Financial and Other Applications Development
About Encore Financial Encore Financial is a fast-growing fintech startup focused on building intelligent, user-first solutions for the next generation of investment and wealth management. We’re developing tools that empower investors, advisors, and institutions with smarter insights, streamlined workflows, and real-time financial data. Project Overview We are seeking a team of talented and motivated students to help us build a prototype for a Financial Application Suite . This prototype will serve as a foundational platform for investment research, portfolio management, wealth tracking, and crypto workflows. It will be accessible on both web and mobile, offering a seamless and engaging user experience. This project is ideal for learners eager to apply their development and design skills to real-world fintech use cases while building a product that solves meaningful challenges in the investment space. What You’ll Build You’ll contribute to the development of an intuitive, scalable application with features including: 📊 Real-time portfolio tracking and performance dashboards 🔍 Investment research tools with data visualizations and filters 🪙 Crypto portfolio and workflow management 💡 AI-powered insights and alerts 🔐 Secure, user-authenticated access and cloud-synced data 📈 Visual analytics (e.g., attribution, benchmarks, wealth trends) Key Focus Areas 1. Front-End Development Responsive design (web & mobile) Financial dashboards and interactive charts Clean UI components and transitions 2. Back-End Development & API Integration Scalable infrastructure using modern frameworks Integration with market data APIs (stocks, ETFs, crypto) Database design and data security best practices 3. Data Visualization & Analytics Custom charts (line, bar, pie, heatmaps) Portfolio performance and attribution analysis AI-powered summaries and financial metrics 4. User Experience (UX) Design Intuitive user flows and clean navigation Feedback-driven design iterations Accessibility and mobile optimization What You’ll Learn Real-world fintech development Cross-platform app deployment API handling and financial data modeling Working in agile teams with code reviews and feedback Product thinking and user-centric design Ideal Candidates We’re looking for students who are: ✅ Passionate about fintech and modern finance ✅ Curious, self-driven, and eager to learn ✅ Skilled in any of the following: JavaScript/React, Python, Flutter, Figma, Node.js, Firebase, or similar ✅ Able to work collaboratively in a remote team environment
Cloud application development for an AI powered project management product
Efficient project management relies on effective governance and the smooth creation of project documents. Many organizations face challenges due to manual and inefficient processes, causing delays, errors, and non-compliance with industry standards. The current lack of AI-driven project management software exacerbates these issues, leading to significant time investments by project managers and teams in document creation, impacting project goals and decision-making timelines. The objective of this project is to create a minimum viable product (MVP) of a project management software solution that leverages generative AI to intelligently create project management artifacts based on the nature of the project, its appropriate project lifecycle, user inputs, information, and documents.
Backend AI API development and third party API Integration
Preeminent Technologies is Fostering Technological Advancements in Global Travel Sector through Building Innovative Solutions in Canada. We are building an AI, Big Data Analytics, LLMs/Machine Learning enabled traveler-centric (comprehensive enterprise commercial) travel planning and travel booking platform. Segment 1: As back-end developers, the intern resources will be responsible for developing and maintaining cloud-based azure functions, backend-APIs using .Net 8, C#, Azure, and Enterprise APIs. These resources will collaborate with cross-functional teams to design, develop, and implement scalable, secure and cloud hosted solutions. Additionally, the resources will participate in code reviews, troubleshoot system issues, and contribute to continuous improvement initiatives. Segment 2: We are developing programs and training automations in analyzing AI datasets, OpenAI, conversational and generative AI models, building automation for AI and LLM/ML model training, fine-tuning AI and LLM/ML models, and running automated test processes to validate results against real-time data, price, availability, and other parameters. The machine-learning problem we are addressing revolves around optimizing search processes within the travel domain, particularly when dealing with datasets sourced from multiple providers. I wanted to reach out to explore potential collaboration opportunities for us to support development activities and would welcome the opportunity to connecting with your team on this initiative to discuss further details. Required Expertise Skills: The ideal candidates will have strong background in software development, cloud platforms, SDLC concepts, clean architecture approach, and possess the technical skills necessary to integrate various APIs and modern technologies seamlessly. We are looking to fill in the role of technical intern resources as intermediate backend developers, will be responsible for developing and maintaining cloud-based application using .Net 8, C#, Azure OpenAI service, and Enterprise API integrations.
AI-Enhanced Data Platform Pitch Deck for Renewable Energy
DDB Consultants Inc. seeks to develop a compelling pitch deck for an innovative AI-enhanced data capture and reconciliation platform tailored for the renewable energy sector. The platform aims to streamline data management processes, improve accuracy, and enhance decision-making capabilities for renewable energy companies. The project will require learners to apply their knowledge of AI technologies, data analytics, and renewable energy industry dynamics. The goal is to create a persuasive and visually appealing presentation that effectively communicates the platform's value proposition to potential investors. The pitch deck should highlight the platform's unique features, market potential, and competitive advantages, while also addressing potential challenges and solutions. - Understand the renewable energy service industry's pain point when it comes to data and information management - Identify key features and benefits of the AI-enhanced platform. - Research market trends and competitive landscape. - Develop a cohesive narrative for the pitch deck. - Design visually engaging slides that support the narrative.
AI-Assistant App for Cybersecurity
Primary Objectives The main objective of this project is to build 2 MVP Applications. MVP's will be AI-powered cybersecurity applications designed to assist small businesses. APP1 - Cyber Assistant App The purpose of this App is to assist small businesses by focusing on being an AI-Cyber Assistant that supports small IT and Security Teams on a daily basis. APP2 - AI Workflow Agentic App The purpose of this App is to orchestrate the activities involved in preparing an organization for ISO27001 and SOC2 certification audits by automating the steps and activities for the creation and evidencing of required controls and documentation.
Automate process to Training AI & Machine Learning Model for our application
Preeminent Technologies is Fostering Technological Advancements in Global Travel Sector through Building Innovative Solutions in Canada. We are building an AI, Big Data Analytics, LLMs/Machine Learning enabled traveler-centric (comprehensive enterprise commercial) travel planning and travel booking platform. We are developing programs and training automations in analyzing AI datasets, OpenAI, conversational and generative AI models, building automation for AI and LLM/ML model training, fine-tuning AI and LLM/ML models, and running automated test processes to validate results against real-time data, price, availability, and other parameters. The machine-learning problem we are addressing revolves around optimizing search processes within the travel domain, particularly when dealing with datasets sourced from multiple providers.