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Podcast Platform Boosts Engagement 7× Using AI Recommendations

Podcast Platform Boosts Engagement 7× Using AI Recommendations

A leading podcast platform partnered with Dataforest to replace manual recommendations with an AI-powered personalization engine. The new system analyzes user behavior and context in real time to deliver tailored suggestions in under 0.5 seconds, handling up to 20 recommendations per second. This resulted in 7× higher user engagement, enhancing listener experience and significantly increasing the client’s revenue.

7

×

higher user engagement

<

0.5

secs

average recommendation delivery speed

~

20

recommendations/sec throughput

The client is a leading web and mobile podcast platform in Saudi Arabia, recognized across the MENA region for its high-quality, authentic journalism in text, visual, and audio formats.

Databricks

Databricks

TensorFlow

TensorFlow

Spark

Spark

PostgreSQL

PostgreSQL

Databricks
vector search

Databricks
vector search

THE CHALLENGE

The podcast platform faced very limited personalization due to its manual recommendation process

The podcast platform relied on static, manually curated recommendations that couldn’t adapt to user behavior. This restricted engagement, slowed revenue growth, and left the platform behind competitors who leveraged dynamic personalization.

No Adaptability to User Behavior

Recommendations weren’t responsive to user preferences, resulting in low engagement and poor discovery of new content.

Missing Real-Time Data Infrastructure

The system lacked pipelines to process data instantly, preventing real-time insights and timely content delivery.

Cold Start Problem for New Users

With no recommendation system for users without history, new listeners had a poor first experience.

Scalability Gaps

The legacy approach couldn’t support rapid growth in users and content, limiting future expansion.

Boost Engagement 7× with AI-Powered Personalization

Validate your strategy with a 1-Week PoC

Get pricing

Boost Engagement 7× with AI-Powered Personalization

Validate your strategy with a 1-Week PoC

Get pricing

THE SOLUTION

AI-Powered Recommendation Engine with 7x Engagement Boost

We built a flexible recommendation model that processes diverse user signals in real time. It delivers highly relevant podcast suggestions, improving user engagement by 7x and enabling scalable growth.

Automated Data Pipelines

Developed real-time ETL pipelines to collect and process behavioral data, ensuring accuracy and enabling consistent recommendations.

Contextual Cold Start Solution

Used contextual data such as time, location, and language to deliver relevant suggestions for new users without history.

Modular, Scalable Architecture

Created a system with multiple recommendation modules and a ranking model that scales with users and content growth.

Cross-Signal Personalization

Integrated listening history, comments, and metadata to generate recommendations across all content types, boosting relevance.

THE RESULT

AI-Powered Personalization: 7x More Podcast Engagement and 30% Higher User Interaction

A leading podcast platform in Saudi Arabia and the MENA region needed to replace its static, manually curated recommendations to drive growth and user satisfaction. DATAFOREST delivered a scalable AI-powered recommendation engine that personalizes podcast suggestions in real time based on user behavior, preferences, and context.

We developed a modular system with a learning-based ranking model and a real-time data pipeline to process user activity efficiently. Key challenges included scaling architecture, integrating diverse interaction signals, and solving the cold start problem for new users. It was addressed by combining behavioral data with contextual metadata (e.g., time, language, location). Recommendations now auto-update every 48 hours, ensuring ongoing relevance and eliminating manual work.

This transformation enabled the podcast to personalize content at scale, increase user satisfaction, boost revenue, and future-proof its platform with a flexible, data-driven solution.

<0.5 sec

average recommendation delivery speed

~20

personalized recommendations processed per second

higher user engagement compared to the manual system (A/B tested)

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Podcast Platform Boosts Engagement 7× Using AI Recommendations

Steps of providing data scraping services

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It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.
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Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.  At this stage, we need to ensure that we understand the full scope of the project. Receive from you or perform a set of interviews and prepare the following documents: list of features with detailed description and acceptance criteria; list of fields that need to be scraped, solution architecture. Ultimately we make a project plan which we strictly follow. We are a result-oriented company, and that is one of our core values as well.
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After quality assurance tests are completed, we deliver data and solutions to the client. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While developing and crawling data, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.
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We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

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Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.
Analysis icon

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.  

At this stage, we need to ensure that we understand the full scope of the project. We receive from you or perform a set of interviews and prepare the following documents: integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.
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Solution development

At this stage, we build ETL pipelines and necessary APIs to automate the process. We attract our DevOps team to build the most efficient and scalable solution. Ending up with unit tests and quality assurance tests to ensure that the solution is working properly. Focus on Results is one of our core values as well.
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Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.
Support improvement icon

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Steps of providing web applications services

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Web development discovery

In the initial stage of the web-based development project, professional business analysts make detailed documentation of the project requirements and the approximate structure of the future web application. DATAFOREST is a custom web application development agency, guided by extensive experience in multiple industries. We give you detailed project documentation and then assemble the team according to your time and budget.
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UX and UI design

Based on your wishes, the needs of your target audience, and the best web application design and development practices, our UX and UI experts create an aesthetically pleasing and user-friendly interface for your app to satisfy even the most demanding users.
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The Way We Deal with Your Task and Help Achieve Results

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Step 1 of 5
Free consultation

It's a good time to get info about each other, share values, and discuss your project in detail. We will advise you on a solution and help you understand if we are a perfect match for you.
Analysis icon

Step 2 of 5
Discovering And Feasibility Analysis

One of our core values is flexibility. Hence, we work with either one-page high-level requirements or a whole pack of tech docs. In AI demand forecasting case studies, there are numerous models and approaches, so at this stage, we perform a set of interviews to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create a solution architecture, a project plan, and a list of insights or features to achieve.
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Step 3 of 5
Solution Development

The work starts with data gathering, data cleaning, and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for further development. Ultimately, we interpret the results. Nevertheless, demand forecasting solution modeling is a process requiring many back-and-forth iterations. We are result-focused, as it's also one of our core values.
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Step 4 of 5
Solution Delivery

AI demand forecasting solutions can be a list of insights or models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect the client's participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high level of communication is also our core value.
Support improvement icon

Step 5 of 5
Support And Continuous Improvement

We understand how crucial the solutions that we code for our clients are! We aim to build long-term relations, providing guarantees and supporting agreements. Moreover, we are always happy to assist with further developments, and statistics show that 97% of our clients return to us with new projects.

