Deep Talk is a no-code deep learning platform to analyze text and conversational data
🔥🔥 What will you find in Deep Talk?
Tools to analyze general text and conversational data
With a few clicks you will know what your customers are talking about
Topic detection for conversations
Topic trends and evolution
Group different topics to follow them (Sales, Complaints, Leads, etc)
Wordcloud for every topic
🦾💪 Who uses Deep Talk?
Customer success teams who want to detect what kind of issues people are experimenting with, new features requested, the most frequent topics people are talking about.
Customer experience teams who want to detect complaints, and why the people are unsatisfied.
Sales teams who want to detect sales opportunities in conversations, mails, chats
Support teams who want to detect the most frequent issues or problems the people are having
AI/Analytics teams who don't want to spend months building and deploying NLP/DL models to process their data or building chatbots from zero
Deep-Talk.ai's answer:
Turn text into analytics with a no-code platform. Transform customer and employee feedback from any source into actionable data.
Based on our record, Apache Kafka seems to be more popular. It has been mentiond 120 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / about 2 months ago
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 3 months ago
Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 3 months ago
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 3 months ago
RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 3 months ago
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