Frontline UI: Enhancing Connect Our Kids’ SaaS Experience

At Connect Our Kids, innovation isn’t just a goal—it’s a necessity. When they set out to enhance the development and maintenance of Connect Our Kids, a platform dedicated to transforming child welfare through technology, they knew they needed a team that could elevate their SaaS product from functional to exceptional. That’s where we came in.

Mission: Elevate the SaaS Experience

Big Armor needed a robust, scalable, and high-performing solution to ensure Connect Our Kids was not only responsive but also optimized for cross-browser compatibility and seamless user experiences across mobile and desktop. Our team was brought in to take the platform to the next level—faster, smarter, and more intuitive than ever before.

Our Approach: Building from the Ground Up

We took full ownership of the front-end SaaS architecture, ensuring the system was efficient, intuitive, and built for scale. Our process was methodical and laser-focused on delivering a best-in-class SaaS application with enterprise-grade security, optimized performance, and seamless integrations.

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Product URL: connectourkids

Front-End Development

• We reimagined the UI/UX with Angular 8+, crafting a responsive, modern, and highly interactive web application.
• Wireframes and mockups weren’t just translated into code; they were transformed into engaging digital experiences.

Seamless Integrations

• Built a smooth GraphQL-powered API integration with Apollo to enhance real-time data fetching and optimize client-server communication.
• Ensured effortless back-end connectivity, making data flow like a dream.

Agile Development & CI/CD Automation

• Implemented lazy loading, code splitting, and caching strategies to supercharge application speed.
• Fine-tuned every element for blazing-fast load times and ultra-smooth navigation.

Security First

• Integrated enterprise-grade security protocols, proactively mitigating risks like XSS and CSRF attacks.
• nsured the application met the highest standards of SaaS security compliance.

Agile Development & CI/CD Automation

• Built and maintained a continuous integration & deployment pipeline, ensuring seamless updates and minimal downtime.
• Leveraged Git for version control, ensuring collaborative, conflict-free development.

Bug-Squashing & Continuous Improvement

• Proactively identified and eliminated UI bugs, ensuring a flawless user experience.
• Adopted a data-driven approach to UX enhancements, leading to an intuitive and frustration-free interface.

The Impact: A Game-Changer for Big Armor & Connect Our Kids

The transformation was nothing short of revolutionary:

• Enhanced User Experience: Faster, more intuitive, and mobile-friendly.
• Performance Gains: Significant reductions in load times and latency.
• Cross-Browser Compatibility: No more glitches—just smooth interactions across all devices.
• Security Reinforcement: Fortified against cyber threats, ensuring data integrity and user trust.
• Agile & Scalable SaaS Infrastructure: A foundation built for growth and innovation.

ROI %

400

Tech Stack That Makes It All Happen:

• Angular 8+
• TypeScript
• Apollo GraphQL
• Git
• CI/CD

Development Journey

August 15, 2022

Project Kickoff 🚀

• Conducted initial strategy meetings with the Connect Our Kids team.
• Defined core objectives: UI/UX redesign, performance optimization, cross-browser compatibility.
• Created a high-level roadmap and development timeline.

September 5, 2022

Architecture & UI/UX Design Begins 💻

• Designed the system architecture using Angular 8+.
• Developed wireframes and prototypes based on existing user feedback.
• Planned API integrations with Apollo GraphQL for seamless backend connectivity.

October 3, 2022

Core Development Begins 🛠️

• Implemented a responsive and interactive UI using Angular framework.
• Integrated front-end components with Apollo GraphQL.
• Developed authentication and user role management system.

November 14, 2022

Performance Optimization Phase ⚡

• Implemented lazy loading and code splitting for improved efficiency.
• Optimized API calls and database queries for faster response times.
• Conducted security enhancements to mitigate XSS and CSRF vulnerabilities.

December 12, 2022

Cross-Browser Compatibility Testing 🔍

• Conducted extensive testing on multiple browsers (Chrome, Firefox, Safari, Edge).
• Fixed UI inconsistencies and responsiveness issues.
• Ensured accessibility compliance with WCAG standards.

