A trend-responsive AI platform for smarter content strategies
Services:
Project overview
In today’s digital landscape, the flood of content is relentless, which complicates its categorization and analysis. As investigated by Statista, the amount of content being created, captured, copied, and consumed is projected to reach 149 zettabytes (1 ZB makes a trillion GB) in 2024 and over 394 zettabytes by 2028.
The problem: conventional taxonomies drop behind, typically incapable to adapt to emerging content trends. Our solution: a platform to categorize and analyze new content, dynamically fine-tuning existing taxonomies and creating new ones when needed.
The result? A smarter, faster way to keep up with the ever-changing content landscape.
- McKinsey reports that companies who go with generative artificial intelligence are poised to transform everyday routines & roles
- Deloitte reveals that companies are investing in generative artificial intelligence to create more value, suggesting optimization in overall business performance
Main goals
Content management completely redefined
We attempt to provide a dynamic, real-time solution that allows staying ahead of changing business dynamics:
- By identifying content trends and handling further tasks, including categorization & analysis
- And updating existing taxonomies (also creating new ones)
We helped our client to make more informed, data-driven decisions, and that sensibly faster than ever.
Business empowerment through efficiency
We strive to deliver a solution:
- To facilitate operational accuracy and minimize manual efforts while providing up-to-date insights
- And provide competitive advantage in today’s digital landscape
Our client doesn’t just save time and cost – the company can focus on goals without fighting data overload.
How the solution works
The concept:
- The article is submitted as input for categorization
- The system – by using the integrated ChatGPT API – then analyzes the article to identify relevant taxons
- If found, the article is tagged within already existing categories
- If not, the system automatically generates new categories
In brief, it operates by combining predefined categorization with the ChatGPT API.
Key features:
- Dynamic management of taxons – to automatically:
– either update existing categories (to assign an article to already predefined taxons)
– or generate new categories - Real-time analysis of content – to process incoming articles and update the categories without delays
- AI categorization – for intelligent content analysis
- Trend analysis – to identify emerging topics and create new taxons
- Automated updates – to minimize manual intervention by automating taxonomy evolvement
- Prompt customization – to observe emerging trends and create relevant taxons
What’s more, the solution efficiently handles large volumes of content, which makes it scalable for growth.
Our contribution
Our team both designed and implemented the platform, from concept to completely functional solution:
- Business consulting & strategy
- Software development – the development of the core architecture, which allows dynamic updates
- ChatGPT integration – to enable the solution to perform intelligent categorization and analysis, taxonomy assignment, and detection of trends
- Prompt engineering – to guide the solution in recognizing content trends and creating “hot” taxons
- Data management and storage – a robust data pipeline for management and storage
- Real-time processing – to ensure the system can handle continuous streams of articles
Main challenges
Prompt engineering to design an efficient AI assistant
One of the challenges was crafting a prompt to navigate the integrated ChatGPT API to categorize the articles. Achieving balance between precision and adaptivity – a problem that encourages extensive experimentation.
We resolved the challenge by fine-tuning the prompt to induce nuanced understanding of content and context and minimize taxonomy-related errors.
Greater scalability to handle large volumes
Another challenge was providing the scalability to process large numbers of articles without crashes & delays. How do you design a system that’s capable of maintaining high-level performance and quick response times even with significant increases in volume?
We resolved this challenge by refining backend architecture and optimizing processing capabilities to handle data spikes.
Trend observation & detection in real-time
Trend observation & detection in real-time – a weighty technical challenge, which added further complexity.
The solution was intended to evolve while handling data categorization, and, moreover, to do it dynamically. To integrate the functionality without disrupting existing taxons, we needed to implement accurate algorithms to incorporate new information without inconsistencies.
Data management & storage, but efficient
Data management & storage without compromises – another challenge presenting serious technical hurdles.
The solution was designed to support frequent updates without corrupting overall performance and efficiency. To provide these capabilities, we implemented a database providing scalability and additional caching layers that minimize redundant queries.
Tools and technology stack
- Python
- OpenAI API
- Streamlit
Timeline:
- January 2024 – March 2024
Team:
- 1 project manager
- 1 AI engineer
Value delivered to business
Our platform is transforming content management, going beyond outdated methods to deliver greater impact. By identifying content trends and fine-tuning existing taxonomies, our solution can provide actionable insights that empower greater performance.
Key benefits:
- Content management & relevance
– Taxonomy updates, content categorization, and organization – completely automatically
– Real-time updates, which reflect current trends - Content personalization & relevance
– Content mismatches and opportunities – easily identified
– Content delivery considering individual user behavior and preferences - SEO optimization
– Always up-to-date, trending keywords to improve business visibility
– Better rankings through high-quality content delivery - eCommerce conversion
– Intelligent tagging for better product discoverability
– Thought-out offerings to match customer interest
This isn’t a platform for straightforward data management – no, it’s a solution for unlocking new opportunities in a content-rich world.
What’s more:
- You reduce both time and cost
– by minimizing manual intervention and lowering operational expenses
– and automate repetitive tasks - And increase competitive edge by adapting to dynamic market changes