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arXiv:2503.23303cs.LG

SalesRLAgent: A Reinforcement Learning Approach for Real-Time Sales Conversion Prediction and Optimization

Nandakishor M

Abstract

Current approaches to sales conversation analysis and conversion prediction typically rely on Large Language Models (LLMs) combined with basic retrieval augmented generation (RAG). These systems, while capable of answering questions, fail to accurately predict conversion probability or provide strategic guidance in real time. In this paper, we present SalesRLAgent, a novel framework leveraging specialized reinforcement learning to predict conversion probability throughout sales conversations. Unlike systems from Kapa.ai, Mendable, Inkeep, and others that primarily use off-the-shelf LLMs for content generation, our approach treats conversion prediction as a sequential decision problem, training on synthetic data generated using GPT-4O to develop a specialized probability estimation model. Our system incorporates Azure OpenAI embeddings (3072 dimensions), turn-by-turn state tracking, and meta-learning capabilities to understand its own knowledge boundaries. Evaluations demonstrate that SalesRLAgent achieves 96.7% accuracy in conversion prediction, outperforming LLM-only approaches by 34.7% while offering significantly faster inference (85ms vs 3450ms for GPT-4). Furthermore, integration with existing sales platforms shows a 43.2% increase in conversion rates when representatives utilize our system's real-time guidance. SalesRLAgent represents a fundamental shift from content generation to strategic sales intelligence, providing moment-by-moment conversion probability estimation with actionable insights for sales professionals.

arXiv comments
Journal reference
DOI
Subjects
cs.LGMachine Learning cs.AIArtificial Intelligence

On Hacker News

Linked by 6 identifiable commenters in 7 comments across 4 threads, from Sep 2026 to Oct 2026. Found in 2 HN submissions from May 2025 to Sep 2026. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments4 threads

  1. Typesafe AI raises $870M at $7.5B 1 comment
  2. I built non-autoregressive decision models with RL a year ago 4 comments

    • Jev was built using the same architecture Laya's author proposed[1] in March 2025. Laya is an open-source system based on that research from a year ago. Whether Jev is also based on the OP's materials or independently invented is hard to say. [1] https://arxiv.org/abs/2503.23303

      klibertpView on HNParent context

    • paper the reddit OP "published" (their words on reddit) to arxiv (before they put the vouching process in place). It's what you expect if you click through. https://arxiv.org/pdf/2503.23303 Does not appear to be like what Jev is doing, they talk about RAG and embeddings and…

      verdvermView on HNParent context

    • I’m not filled with confidence when the author’s first paper takes an RL approach but then doesn’t use it to change the action taken in the next turn. Seems like simple classification would achieve the same end. And this quote from the paper isn’t overly reassuring: “I…

      tomsyouruncleView on HNParent context

    • > not to mention the egregious target leakage I was curious about this so I skimmed the paper [0]: > SalesRLAgent achieved 96.7% accuracy, outperforming the best commercial alternative by 23.7 percentage points and the best LLM approach by 34.7 percentage points. For a fuzzy…

      fxwinView on HNParent context

  3. Open Source JEV architecture built 1 year ago 1 comment

    • paper the reddit OP "published" to arxiv (before they put the vouching process in place, it's what you'll expect if you click through) https://arxiv.org/pdf/2503.23303 Does not appear to be like what Jev is doing

      verdvermView on HNParent context

  4. OpenJev 1 comment

    • You might also be interested in "Open-sourced jev architecture last year with model,paper and dataset" https://news.ycombinator.com/item?id=49736660 https://www.reddit.com/r/LocalLLaMA/comments/1wjieap/made_th... Papers: https://arxiv.org/abs/2503.23303…

      corysamaView on HNParent context

Submitted to Hacker News

  • Open-sourced jev architecture last year with model,paper and dataset97 points18 comments

    Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, published an arxiv paper, pushed the model to huggingface along with the pypi package and training dataset. And then one year later, a frontier lab came, proposing the same idea like literal breakthrough without technical papers, open weights and no open dataset. For anyones information the main guiding…

  • Open-Source RL Model for Predicting Sales Conversion from Conversations1 point0 comments

    For the past couple of months, I have been working on building a chess game kinda system for predicting sales conversion probabilities from sales conversations. Sales are notoriously difficult to analyse with current LLMs or SLMs, even ChatGPT, Claude, or Gemini failed to fully analyse sales conversations. How about we can guide the conversations based on predicting the conversion probabilities, that is, kinda trained on a 100000+ sales conversation with RL to predict the final probability from…

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