January 16, 2023

Beta Testing Begins 📢

• Launched beta version for a select group of users.
• Gathered feedback on UI/UX, performance, and usability.
• Identified and resolved reported bugs and performance bottlenecks.

March 6, 2023

Bug Fixing & Security Enhancements 🛡️

• Addressed reported bugs and refined UI elements.
• Strengthened authentication mechanisms and encryption protocols.
• Conducted penetration testing and security audits.

April 10, 2023

CI/CD Pipeline Implementation 🔄

• Automated deployment process using CI/CD pipelines.
• Improved version control with Git for better team collaboration.
• Streamlined rollback strategies for error recovery.

June 5, 2023

Final UI/UX Enhancements 🎨

• Refined UI based on beta testing feedback.
• Improved mobile responsiveness for a seamless user experience.
• Conducted usability testing to ensure a smooth workflow.

July 17, 2023

Final Testing & Deployment Readiness ✅

• Conducted full-scale integration testing.
• Verified system scalability and load performance.
• Prepared detailed documentation for future development and maintenance.

September 4, 2023

Official Public Launch 🎉

• Successfully launched the fully optimized and redesigned application.
• Initiated a marketing push to onboard new users.
• Provided ongoing monitoring for stability and user adoption

Post-Launch Enhancements & Scaling

• Monitored analytics to assess user engagement.
• Collected post-launch feedback for iterative improvements.
• Planned next-phase features for future scalability and integration.

Outcome & Results:

• Improved application loading speed and performance.
• Enhanced user interaction and cross-browser compatibility.
• Strengthened security measures, reducing vulnerabilities.
• Achieved a seamless deployment process via CI/CD automation.

Datability AI: Smarter Goals, Better Outcomes

When Datability approached us with a vision—an AI-powered chatbot that helps educators craft measurable, SMART goals—we knew we had the perfect challenge on our hands. From concept to deployment, we built a seamless, AI-driven experience that transforms how educators set and refine their objectives.

The Mission: Smarter Goal-Setting for Educators

Datability wanted more than just an AI chatbot; they needed a powerful, intuitive, and intelligent tool that could analyze, refine, and generate educational goals with precision. Our team took on the challenge, designing and developing an interactive AI assistant that evaluates goal measurability, suggests improvements, and generates new objectives that adhere to the SMART criteria—Specific, Measurable, Achievable, Relevant, and Time-bound.

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Project URL : http://www.databilityweb.com

SaaS in Action: Challenges & Solutions

Designing a Flawless User Experience

The Challenge:

Integrating an AI chatbot into an existing platform without disrupting the user experience was no small feat. We needed to ensure a smooth, intuitive interface that made goal-setting feel effortless.

Our Solution:

Our design team engineered a sleek, user-friendly chatbot experience with a one-click “Check Measurability” feature, allowing educators to validate their goals instantly. We iterated on UI/UX until the chatbot felt like a natural extension of Datability, not just an add-on.

Implementation Highlights:

• Seamless UI integration with Datability’s existing platform
• Intuitive user flows for effortless goal evaluation
• Designed, tested, and refined multiple prototypes

Designing a Flawless User Experience

The Challenge:

With multiple developers, stakeholders, and evolving requirements, maintaining clear communication and on-time delivery was crucial.

Our Solution:

We adopted an agile development approach, ensuring transparency and efficiency at every stage. With daily progress updates, structured pull requests, and proactive stakeholder communication, we kept everyone aligned and the project on track.

Implementation Highlights:

• Daily updates to monitor progress and resolve blockers
• PIull requests & code reviews for continuous quality assurance
• Direct stakeholder communication for quick feedback cycles

Training the AI for SMART Success

The Challenge:

AI is only as good as its training. We needed to fine-tune Datability’s chatbot so it could accurately assess and enhance educational goals, making sure every suggestion aligned with the SMART framework.

Our Solution:

We trained the AI using high-quality datasets filled with structured, well-crafted goals. By designing detailed custom prompts, we ensured that every response from the chatbot was insightful, relevant, and actionable.

