AI-Powered Web Platform for Data-Driven E-commerce Decisions

AI-Powered Web Platform for Data-Driven E-commerce Decisions

Dropship.ai is a powerful data intelligence platform that helps e-commerce businesses identify profitable products, analyze market trends, and optimize sales strategies. Using large-scale data scraping, AI-driven insights, data enrichment solutions, integrations with Shopify, Meta, and Stripe, it enables smarter product decisions and drives revenue growth.

E-commerce

Web and mobile development

SaaS Platform

E-commerce

Web and mobile development

SaaS Platform

3M+

total unique users

200K+

active users per month

About the client

A former dropshipper built Dropship.ai to tackle the real-world challenges he faced during his career. Today, the platform powers 3M+ users with AI-driven insights on winning products, sales performance, and advertiser activity, using enriched data and AI-driven tools to enable faster, smarter campaign optimization and revenue growth.

Tech stack

AWS

Python

ReactJS

Kafka

Sentence Transformers

The client's needs

The client required a scalable, high-performance platform to process billions of daily e-commerce datapoints from sources like Facebook, Shopify, and AliExpress. The goal was to deliver real-time, AI-driven insights—identifying trending products, optimizing ad strategies, and enabling competitor benchmarking—to empower entrepreneurs with fast, data-driven decisions in a highly competitive market.

Challenges & solutions

Challenge

Build a scalable, user-friendly web platform with advanced, interactive data analysis tools, along with a browser extension that delivers real-time data enrichment for users.

Solution

Developed a high-performance web application paired with a custom Chrome extension for live product and ad research. Seamlessly integrated with Meta and Shopify, the solution offers intuitive UX and powers the backend with enriched data—featuring dozens of interactive analysis tools to support faster, smarter decisions.

Challenge

The platform had to process hundreds of millions of web pages daily from Instagram, Facebook, Shopify, and AliExpress—alongside user-generated data captured through a custom Chrome extension we developed—demanding high speed, accuracy, and scalability.

Solution

Deployed high-performance data scraping pipelines with direct integrations to Meta APIs, Shopify, and AliExpress, enabling real-time access to high-value product and market data and powering intelligent, data-driven decisions.

Challenge

The platform required a robust data architecture to manage and scale massive datasets from multiple sources—supporting high-volume input traffic while ensuring fast, reliable access to enriched data for real-time insights.

Solution

Designed and deployed a cost-efficient, scalable infrastructure using event-driven systems like Kafka and Flink, along with purpose-fit databases such as PostgreSQL, Elasticsearch, Cassandra, and Redis, delivering high performance, flexibility, and long-term scalability.

Challenge

The platform needed to transform massive volumes of unstructured product and ad data into clear, actionable insights to support smarter, revenue-focused decision-making.

Solution

Built AI-driven models for data cleaning, anomaly detection, enrichment, and predictive analytics. Designed to interpret unstructured data, these models uncover patterns in sales, refunds, and advertising, enabling insight-driven decisions by detecting indirect behavioral signals across channels.

Challenge

The platform needed to process and analyze billions of images, videos, and text descriptions to enable accurate product categorization and intelligent, AI-powered search.

Solution

Fine-tuned open-source AI models to deliver high-precision image recognition and product classification. This cost-efficient solution enhanced trend detection and enabled fast, on-demand search across visual and textual data—driving better discovery and decision-making at scale.

Challenge

Operating in a fast-paced, constantly evolving environment, the client needed a highly skilled team and scalable infrastructure to support the continuous innovation.

Solution

Assembled a flexible, high-performing team spanning Business and Data Analytics, Data Engineering, AI/Data Science, DevOps, Web Development, and QA. This cross-functional setup ensures reliable platform performance while driving continuous improvement—proactively researching new features, suggesting updates, and uncovering opportunities to boost business outcomes.

Challenge

Solution

Challenge

Solution

Results

Dataforest developed a scalable, enterprise-grade DaaS (Data-as-a-Service) platform that empowers e-commerce businesses to identify trending products and gain market insights, powered by enriched datasets, real-time analytics, and deep platform integrations. It helps users identify profitable products, optimize their sales strategies, and maximize revenue for their campaigns.

Now known as Dropship.ai, the platform has become one of the most widely adopted AI tools in e-commerce—serving 3M+ unique users and 200K+ monthly active users. It tracks more than 600M products, monitors 3M+ stores, and analyzes 1M+ advertisers, delivering unmatched visibility into global market trends and product performance.

