AI Multilingual Chatbot for Financial Assistance
24/7 multilingual
support enabled through an AI chatbot.
Lower operational costs
achieved by automating FAQs and loan pre-qualification assistance.
Industries
Industries We Serve
Cross-industry engineering experience across regulated and high-growth sectors.
All IndustriesSuccess Story
Supporting a Content Amplification Platform
Zoolatech helped evolve inPowered's content amplification platform by enhancing distributed services that optimize content distribution across multiple advertising channels.
Multi-channel reach
across major native advertising and social platforms.
Scalable architecture
supporting distributed services and growing data volumes.
Technologies
Java
Dropwizard
Node.js
Angular
AWS ECS
Docker
MySQL
Redis
Elasticsearch
REST APIs
Expertise
Platform engineering
Fullstack engineering
API development
Client Overview
inPowered
inPowered is a content amplification platform that helps brands distribute owned, earned, and paid content across native advertising and social media channels.
The platform uses audience targeting, campaign optimization, and machine learning techniques to improve engagement outcomes for enterprise brands and advertising agencies.
Industries
Advertising technology (AdTech)
Headquarters
San Francisco, CA, USA
Company size
100+ employees
The Challenge
Scaling Audience Optimization Increased Platform Complexity
As the platform expanded across advertising channels and audience segments, maintaining performance, scalability, and operational efficiency became increasingly complex. The platform needed to support growing data volumes and distributed services while enabling continuous optimization.
Have a Similar Challenge?
Looking to scale a high-growth digital platform while maintaining reliability and performance?
Growing infrastructure complexity
The platform relied on multiple distributed services, creating additional operational and maintenance requirements.
Large-scale audience testing
Thousands of audience segments were continuously evaluated to identify the most effective targeting strategies.
Expanding channel ecosystem
Supporting multiple advertising and social platforms increased integration and platform management complexity.
Continuous optimization demands
The business model depended on efficiently converting traffic into measurable engagement outcomes, requiring ongoing platform improvements.
Have a Similar Challenge?
Looking to scale a high-growth digital platform while maintaining reliability and performance?
Why They Chose Us
Demonstrating Engineering Ownership in a Complex Environment
The engagement highlighted Zoolatech’s ability to contribute to distributed systems operating at scale while collaborating closely with product and engineering leadership.
Distributed systems expertise
The team supported services operating across multiple domains, APIs, databases, and cloud environments.
Product-focused delivery
Engineers contributed across the software development lifecycle, including design, implementation, testing, and production operations.
Zoolatech is a senior-heavy engineering firm with Silicon Valley roots and a Miami HQ, specializing in legacy modernization, system re-architecture, and AI deployment to drive long-term, compounding value.
2017
Year Founded
600+
Employees
96%
Client Satisfaction
Workflow
Supporting Continuous Platform Evolution
The engagement followed an iterative delivery model focused on platform enhancement and operational reliability.
Phase 1
Platform assessment
The team aligned with architects and engineering stakeholders to understand platform requirements and priorities.
Phase 2
Service enhancement
Engineers supported backend services and platform capabilities while maintaining code quality and architectural consistency.
Phase 3
Testing and validation
Changes were validated through development lifecycle activities, reviews, and testing processes.
Phase 4
Production operations
The team participated in deployments, operational support, and ongoing platform maintenance.
Phase 5
Continuous improvement
Platform capabilities were refined through iterative development and optimization initiatives.
The engagement supported the evolution of a content amplification platform operating across multiple advertising channels.
Solution
Enhancing Distributed Advertising Platform Capabilities
Zoolatech supported the ongoing development and operation of a distributed platform designed to optimize content distribution, audience targeting, and engagement measurement.
Distributed microservices architecture
The platform operates through independent REST-based services, allowing teams to manage functionality across multiple business domains.
Multi-channel content distribution
The solution supports content promotion across numerous advertising and social media channels through a single platform.
Audience optimization workflows
Machine learning-driven processes help identify and prioritize audience segments for campaign testing and optimization.
Cloud-native deployment model
Services are containerized and deployed across AWS infrastructure to support scalability and operational resilience.
Results
A Scalable Foundation for Continued Growth
The engagement strengthened the platform's ability to support continued growth, distributed services, and ongoing optimization initiatives.
Ongoing platform reliability
The distributed architecture enabled continued operation across multiple advertising channels and services.
Support for audience optimization
The platform continued to evaluate and optimize audience targeting strategies at scale.
Scalable engineering foundation
The architecture provided a framework for future enhancements, integrations, and machine learning initiatives.
Empowerment & Value
Positioning the Platform for Continued Expansion
The client can continue evolving platform capabilities while supporting additional channels and optimization initiatives.
Future channel growth
The platform architecture supports the introduction of additional advertising and distribution channels.
Foundation for advanced analytics
The existing infrastructure enables continued investment in machine learning, optimization, reporting, and data initiatives.
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