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Dataforest

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The Bot System to Collect Users’ Private Offers

MNDA

Private Company
Company Type
-, United States
Location
Project work
Engagement Model
1 - 5 people
Team Size
3 - 6 Months
Duration
$21K - $50K
Budget

About

The client’s solution collects the private offers from banks and merchants accounts into one solution, so the user can see and opt to use any of them.

Challenge, approach, and impact

Data Collection System Development

Developing a 16-bot system to collect private offers from banks and merchants accounts into one solution, allowing users to view and utilize the offers conveniently.

KPIs Implementation

Achieving KPI #1 by integrating with 6 American Banks and KPI #2 by ensuring users can log in, collect, and process requests within 4 minutes.

Client Needs Fulfillment

Building a secure system to collect data from American banks' users without security violations, storing the collected data in a unified solution, and expanding to include USA merchants.

Challenges & Solutions

1. Challenge: Developing undetectable bots to gather commercial offers from end users' bank accounts. Solution: Creating unique bot solutions for each bank to securely access accounts and retrieve information. 2. Challenge: Building a custom Load Balancer for efficient workload distribution. Solution: Engineering a custom Load Balancer based on AWS. 3. Challenge: Overcoming anti-bot protections with human-like behavior and custom captcha bypass methods.

Project Results

Successfully expanding the automated bot system to include 13 merchant bots and 6 banking bots, empowering users to access both banking and commercial offers in one solution. Ensuring cohesive data gathering and storage by all 18 bots in a highly secure environment, leading to fast and seamless service. Demonstrating impressive scalability from 5 to 18 bots, enabling substantial service expansion.

How we built

Banking & Trading Platforms
E-Commerce

Testimonials

Anonymous

Dataforest

Verified Testimonial

This project was a strong example of building secure and scalable automation under strict constraints. We worked with multiple banking systems, each requiring a custom bot approach, anti-bot handling, and careful orchestration. The final system proved reliable, fast, and easy to scale, expanding from banking integrations to merchant platforms without compromising performance or security.

Team structure

Client team

Client

Product Stakeholder

The client stakeholders were working closely with the team at Dataforest

Agency team

Data Engineer

Production

Backend Developer

Production

Product Manager

Production

Business Analytics

Production

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