Implementation Highlights:

• Created a precise AI prompt system for goal evaluation
• Trained the model on real-world educator inputs
• Iterated and refined AI responses for higher accuracy and relevancy

Agile Project Management & Stakeholder Success

The Challenge:

Building an AI-driven chatbot meant seamlessly connecting Datability’s frontend with powerful GPT-4 capabilities, ensuring smooth real-time processing while keeping the system scalable and secure.

Our Solution:

Our backend engineers crafted a robust API architecture, integrating socket connections between Datability’s React app and Sails.js server. We tackled API key management, ensuring secure connections and optimized performance.

Implementation Highlights:

• Configured server environments for optimal AI performance
• Managed API keys and model authentication for GPT-4 integration
• Established real-time socket connections for instant responses

The Outcome: AI-Powered Goal-Setting at Its Best

By the time we wrapped up, Datability had a fully integrated, AI-powered chatbot that revolutionized goal-setting in education. Now, educators can instantly analyze, refine, and create SMART goals with AI-powered insights, making Datability an even more powerful SaaS solution.

The result? 

A smoother workflow for educators, smarter goal evaluations, and a more intuitive SaaS platform—all powered by AI, built by us.

From idea to execution, we delivered a smarter, AI-driven future for Datability.

Active Users

119

ROI %

157

Development Journey

March 1, 2024

Project Kickoff 🚀

Held initial strategy meetings with stakeholders to define the project scope and objectives. Outlined key features: AI chatbot integration, goal evaluation, and user feedback. Created a high-level roadmap and development timeline.

March 15, 2024

Architecture & UI/UX Design Begins 💻

Designed the system architecture using React.js for the frontend and Sails.js for the backend. Wireframed chatbot integration into the existing user interface. Planned cloud infrastructure deployment, focusing on scalability and security.

April 1, 2024

Core Development Begins 🛠️

Built authentication & user management system. Developed API endpoints for chatbot interactions. Implemented database schema for storing educational goals and chatbot evaluations.

April 15, 2024

AI Chatbot Training & Integration 🤖

Integrated the GPT-4-based AI chatbot into the system. Developed a detailed prompt structure to ensure accurate assessment of educational goals. Conducted initial tests to fine-tune chatbot responses.

May 1, 2024

Beta Testing & Performance Optimization 🔍

• Conducted extensive testing on multiple browsers (Chrome, Firefox, Safari, Edge).
• Fixed UI inconsistencies and responsiveness issues.
• Ensured accessibility compliance with WCAG standards.

May 15, 2024

Final Testing & Security Enhancements 🔒

Conducted thorough security audits and performance testing. Optimized API response times and improved encryption protocols. Ensured chatbot compliance with educational standards.

May 30, 2024

Official Public Launch 🎉

Successfully launched the AI chatbot integration. Released a marketing push to onboard educators. Established a monitoring system for continuous improvements and updates.

DocuMind AI – Smart Document Search & Insights

When we were brought in to build Documind, we knew we were tackling something big—a cutting-edge AI-powered document intelligence platform designed to revolutionize how businesses extract, search, and analyze information from unstructured documents.

The Mission: Smarter Document Processing

From day one, we set out to build a scalable, AI-driven SaaS solution that could seamlessly process PDFs and Word documents, generate high-quality embeddings, store them efficiently, and power blazing-fast semantic search—all while maintaining an intuitive user experience.

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Project URL: http://www.documind.chat

What We Delivered

🚀 AI-Driven Document Processing

We engineered a robust document ingestion pipeline capable of extracting text, tables, and images from PDFs and Word files with precision. Our custom-built AI modules ensured that every piece of information was properly parsed and structured for maximum usability.

🖥️ Streamlit-Powered SaaS Dashboard

We didn’t just build a backend powerhouse—we designed an elegant, fully interactive UI using Streamlit. The real-time dashboard lets users query documents, visualize results, and track performance effortlessly.

🔍 Vector-Powered Semantic Search

Leveraging OpenAI embeddings and the Supabase vector database, we created a lightning-fast search engine that retrieves relevant documents with human-like intelligence. Users can now ask questions and get precise answers in seconds, rather than manually sifting through files.

