Lokal – Revolutionizing Telugu News Accessibility

Business Problem

Lokal is a regional news platform revolutionizing how Telugu-speaking audiences access news by providing concise summaries and engaging headlines in their native language. Leveraging advanced AI models and culturally nuanced prompt engineering, Lokal ensures accurate, reliable, and audience-focused content delivery.

Lokal was challenged to deliver concise and engaging news summaries and headlines in Telugu, a complex and richly nuanced language. The primary goals were:

  • Making regional news accessible to a larger audience.
  • Generating reliable, culturally relevant content.
  • Reducing manual effort while ensuring quality.

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Solution

Using Claude 3.5 Sonnet on Amazon Bedrock, Lokal deployed a three-stage approach to transform Telugu news delivery:

1.

Prompt-Engineered Summaries: Crafted summaries adhering to journalistic standards, focusing on clarity, accuracy, and the 5Ws and H framework.

3.

Automated Quality Checks: Ensured grammatical accuracy, cultural relevance, and impactful word choice, tailored for Telugu.

2.

Headline Generation: Designed creative and attention-grabbing headlines using concise and culturally relevant formats.

Architecture

  • User Input
    News Article Input: Raw Telugu news articles are provided as input.
  • Summary Generation
    Model Selection: Claude 3.5 Sonnet is used for its advanced language generation capabilities.
    Prompt Engineering:
    A summary generation prompt is used to extract the essence of the article.
    The prompt ensures adherence to journalistic standards, accuracy, and concise outputs.
    Output: An Intermediate Summary Output is generated in Telugu.
  • Headline Generation
    Headline Prompt:
    The Intermediate Summary Output is used as input for a headline-generation prompt.
    The prompt creates concise, engaging, and culturally relevant headlines.
    Output: An Intermediate Headline Output is created.
  • Validation Process
    Validation Prompt:
    A validation prompt reviews the Intermediate Headline and Summary Outputs.
    Checks for grammar, spelling, cultural relevance, and adherence to format.
    Model Used: Claude 3.5 Sonnet performs quality control.
  • Final Output
    Final News Summary and Headline:
    Outputs are finalized after validation.
    These include a concise, impactful headline and an accurate summary.
Outcomes

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Efficiency Boost: Reduced manual content creation by, enabling faster news dissemination.

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Engagement Growth: Improved audience interaction with increased click-through rates due to high-quality, captivating headlines.

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Scalability Achieved: Demonstrated a scalable approach, and readiness to replicate for other regional languages.