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NIX helped Starday, an F&B company, enhance its trend analysis capacity from 25,000 to over 100,000 posts/day, enabling the classification of posts in under an hour for faster, data-driven innovation.
Food & Beverages
Data Science, AI, Cloud Services, Generative AI, AWS
Python, AWS GraphRAG Toolkit, LangChain, Anthropic Claude
Starday is an AI-powered food and beverage (F&B) innovation company that combines deep consumer packaged goods expertise with AI and predictive analytics to enhance F&B decision making. After successfully launching four brands and 16 products of their own to retail shelves, Starday partnered with F&B brands, manufacturers, distributors, and retailers to help them drive organic growth through high-potential, risk-reduced innovation opportunities.
Starday required a solution to manage a massive, unstructured dataset of social media content from platforms such as TikTok. With millions of posts generated daily, traditional methods were inefficient and couldn’t keep pace with emerging trends. The company partnered with NIX for an automated solution that categorizes content, identifies key trends, and generates actionable reports to guide future product development.
The primary challenge was the sheer scale and complexity of social media data, and with trends changing by the second, speed was paramount. The client needed to move beyond simple keyword tracking to a more nuanced understanding of conversations. The specific pain points included:
Scalability and data volume: Required a 4x increase in data capacity (25,000 → 100,000+ posts/day) to keep pace with the millions of daily posts and ensure efficient categorization.
Trend detection: Lack of an automated system to continuously update their ontology of keywords and topics, leading to missed opportunities.
Insight extraction: Difficulty in extracting complex relationships and actionable insights from unstructured text.
NIX AI engineers needed to create an AI solution from scratch that would:
Our team designed a three-pipeline system, strategically leveraging AI models within the client’s existing AWS infrastructure. This integrated AI solution was engineered for raw power and efficiency, ensuring the client could scale their social media analysis without a significant increase in operational costs.
NIX AI engineers implemented a tiered model-selection strategy to optimize both speed and value. We utilized Anthropic Claude 3 Haiku as the primary workhorse for high-volume, repetitive tasks, automating functions such as domain relevance validation and term categorization to expedite data ingestion.
When a higher level of reasoning was needed, we deployed Anthropic Claude 3.5 Sonnet. Its advanced capabilities were critical for synthesizing insights from the knowledge graph and generating the final reports that provided our client with the strategic intelligence needed for data-driven decisions.
We built the AI solution on top of specialized pipelines designed to handle the full data life cycle, each addressing a specific business need.
By implementing this AI-driven solution, Starday fundamentally transformed its ability to process and act on social media data.
The solution, developed by NIX, streamlined the entire analysis workflow, leading to a significant increase in operational efficiency and a deeper, more granular understanding of market trends.
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