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author

Bhavishya Pohani

Senior Research Scientist
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Snorkel AI

Bhavishya Pohani is a Senior Research Scientist at Snorkel AI, focusing on large language model fine-tuning & agentic systems. Before Snorkel, he worked on building deep learning systems at Chubb Insurance.

The latest from Bhavishya

Building FinQA: An Open RL Environment for Financial Reasoning Agents
Blog
Building FinQA: An Open RL Environment for Financial Reasoning Agents

TL;DR: We built FinQA — a financial question-answering environment with 290 expert-curated questions across 22 public companies, now available on OpenEnv. Agents use MCP tools to discover schemas, write constrained SQL queries, and answer multi-step questions from real SEC 10-K filings. Most open-source models struggle with this kind of multi-step tool use, and even frontier closed-source models, while more accurate,…

Mar 30, 2026
Learn more about Building FinQA: An Open RL Environment for Financial Reasoning Agents
Evaluating Multi-Agent Systems in Enterprise Tool Use
Blog
Evaluating Multi-Agent Systems in Enterprise Tool Use

In recent months, there has been increasing interest in the area of multi-agent systems and how they can be used to solve more complex tasks than a single agent could accomplish on its own. The topic is particularly interesting and raises several questions and ideas to consider: Anthropic’s blog post about how they architected a multi-agent deep research system is…

Oct 09, 2025
Learn more about Evaluating Multi-Agent Systems in Enterprise Tool Use
A Clinical Text Classification Paradigm Using Weak Supervision…
This work develops a rule-based NLP algorithm to automatically generate labels for the training data, and then use the pre-trained word embeddings as deep representation features for training machine learning models.
Research Paper
A Clinical Text Classification Paradigm Using Weak Supervision…

This work develops a rule-based NLP algorithm to automatically generate labels for the training data, and then use the pre-trained word embeddings as deep representation features for training machine learning models.

Learn more about A Clinical Text Classification Paradigm Using Weak Supervision…
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