Spotlights:
AI-Generative Media & Brand Solutions
AI-Generative Enterprise enables Media companies and Brands to optimize media production with Generative AI, while handling the constraints of dated information, uncertain engagement and output
OUR PIONEERING CLIENTS
Products
Media Content Druid Platform
01
Drives 40-60% Additional Efficiency in Media Production
​
The Druid Framework uses Interactive and Retrieval supported LLMs viz. GPTS to create bespoke workflows for content types such as Articles, Newsletters, Opinion pieces, Listicles, How-To articles, Technical Review & Comparisons, Editorial and Click Driving content. For Publishers and Brands, Druid Platform can integrate with CMS' to synch new content.
Refresh Workflow
02
Realize Latent Potential of Aging Content with Refresh Workflows
​
Aging content holds great potential for media companies but is often under-leveraged as teams focus more on new production. The Druid platform identifies target content and gets approvals from editorial team with alternative revisions generated by the Refresh customizable module. Approved content is updated automatically in the CMS.
Introducing! Interactive Retrieval Augmented (IRAG) © Generative AI
03
LLMs do not work well for Enterprise applications out of the box given that they cannot exactly recall their training data (non-deterministic) and their data is often outdated. In addition, for any use case there are a wide range of edge-cases to be handled, as well as the organizational and personal preferences of writers to be accounted for. AI-Generative's IRAG creates an iterative process that emulates the human process for writing content.
Bespoke Workflows
IRAG features a unique meta-workflow for each content type, such as different article formats. This workflow is adaptable to client-specific needs, allowing for customization and extensibility based on the unique requirements of a media or brand entity
​
Iterative development
At the heart of IRAG is its iterative approach to content creation. The platform engages in a dynamic process of context building and content generation, where user feedback and approval are integral. This ensures that the content evolves and refines with each iteration, aligning closely with the user's vision and objectives
CONTEXT RETRIEVAL
IRAG integrates both corporate and public data sources, harnessing corporate data via APIs and vector databases, along with internet data sources. This rich tapestry of information provides the LLM with external context, enabling it to utilize all available data for generating more accurate and relevant content
SEAMLESS
INTEGRATION
The platform seamlessly integrates with Content Management Systems (CMS) and vector databases. For instance, when generating a listicle, IRAG can load examples from the corporate database, use these to create a new listicle based on guidelines, and insert new content in the CMS
LLM Driven Capabilities for Brands & Publishers
01.
Semantic & Hybrid Search: Context aware searching of documents and images
02.
AI Chat Context: Corporate + current public added
context to LLM for best results
03.
Recommender: Advanced image + text based content reco's on every page/ section
04.
Image Classification: Rate similarity of faces and images for personalized content
