Post

Dwayne Forde
@dwayne.io

Wealth tech has grown large enough that "trust us, the AI is accurate" shouldn't be the bar anymore. The space deserves proper, public research on raw model capabilities.

Mantle@withmantle.com

For LPs, fund managers, and the teams building wealth tech: AI is doing more of the document work in private markets. But how do you know it's getting the numbers right? Today, we're launching AWE-Bench (Assets & Wealth Extraction Benchmark): blog.withmantle.com/introducing-...

blog.withmantle.comIntroducing AWE-Bench: A Benchmark for AI Extraction in Wealth and Equity | MantleIntroducing AWE-Bench, an open benchmark for AI document extraction in wealth and equity. Compare model accuracy, cost, and speed field by field.

1 repost2 likes

Dwayne Forde
@dwayne.io

Until now there's been no shared way to measure how well models handle the documents this industry actually runs on: capital calls, distribution notices, capital account statements. AWE-Bench is our attempt to fill that gap.

Dwayne Forde
@dwayne.io

This is only the start. Extraction is the foundation, and next we want to add much larger reasoning tasks, where models have to connect information across documents rather than just pull fields from one.

Dwayne Forde
@dwayne.io

We also want this to be genuinely open. The dataset and benchmark tooling will be released soon so anyone can run it, challenge it, and build on it. If you're working with AI in the Wealth tech space, I'd love your feedback 👇 research.withmantle.com/awe

research.withmantle.comAWE Benchmark | Assets & Wealth Document Extraction | Mantle ResearchCompare AI models on financial document extraction with the AWE benchmark. Explore accuracy, cost, and performance across fields and document layouts.