⚡ Performance & Scalability

Speed and efficiency were top priorities, so we:

• Optimized async processing for real-time responsiveness.
• Integrated Supabase vector functions to boost search performance.
• Designed a Dockerization roadmap for seamless cross-platform deployment.

🤖 Agentic RAG Workflows


To take AI-powered search to the next level, we implemented dynamic Retrieval-Augmented Generation (RAG) workflows. Our system refines queries, validates AI-generated responses, and expands searches dynamically—ensuring higher accuracy and deeper insights.

🔗 Integrations & Future-Proofing


The platform doesn’t work in isolation—it connects with third-party tools like Ottomator for workflow automation and is built to evolve. We’ve mapped out Redis caching, multi-hop reasoning, and other AI-powered enhancements to keep Documind ahead of the curve.





Active Users

595

ROI %

499

Tech Stack That Makes It All Happen:


• Languages & Frameworks: Python, Streamlit
• AI/ML: OpenAI API (GPT-4, text-embedding-ada-002), LangChain
• Databases: Supabase (PostgreSQL + Vector), Weaviate
• Libraries & Tools: PyPDF2, python-docx, Sentence Transformers, GitHub
• DevOps & Scaling: Docker (planned), Microsoft Visual C++ Build Tools

Development Journey

July 1, 2021


Project Inception & Ideation

• Brainstormed the concept of an AI-driven document processing system.
• Researched existing solutions and identified pain points in document retrieval and search.
• Defined core features: document extraction, vector search, and AI-powered query workflows.
• Created a high-level roadmap and timeline. 🛠️

July 15, 2021


Architecture & UI/UX Design Begins 💻

• Designed system architecture using Python, OpenAI API, and Supabase.
• Created wireframes and UI mockups for the document upload and search interface.
• Planned database schema for storing embeddings and metadata.
• Evaluated vector search solutions (Supabase vs. Weaviate). 💻

August 2, 2021


Core Development Begins 🛠️

• Built initial PDF and Word document parsing modules with PyPDF2 and python-docx.
• Developed vector embedding pipeline using OpenAI’s text-embedding-ada-002.
• Set up a Supabase PostgreSQL + Vector Extension database for efficient retrieval.
• Implemented initial backend API for document processing. 🚦

September 1, 2021


Vector Search & Retrieval MVP Completed

• Integrated semantic search capabilities using Supabase vector functions.
• Implemented document metadata filtering for better search accuracy.
• Developed query ranking logic based on vector similarity scores.
• Conducted internal testing on real-world document datasets.

September 20, 2021


Agentic RAG Workflow Implementation

• Designed dynamic query refinement using AI-driven logic.
• Implemented multi-step retrieval and validation to improve response accuracy.
• Built a feedback mechanism to enhance search results over time. 🔍

October 10, 2021


Streamlit UI Development

• Developed a user-friendly front-end in Streamlit for real-time querying.
• Implemented document upload, search results display, and performance tracking.
• Added real-time progress indicators and interactive elements. 🖥️

November 1, 2021


Performance & Scalability Enhancements

• Optimized vector search queries to improve response times.
• Implemented asynchronous processing for faster document ingestion.
• Explored Dockerization for cross-platform compatibility.
• Addressed ONNX dependency errors and streamlined model execution. 🏗️

December 1, 2021


Beta Testing & Iteration

• Launched beta version with select testers to evaluate search accuracy and UI experience.
• Gathered feedback and made improvements to query refinement and retrieval logic.
• Fixed UI inconsistencies and improved error handling mechanisms. 📢

January 10, 2022


Official Release & Deployment

• Rolled out stable version with full document processing and search capabilities.
• Implemented final security audits and performance benchmarks.
• Began onboarding users and expanding database integration. 🚀

January 31, 2022


Future Roadmap Planning

• Planned Redis caching for faster retrieval and query optimization.
• Explored multi-hop reasoning capabilities for better document understanding.
• Discussed potential integrations with third-party tools like Ottomator. 📈