AlphaLab launches Quanty One, an AI quant researcher

Nov 13, 2026
The agent builds and tests trading strategies in conversation on AlphaLab's research platform; firms can also plug in their own agents via MCP.

AlphaLab has made Quanty One available, an AI quantitative researcher that builds trading strategies, runs experiments and writes reports in conversation, the company said in a release sent to AI Brief. AlphaLab is developed by Edgebot Corporation.

Quanty One runs on AlphaLab's research platform, which provides licensed market data, 279 tested research components and a simulator that accounts for trading costs. Controls check for look-ahead bias before a test runs, out-of-sample testing helps catch overfitting, and separate reviewer agents examine the research methods. Work continues in the background, with human approval at key decision points.

Firms can also connect their own AI agents to the platform through the Model Context Protocol. Both products are available now through AlphaLab Cloud, with plans for individual researchers and small quant teams.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Finance AI Weekly, AI Programming Weekly or Daily AI Brief.

Also, consider following us on social media:

AI in Finance AI Brief AI Brief (X)
Free newsletter

AI Programming Weekly

Weekly news about AI tools for software engineers, AI enabled IDE's and much more.

Guide
AI app builders

AI app builders

Tools that turn a description into a working web or mobile app, and the platforms companies use to build internal tools with AI

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.