With seamless integration into platforms like Shopify, Meta and Stripe, Dropship.ai accelerates product discovery, optimizes ad performance, and improves conversion rates, driving faster execution of sales strategies and measurable revenue growth.

If we experience any problems, they come back to us with good recommendations on how the project can be improved.

Josef G.

CEO, Founder Software Development Agency

Steps of providing
data scraping services

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 try to help to understand if we are a perfect match for you.

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. 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.

Step 3 of 5

Solution development

At this stage, we develop the scraping engine core logic. We run multiple tests to ensure that the solution is working properly. We map the fields and run the scraping. While scraping, we keep the full raw data so the final model can be enlarged easily. Ultimately we store data in any database and run quality assurance tests.

Step 4 of 5

Data delivery

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.

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.

How we provide data integration solutions

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 try to help to understand if we are a perfect match for you.

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.

Step 3 of 5

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.

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 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.

Step 5 of 5

Support and continuous improvement

Steps of providing web applications services

Step 1 of 7

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.

Step 2 of 7

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.

Step 3 of 7

Web-based application development

At DATAFOREST we are following the best programming design principles and approaches. Being a data engineering company, we build high load platforms, with a significant level of flexibility and result orientation. We keep our deadlines and follow SOC 2 compliance requirements.

Step 4 of 7

Integration

With DATAFOREST, integrating the application into your business won’t stop your processes for a minute. We provide seamless integration with your software infrastructure and ensure smooth operation in no time.

Step 5 of 7

Quality assurance

We use a multi-level quality assurance system to avoid any unforeseen issues. Working with DATAFOREST, you can be confident that your web app development service solutions arrive to the market polished and in full compliance with all certification requirements.

Step 6 of 7

24/7 support

Once a product is released to the market, it’s crucial to keep it running smoothly. That’s why our experts provide several models of post-release support to ensure application uptime and stable workflows, increasing user satisfaction.

Step 7 of 7

Web app continuous improvement

Every truly high-quality software product has to constantly evolve to keep up with the times. We understand this, and therefore we provide services for updating and refining our software, as well as introducing new features to meet the growing needs of your business and target audience.

The way we deal with your task and help achieve results

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 try to help to understand if we are a perfect match for you.

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.

In Data Science, there are numerous models and approaches, so at this stage we perform a set of interviews in order to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create solution architecture, a project plan, and a list of insights or features that we have to achieve.

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 the further development. Ultimately, we interpret the results. Nevertheless, data modeling is about a process that requires lots of back and forth iterations. We are result focused, as it’s one of our core values as well.

Step 4 of 5

Solution delivery

Data Science solutions can be a list of insights or a variety of different models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect 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.

Step 5 of 5

Support and continuous improvement

The way we deal with your issue and achieve result

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.

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.

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.

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.

Step 5 of 5

Support and continuous improvement

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

Email marketing SaaS platform

DATAFOREST built a scalable SaaS multivendor platform for a UK based job advertising company, tailored for the US market expansion. It optimizes email marketing with an advanced distribution algorithm for high deliverability and engagement. Key features included an SEO-optimized website, multi-domain management, and efficient email marketing, driving organic traffic and boosting affiliate earnings.

50K+

leads managed on the platform

24,5%

conversion rate

View case study

Email marketing SaaS platform

E-commerce scraping

The dropshipping company needed a way to automatically monitor prices and stock availability for over 100,000 products from over 1,500 stores. We created a system using custom scripts and a web interface that could check 60 million pages daily. This led to a reduction in manual work and errors, and improvements in customer experience and a $50-70k increase in monthly profits.

1000h+

manual work reduced

60 mln

pages processed daily

Jonathan Lien

CEO Advanced Clear Path, Inc., E-commerce Company

View case study

They always find cutting-edge solutions, and they help bring our ideas to life.

Data-driven marketing

We created a solution that helped optimize the customer base to get the most out of the customer data. This solution notifies the client about the services/goods, which they would likely buy, according to the gathered information.

20%

sales growth

200%

traffic boost

Jeremy Groves

CEO ThinkDigital, Digital and Marketing Agency

View case study

They developed solutions that brought value to our business.

Bank Data Analytics Platform

The Bank Data Analytics Platform project aims to develop a web-based application for the Client and its customers to query and analyze data relating to various banks and other financial institutions. The project involves building an interactive B2B web app with custom dashboards and analytics features, as well as using AI functionality to empower the application's development and analytics capabilities.

30+

system integrations

19%

CX boost