With the advent of Artificial Intelligence (AI), Machine learning (ML), Natural Language Processing(NLP), and Robotic Process Automation (RPA), businesses can streamline workflows, cut costs, and foster sustainable growth amid market challenges. Despite advancements in enterprise resource planning (ERP) systems, a … Read More
AI For Telecommunication
AI for Media & Telecommunication
Telecoms shift from providing mere connectivity to becoming comprehensive service providers for increased customer acquisition. Leveraging existing customer bases makes offering personalized content easier, enabling a seamless transition into a complete package—connectivity and content—for robust business growth. Exceptional machine learning capabilities are crucial for enhancing the customer experience in this evolving landscape.
Automated metadata enrichment
- Automated metadata is crucial for telecoms, facilitating a personalized user experience by streamlining labeling during hosting and collecting in-depth user interaction data.
- RecoSense's knowledge graph empowers telecoms with automated rich metadata generation, reducing costs, eliminating manual work, and minimizing error rates in the process.
In-depth user profile with identity resolution
- In the absence of third-party cookies, identity resolution is vital for precise user identification, enabling the implementation of effective machine learning techniques.
- RecoSense's customer data platform provides telecommunication organizations with a complete user overview and campaign performance insights, preventing business losses associated with anonymous data.
PayTV - Auto playlist generation and personalized homepage
- For PayTV, automated playlists and personalized homepages, facilitated by RecoSense, enhance customer satisfaction and engagement, especially in the context of limited remote control operation.
- Leveraging RecoSense's personalization expertise with shared devices, companies can go a step further by enabling customized homepages for different users, a crucial strategy for expanding subscription bases while retaining existing customers.
- Achieving effective AI personalization demands expertise across diverse techniques and the ability to optimize for production, enhancing user experience by recommending relevant items.
- RecoSense's services aid organizations in delivering dynamic and monitored personalized experiences, ensuring ongoing effectiveness of models throughout their lifecycle, recognizing personalization as an iterative process rather than a one-time investment.
Content recommendation engine - Subscription plans
- Crafting packages to suit specific user groups is crucial for both the general public and businesses. Automating the recommendation of the best package based on customer understanding provides a competitive market advantage.
- RecoSense's deep expertise in recommendation engines extends to automating the challenging task of pricing solutions, enabling companies to streamline and optimize their pricing strategies effortlessly.
Ads network with FPD
- With the phasing out of third-party cookies, ad networks face challenges. Telecommunication organizations must maximize limited first-party data for targeted ads, transitioning to a new landscape.
- RecoSense's capability in creating ad networks, as effective as traditional third-party cookieRecoSense’s capability to create ad networks that are equally effective as the current third-party cookies data networks allow companies to continue the growth of businesses with ease.
- Offering what users want automatically is powerful, but RecoSense's BERT-based model takes it a step further, understanding user intent for effective results in text or voice searches.
- Telecommunication companies leveraging RecoSense must ensure their content appears in varied but relevant search results to prevent business loss caused by a decline in content performance.
- Augmenting business intelligence with AI, RecoSense offers unique insights into user information and real-time performance data.
- RecoSense integrates robotic process automation, allowing companies to effectively leverage data from diverse sources. Insights include trigger content for subscriptions, advertising campaign performance, user behavior, traffic patterns, and social media signals.
- Privacy concerns limit data collection, reshaping the advertising landscape. Hyper-targeting demands a blend of rich metadata, advanced analytics, personalization, first-party ad networks, identity resolution, and recommendations for effective advertising.
- RecoSense leverages years of experience to comprehend customer demands, deploying end-to-end machine learning services. This expertise makes hyper-targeting in advertising feasible, even in the face of evolving privacy regulations.
With evolving digital transactions and sophisticated fraud techniques, the need for robust fraud detection mechanisms is equally increasing. One area where this is particularly pertinent is in identifying fake bank statements, a common tool fraudsters use to manipulate financial information. … Read More
The investment banking sector is currently grappling with several challenges. These include dealing with capital charges, digital adoption, rigid cost structure, intricate and layered technological stacks, and increased regulatory demands. As a result, various investment banks shifted their emphasis from … Read More