Kesem Solutions
Kesem Solutions is a team of software development and Australian technology experts specialising in AI-driven and advanced digital solutions. We excel in mobile app development with iOS and React Native, AI and Retrieval-Augmented Generation (RAG) systems, enterprise-grade applications using J2EE, and scalable web platforms with Spring and GWT.
Our certifications in Microsoft (.NET, MCSD, MCDBA, MCTS) and Oracle (OCP), combined with deep experience in SAP and IoT integration, enable us to deliver innovative, cross-platform applications across finance, healthcare, energy, and other critical industries.
With a strong focus on quality and innovation, Kesem Solutions ensures every project is delivered on time, within budget, and enhanced with the latest AI and RAG capabilities, always aligned with client needs and future scalability.
What the Tech?
We get it—technical jargon isn’t everyone’s cup of tea. So, if you’re scratching your head wondering what all this tech talk really means, don’t worry! We’ve put together a quick guide to help you decode the terms we use every day.
Because while we love diving deep into the world of J2EE, React Native, and IoT, we know it’s important to make sure you’re right there with us, understanding exactly what it is we do to bring your projects to life!
IoT (Internet of Things)
Think of IoT as a network of devices—like smart thermostats or fitness trackers—that connect and communicate over the internet to make our lives easier and more efficient.
BLE (Bluetooth Low Energy)
A power-friendly version of Bluetooth that lets devices communicate wirelessly without draining your battery. It's the secret sauce behind things like smartwatches and wireless earbuds.
API (Application Programming Interface)
A set of rules that allows different software applications to talk to each other. Think of it as a translator that helps various apps, programs, and systems work together seamlessly.
AWS (Amazon Web Services)
A cloud platform that provides a vast array of IT resources over the internet. It’s like having a supercomputer in the cloud that can handle everything from storage to complex applications.
Cloud
Not the fluffy stuff in the sky! The cloud is where you can store data and run applications remotely, giving you access to your stuff from anywhere, anytime, without needing a physical server.
Integration Apps
These are the behind-the-scenes tools that make sure all your different software systems work together smoothly, so your data flows seamlessly across platforms.
Hybrid App Development
Hybrid apps work across multiple platforms (like iOS and Android) with a single codebase, making them faster to develop and easier to maintain.
UI/UX Design
This is all about creating apps and websites that are not only beautiful (UI: User Interface) but also easy and enjoyable to use (UX: User Experience).
FAQ
What industries does Kesem Solutions specialise in?
Kesem Solutions has extensive experience across various industries, including Finance, Banking, HR and recruitment, Manufacturing, Utilities, Automotive, Telecommunications, and Information Technology. We also work with both private sector businesses and government entities at the federal, state, and local levels.
What technologies and frameworks does Kesem Solutions work with?
Our team is trained in a wide range of technologies, including iOS, React Native, J2EE, Swings, GWT, Spring frameworks, Microsoft technologies (MCSD.Net, MCDBA, MCTS), Oracle technologies (OCP), SAP systems, Computer Associates, and other open-source frameworks. In addition to Python with frameworks like PyTorch, TensorFlow, and LangChain because of their maturity and ecosystem strength. JavaScript/TypeScript (React Native, Node.js), Swift/Objective-C (iOS), and SQL for data-heavy applications. This mix allows us to align AI pipelines with robust, scalable enterprise and mobile solutions.
What types of applications does Kesem Solutions develop?
We design, develop, and implement cross-platform applications, including BLE (IoT) integrated apps, for sectors such as medical, environmental, and energy.
What AI App Development in Australia Kesem Solutions offers?
Kesem Solutions has an extensive experience in OpenAI, GPT-3, GPT-4, DALL-E, Flutter, TensorFlow and PyTorch. We also developed apps in OpenVision, YOLOv5, YOLOv8, YOLOv10 and YOLOv11
What are the differences between supervised, unsupervised, and reinforcement learning?
Supervised learning uses labelled data to map inputs to known outputs. Unsupervised learning finds patterns and groupings in unlabelled data. Reinforcement learning trains agents through trial and error with feedback in the form of rewards, optimising decision-making over time.
Your solution might require supervised learning only or a combination of LLM.
How do you approach selecting or integrating suitable machine learning models in production?
We evaluate based on accuracy, efficiency, cost, and deployment environment. We benchmark multiple models, validate against client datasets, and integrate with scalable APIs or containerised services, ensuring the chosen model aligns with business goals and infrastructure.
What strategies do you use for managing and retrieving large datasets efficiently?
We leverage vector databases (e.g., FAISS, Pinecone, ChromaDB) for embeddings, optimise indexing and chunking strategies, and use cloud-native storage (S3, GCS) with caching for speed. For structured data, we combine relational databases with batch or stream pipelines.
How do you handle bias, errors, and ethical considerations in AI systems?
We mitigate bias with diverse training data, fairness testing, and human oversight. Errors are reduced through robust validation, fallback responses, and clear user disclaimers. Ethical considerations are embedded via transparency, explainability, and compliance with AI guidelines.
What is BLE, and how does Kesem Solutions use it?
BLE (Bluetooth Low Energy) is a wireless communication technology used to transmit data over short distances with minimal power consumption. Kesem Solutions integrates BLE into IoT applications, particularly in fields like medical, environmental, and energy monitoring..
How does Kesem ensure the quality and timeliness of projects?
Our team combines technical expertise with strong business and project management experience. We focus on delivering high-quality projects on time, within budget, and adhering to scope, ensuring the best outcomes for our clients.
What certifications do Kesem Solutions professionals hold?
Our professionals hold certifications such as Microsoft Certified Solution Developer (MCSD.Net), Microsoft Certified Database Administrator (MCDBA), Microsoft Certified Technology Specialist (MCTS), and Oracle Professional Certification (OCP), among others. These credentials ensure that our team is well-equipped to handle complex technical challenges.
What specific AI and ML projects have you worked on, and what were your contributions?
We’ve delivered AI-powered mobile and web applications such as BoxAeye (AI packing assistant), iUFlow (digital health diagnostics), and RAG chatbots for enterprise knowledge retrieval. Our contributions span end-to-end: data preparation, model integration (LLMs, vision models), RAG architecture design, deployment, and optimisation for cost, latency, and scalability.
What does your RAG solution include beyond just an LLM and retrieval?Toggle Title
Our RAG systems include preprocessing pipelines, metadata-aware chunking, embedding optimisation, query re-ranking, caching, and monitoring. We also integrate user feedback loops, APIs, and dashboards, ensuring the solution is explainable, scalable, and aligned with enterprise workflows.
How do you ensure data security and privacy in your AI or RAG implementations?
We enforce encryption in transit and at rest, anonymise sensitive data, comply with GDPR/CCPA/TGA as required, and use role-based access controls. For healthcare and finance, we implement strict audit trails and on-prem or VPC deployments where needed.
Are your RAG and LLM components flexible to allow model changes as technology evolves?
Yes, our architecture is modular: we abstract embeddings, retrievers, and LLMs behind APIs, allowing us to swap providers (OpenAI, Anthropic, open-source models) without redesign. This ensures future-proofing and cost optimisation as new models emerge.
How do you test and evaluate the accuracy, relevance, and quality of generated responses in RAG?Toggle Title
We use benchmark datasets, human evaluation, and automated metrics (precision/recall, BLEU, ROUGE). Additionally, we run A/B tests in production, track relevance through user feedback, and implement continuous monitoring to refine indexing and model outputs.