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📌 12 AI Startups raise $250M+

📌 12 AI Startups raise $250M+

BONUS: Sales AI Report From HG Insights

October 09, 2024

TODAY’S FUNDING RECAP 🗓️

Braintrust raises a $36M Series A — LLM app development
TensorWave raises a $43M SAFE — GPU cloud
Driver raises a $8M Seed — AI for technical documentation
Distributional raises a $19M Series A — Enterprise AI testing
8 more rounds caught by my funding tracker

Read time: 3 minutes

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TOP PICKS 📢

1/4

→ Braintrust

Amount: $36M 🎉

Valuation: $150M

Round: Series A

Lead Investor: Andreessen Horowitz

Braintrust is a development platform for building applications that use LLMs.

The platform allows companies to evaluate the performance of their AI tools in real time, providing insights into what prompts work best and pinpointing problem areas when AI outputs fail. Key features include prompt templating, logging, model proxying, and real-time prompt serving.

2/4

→ TensorWave

Amount: $43M 🎉

Round: SAFE

Lead Investor: Nexus Venture Partners

TensorWave is a GPU cloud platform powered by AMD hardware only.

The platform offers optimized computing power that supports the training, inference, and deployment of AI models. TensorWave focuses on reducing latency and while offering flexibility in compute resources, allowing businesses to scale their AI workloads without significant infrastructure investments and reduced reliance on Nvidia.

See their pitch deck

3/4

→ Driver

Amount: $8M 🎉

Round: Seed

Lead Investor: Google Ventures

Driver uses AI to automate the generation and updating of technical documentation.

It takes complex manuals, source code, and documentation—often thousands of pages long—and decodes it into simplified, interactive formats that are easier for engineers to understand and implement. The platform is language-agnostic and syncs with repositories like GitHub to ensure that documentation is always up to date.

4/4

→ Distributional

Amount: $19M 🎉

Round: Series A

Lead Investor: Two Sigma Ventures

Distributional offers a platform for testing and auditing AI applications.

Its solution automatically generates statistical tests tailored to an enterprise's AI models and organizes them in a collaborative dashboard. The platform enables users to manage and triage test results, recalibrate tests, and integrate with other tools. Distributional supports both on-premises and managed deployments, providing continuous monitoring during development and production phases.