The way we deal with your issue and achieve result

Consultation icon

Free consultation

Step 1 of 5

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.
Analysis icon

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.  

Depending on project objectives, DevOps activity requires auditing the current approach, running metrics measurement, performing monitoring and checking logs. By having a set of interviews, we ensure that we understand the full scope of the project. Ultimately we make a project plan which we strictly follow. We are a result-oriented DevOps service provider company, and that is one of our core values as well.
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Step 3 of 5

Solution development

At this stage, our certified DevOps engineers refine the product backlog. We deliver great results within digital transformation, cost optimization, CI/CD setup, containerization, and, last but not least, monitoring and logging. We are a result focused company – it’s one of our core values.
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Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. By the way, a high-level of communication is also our core value.
Support improvement icon

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Success stories

Real-Time AI Voice Agent for Cold Calling

We developed a real-time voice-to-voice AI agent for the client, one of the top affiliate CPA networks. It delivers human-like conversations, handles noisy environments, and integrates with the client’s CRM and ATS. Trained on sales data, it boosts performance with <450 ms response time and a 1:1–1.5 sales quality ratio vs. human agents.
1:1–1.5

Sales quality ratio vs. human agents

<450ms

voice bot response latency — faster than human reaction time

Real-Time AI Voice Agent for Cold Calling preview
gradient quote marks

AI-Powered Cold Calling: Real-Time Voice-to-Voice Conversations

Improving Chatbot Builder with AI Agents

A leading chatbot-building solution in Brazil needed to enhance its UI and operational efficiency to stay ahead of the curve. Dataforest significantly improved the usability of the chatbot builder by implementing an intuitive "drag-and-drop" interface, making it accessible to non-technical users. We developed a feature that allows the upload of business-specific data to create chatbots tailored to unique business needs. Additionally, we integrated an AI co-pilot, crafted AI agents, and efficient LLM architecture for various pre-configured bots. As a result, chatbots are easy to create, and they deliver fast, automated, intelligent responses, enhancing customer interactions across platforms like WhatsApp.
32%

client experience improved

43%

boosted speed of the new workflow

Botconversa AI
gradient quote marks

Improve chatbot efficiency and usability with AI Agent

LLM-Powered Recommendation System

An Israeli startup is transforming U.S. service providers' personalized offerings. Dataforest scaled the project from prototype to a full web app with advanced ML, LLMs, and RAG fine-tuning. Managing 100,000+ products for 50,000+ customers, it delivers precise recommendations and revenue forecasts, maximizing sales opportunities
<1 min

tailored recommendations delivery

100,000+

products supported by the platform

LLM-Powered Recommendation System
gradient quote marks

LLM-Powered Recommendation System

Real-Time AI Voice Agent for Cold Calling

We developed a real-time voice-to-voice AI agent for the client, one of the top affiliate CPA networks. It delivers human-like conversations, handles noisy environments, and integrates with the client’s CRM and ATS. Trained on sales data, it boosts performance with <450 ms response time and a 1:1–1.5 sales quality ratio vs. human agents.
1:1–1.5

Sales quality ratio vs. human agents

<450ms

voice bot response latency — faster than human reaction time

Real-Time AI Voice Agent for Cold Calling preview
gradient quote marks

AI-Powered Cold Calling: Real-Time Voice-to-Voice Conversations

Improving Chatbot Builder with AI Agents

A leading chatbot-building solution in Brazil needed to enhance its UI and operational efficiency to stay ahead of the curve. Dataforest significantly improved the usability of the chatbot builder by implementing an intuitive "drag-and-drop" interface, making it accessible to non-technical users. We developed a feature that allows the upload of business-specific data to create chatbots tailored to unique business needs. Additionally, we integrated an AI co-pilot, crafted AI agents, and efficient LLM architecture for various pre-configured bots. As a result, chatbots are easy to create, and they deliver fast, automated, intelligent responses, enhancing customer interactions across platforms like WhatsApp.
32%

client experience improved

43%

boosted speed of the new workflow

Botconversa AI
gradient quote marks

Improve chatbot efficiency and usability with AI Agent

LLM-Powered Recommendation System

An Israeli startup is transforming U.S. service providers' personalized offerings. Dataforest scaled the project from prototype to a full web app with advanced ML, LLMs, and RAG fine-tuning. Managing 100,000+ products for 50,000+ customers, it delivers precise recommendations and revenue forecasts, maximizing sales opportunities
<1 min

tailored recommendations delivery

100,000+

products supported by the platform

LLM-Powered Recommendation System
gradient quote marks

LLM-Powered Recommendation System

Reporting & Analysis Automation with AI Chatbots

The client, a water operation system, aimed to automate analysis and reporting for its application users. We developed a cutting-edge AI tool that spots upward and downward trends in water sample results. It’s smart enough to identify worrisome trends and notify users with actionable insights. Plus, it can even auto-generate inspection tasks! This tool seamlessly integrates into the client’s water compliance app, allowing users to easily inquire about water metrics and trends, eliminating the need for manual analysis.
100%

of valid input are processed

<30 sec

insights delivery

Klir AI
gradient quote marks

Automating Reporting and Analysis with Intelligent AI Chatbots

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