xfund.

The San Francisco-based company’s service provides real-time data for artificial intelligence and machine learning models during inference, or runtime, allowing companies to allow AI to make accurate decisions with lower risk of hallucinations. The company says that its platform is essential as AI adoption continues at a breakneck pace as it helps to improve the quality of AI outputs, make them snappier and reduce the cost of deploying AI and machine learning models.

“AI compute is shifting rapidly from training to real-time inference, creating new demands for fresh data and complex computations at the exact moment decisions are made,” said co-founder and Chief Executive Marc Freed-Finnegan.

Chalk positions itself as a competitor to existing data lake and data warehouse solutions such as Databricks Inc. and Snowflake Inc., which the company says solve the enormous data pipeline and feature store needs for AI model training data and pre-computed data.

However, the company said, these solutions aren’t able to provide this data fast enough to be useful at inference time.

“Chalk is poised to become the Databricks of the AI era,” said Aydin Senkut, founder and managing partner at Felicis. “The team has fundamentally redefined how data moves through the AI stack, a crucial advancement for chain-of-reasoning models.”

A chain-of-reasoning model, also called chain-of-thought, is a type of AI model that will “think” and explain its reasoning process step-by-step before arriving at an answer. This approach allows an AI model to break down complex problems into smaller, logical steps, allowing it to mimic how humans solve problems by “thinking out loud.” These models in particular require detailed, accurate and up-to-date data for the quick delivery of detailed answers.

Chalk says it can deliver data pipeline rates within five-millisecond latency at massive scale.

“Chalk helps us deliver financial products that are more responsive, more personalized, and more secure for millions of users,” said Meng Xin Loh, senior technical product manager at MoneyLion Inc., a fintech company that offers financial products and services. “It’s a direct line from infrastructure to impact.”

For developers, the company’s Compute Engine allows developers to write code in pure Python and automatically translate it into high-performance C++ and Rust pipelines to deliver complex real-time data for extraction and ingestion.

Chalk also provides native vector storage, which is necessary for creating retrieval-augmented generation pipelines and knowledge graphs. These enable the creation of long-term memory for large language models and AI agents. The company’s AI toolchain offers direct integrations with major LLM providers.

Doppel, an AI-driven platform that protects users against social engineering attacks, uses Chalk’s platform to detect, warn about and stop potential cybersecurity threats. Social engineering examples include emails or text messages that trick users into revealing passwords or other sensitive information.

“Chalk powers our LLM pipeline, turning complex inputs — HTML, URLs, screenshots — into structured, auditable features,” said Rahul Madduluri, chief technology officer at Doppel. “It lets us serve lightweight heuristics up front and rich LLM reasoning deeper in the stack, so we detect threats others miss without compromising speed or precision.”

Chalk said that it will use the new capital to build out its platform, onboard new customers and grow its engineering and go-to-market hubs in San Francisco and New York.

Image: Pixabay

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