IR Materials and Earnings Release Localization with PAW

How Peoplying Used PAW to Accelerate IR Localization While Maintaining Financial Communication Quality

Investor relations content requires speed, consistency, and high reliability. Earnings releases, IR decks, investor FAQs, and related communications often move on tight schedules and must remain accurate in tone, terminology, and financial messaging. In this kind of workflow, AI can improve speed, but only when it is applied in a controlled environment designed for financial communication.

This case study shows how Peoplying supported an anonymous client by localizing IR materials and earnings release content through a workflow built around PAW, helping the client accelerate multilingual delivery while maintaining the quality required for investor-facing communications.

Project Overview

The client required localization support for investor-facing communication materials, including:

• earnings release documents,
• investor relations presentations,
• executive summary materials,
• shareholder and investor-facing updates,
• supporting IR communication content.

The client’s goals were to:

• shorten turnaround time for time-sensitive IR localization,
• maintain consistency in financial and investor-facing terminology,
• strengthen output quality under tight deadlines,
• support repeatable multilingual IR communication workflows.

Key Challenges

1) IR Content Is Both Time-Sensitive and High-Risk
Earnings-related materials often require fast production but cannot tolerate weak terminology or unclear language.

2) Financial Messaging Needed Stable Tone and Terminology
Investor-facing content had to remain consistent, concise, and credible.

3) Repeated Release Cycles Required Scalability
The client needed a workflow suitable for recurring reporting cycles, not just one-time translation.

4) AI Needed to Be Applied in a Controlled Way
Speed gains mattered, but raw AI output alone was not enough for IR-quality communication.

Peoplying’s Approach

1) PAW for Controlled Financial-Content Processing
Peoplying used PAW as the core workflow environment to process IR and earnings-related materials in a more structured way than standard standalone MT.

2) Domain-Adapted AI Language Model for Financial Communication
The project benefited from AI language models strengthened through large domain-specific financial and corporate corpora, allowing more stable handling of financial-reporting expressions and investor-facing phrasing.

3) Human Review for Investor-Facing Quality
Financial linguists reviewed the AI-supported output to confirm terminology accuracy, tone suitability, and message clarity.

4) QA for Release-Ready IR Delivery
Final QA focused on consistency across IR documents, investor-facing readability, and release readiness.

Results

Peoplying delivered an AI-supported IR localization workflow that improved both speed and quality:

• faster turnaround for earnings release and IR materials,
• improved handling of finance-related terminology through domain-adapted AI support,
• stronger investor-facing clarity after human review,
• repeatable multilingual workflow for recurring IR cycles.

What This Shows

• PAW helps financial clients improve speed without giving up quality control.
• Domain-adapted AI models are especially valuable in recurring IR and earnings communication workflows.
• Human validation remains essential for final investor-facing trust and clarity.