Our teams help you discover and deploy AI capabilities quickly and efficiently by leveraging the right technology to meet your business needs. We specialize in designing and building experiences for large language models (LLMs).
See how we can help
While it is often difficult to manage the inherent probabilistic nature of LLMs, our teams have deep experience applying a variety of foundational techniques to manage around this inconsistency and increase model performance in an effort to reduce latency, improve accuracy, and reduce costs.
See how we can help
The lack of evaluations has been a key challenge for deploying AI models to production. By treating model evaluations as unit tests for LLM and pairing prompting with evaluations, our experts can transform ambiguous dialogues into quantifiable experiments, making AI a more manageable software product.
See how we can help
Adopting a headless architecture enables businesses to launch AI-driven experiences faster – without requiring a complete overhaul of existing tech stacks. Industry leaders like Nike and Alaska Airlines use this approach to cut costs and deliver AI-powered customer experiences that set them apart.
AI initiatives often get stuck in the Proof of Concept (POC) stage or fail to deliver tangible business value. The team might "build the solution," but it doesn’t address the real problem.
AI is transforming how products are built and experienced, introducing new tools, processes, and challenges for product managers, but it doesn’t fundamentally alter their core mandate of delivering customer and business value. While PMs must now navigate complexities like non-deterministic experiences and data readiness, their focus remains on understanding users, solving problems, and driving outcomes, not just implementing AI for its own sake.
Enterprises often struggle with rigid, outdated front-end systems that drive up costs and hinder their ability to adapt to market demands. Here's what a modern, AI-ready tech stack looks like and how you can achieve AI readiness incrementally in complex enterprise environments.
Get up speed on the things that matter.
Learn the ways in which AI is creating Smart Experiences in digital products today.
Machine learning and artificial intelligence (AI) can be daunting subjects. You might've heard about neural networks, generative adversarial networks (GANs), and recurrent neural networks (RNNs) but have no clue what people are talking about.
The purpose of this article is to help you begin designing with artificial intelligence(AI). This isn’t just a battle cry that “you too can become an AI designer!” but rather a reflection on our experiences exploring the intersection of AI and design —creating what we at Rangle call Smart Experiences. Think of Smart Experiences as experiences that feel “smart” and that help you avoid tedious or repetitive work. A Smart Experience can be as simple as an auto-complete suggestion and as complex as a virtual agent capable of answering your every question.
This past December I attended a Machine Learning for Creativity and Design workshop at NeurIPS 2018 in Montreal. NeurIPS (formerly NIPS) is a Conference on Neural Information Processing Systems or what today is often referred to as "AI". It's one of the most popular conferences in the space attracting thousands of submissions and attendants each year.
Join us to learn and contribute to Canada's artificial intelligence community.
SPEED MATTERS