LLM-Generated Executive Briefings: Automating 10-K & Earnings-Call Analysis for Enterprise Sellers

Author(s)	Adish Rai
Country	United States
Abstract	Outbound noise is at an all-time high and generic outreach underperforms. Recent benchmarks put cold-email replies and cold-call success in the low single digits, pushing enterprise sellers toward deeper, company-specific context. This paper proposes a practical, single-pass long-context approach that ingests a target company’s latest 10-K/10-Q and earnings-call transcript, then produces a seller-ready brief and 2 - 3 persona-specific draft emails. Each recommendation includes a verbatim quote with a precise source reference (timestamp or filing section) to ground the demand hypothesis. We detail an AWS-aligned implementation (Bedrock + Lambda + S3) and a lightweight evaluation rubric (factuality, utility, and operational metrics). We also discuss a data-fusion extension that incorporates CRM and conversation-intelligence data (e.g., meeting notes) to tailor outputs to an account’s live opportunities. A brief sidebar outlines optional enhancements (ephemeral chunking and retrieval) for teams that need lower latency/cost at scale. While the reference design is AWS-centric, the pattern is portable to any stack with equivalent services.
Keywords	Sales enablement; earnings calls; 10-K; large language models; Amazon Bedrock; CRM; enterprise sales
Field	Engineering
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-08-14
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.54995

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