Maximize Your Business Potential With Seamless AI Integration.

Maximize Your Business
Potential With Seamless AI Integration.

With our AI consulting and AI integration services, you now have the ability to choose from an entire gamut of AI solutions and tools to deliver quick results.

RandomWalk
RandomWalk

Leading The World’s AI Integration

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Leading The World’s AI Integration

Choose the ideal AI tools for your business with expert guidance from Random Walk, where we collaborate to implement custom AI solutions.

Our engineers specialize in seamless AI integration, accelerating connections between AI tools and existing software.

From business functions like marketing, HR and finance to different industries like retail and pharma, find the right AI tool.

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If you are an AI tools provider,

Make It Easy To Choose
Your Tools

Work with Random Walk to integrate your AI tool into our platform. While our customers develop software with us, we will recommend your AI solution.

If you are a client looking for AI capabilities,

Begin Your AI Journey
Now

Let us work with you to integrate niche AI tools into your day-to-day business functions like HR, marketing, and finance. We also cater various industry-specific AI tools to aid operations.

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Our Blogs

The Intersection of Computer Vision and Immersive Technologies in AR/VR

In recent years, computer vision has transformed the fields of Augmented Reality (AR) and Virtual Reality (VR), enabling new ways for users to interact with digital environments. The AR/VR market, fueled by computer vision advancements, is projected to reach $296.9 billion by 2024, underscoring the impact of these technologies. As computer vision continues to evolve, it will create even more immersive experiences, transforming everything from how we work and learn to how we shop and socialize in virtual spaces. An example of computer vision in AR/VR is Random Walk’s WebXR-powered AI indoor navigation system that transforms how people navigate complex buildings like malls, hotels, or offices. Addressing the common challenges of traditional maps and signage, this AR experience overlays digital directions onto the user’s real-world view via their device's camera. Users select their destination, and AR visual cues—like arrows and information markers—guide them precisely. The system uses SIFT algorithms for computer vision to detect and track distinctive features in the environment, ensuring accurate localization as users move. Accessible through web browsers, this solution offers a cost-effective, adaptable approach to real-world navigation challenges.

The Intersection of Computer Vision and Immersive Technologies in AR/VR

Leading with AI: Inside the AI Training Programs That Turned Companies into Digital Leaders

The future of work isn't just knocking—it's remodeling everything. As AI transforms industries worldwide, the real edge won’t come from having the most advanced technology, but from preparing the workforce to thrive alongside it. The pivotal question now is not if AI will redefine your industry, but how prepared you are to seize the opportunities it brings. Will your team be equipped to lead or left scrambling to catch up? Recent data from McKinsey Global Institute paints an intriguing picture: AI could contribute to the creation of 20-50 million new jobs globally by 2030. But here's the catch - these aren't just new jobs; they're entirely new ways of working. The organizations leading this transformation aren't just implementing AI; they're reimagining how their entire workforce operates alongside it.

Leading with AI: Inside the AI Training Programs That Turned Companies into Digital Leaders

The Great AI Detective Games: YOLOv8 vs YOLOv11

Meet our two star detectives at the YOLO Detective Agency: the seasoned veteran Detective YOLOv8 (68M neural connections) and the efficient rookie Detective YOLOv11 (60M neural pathways). Today, they're facing their ultimate challenge: finding Waldo in a series of increasingly complex scenes.

The Great AI Detective Games: YOLOv8 vs YOLOv11

1-bit LLMs: The Future of Efficient and Accessible Enterprise AI

As data grows, enterprises face challenges in managing their knowledge systems. While Large Language Models (LLMs) like GPT-4 excel in understanding and generating text, they require substantial computational resources, often needing hundreds of gigabytes of memory and costly GPU hardware. This poses a significant barrier for many organizations, alongside concerns about data privacy and operational costs. As a result, many enterprises find it difficult to utilize the AI capabilities essential for staying competitive, as current LLMs are often technically and financially out of reach.

1-bit LLMs: The Future of Efficient and Accessible Enterprise AI

AI-Powered vs. Traditional Sponsorship Monitoring: Which is Better?

Picture this: You, a brand manager, are at a packed stadium, the crowd's roaring, and suddenly you spot your brand's logo flashing across the giant screen. Your heart races, but then a nagging question hits you: "How do I know if this sponsorship is actually worth the investment?" As brands invest millions in sponsorships, the need for accurate, timely, and insightful monitoring has never been greater. But here's the million-dollar question: Is the traditional approach to sponsorship monitoring still cutting it, or is AI-powered monitoring the new MVP? Let's see how these two methods stack up against each other for brand detection in the high-stakes arena of sports sponsorship.

AI-Powered vs. Traditional Sponsorship Monitoring: Which is Better?
The Intersection of Computer Vision and Immersive Technologies in AR/VR

The Intersection of Computer Vision and Immersive Technologies in AR/VR

In recent years, computer vision has transformed the fields of Augmented Reality (AR) and Virtual Reality (VR), enabling new ways for users to interact with digital environments. The AR/VR market, fueled by computer vision advancements, is projected to reach $296.9 billion by 2024, underscoring the impact of these technologies. As computer vision continues to evolve, it will create even more immersive experiences, transforming everything from how we work and learn to how we shop and socialize in virtual spaces. An example of computer vision in AR/VR is Random Walk’s WebXR-powered AI indoor navigation system that transforms how people navigate complex buildings like malls, hotels, or offices. Addressing the common challenges of traditional maps and signage, this AR experience overlays digital directions onto the user’s real-world view via their device's camera. Users select their destination, and AR visual cues—like arrows and information markers—guide them precisely. The system uses SIFT algorithms for computer vision to detect and track distinctive features in the environment, ensuring accurate localization as users move. Accessible through web browsers, this solution offers a cost-effective, adaptable approach to real-world navigation challenges.

Leading with AI: Inside the AI Training Programs That Turned Companies into Digital Leaders

Leading with AI: Inside the AI Training Programs That Turned Companies into Digital Leaders

The future of work isn't just knocking—it's remodeling everything. As AI transforms industries worldwide, the real edge won’t come from having the most advanced technology, but from preparing the workforce to thrive alongside it. The pivotal question now is not if AI will redefine your industry, but how prepared you are to seize the opportunities it brings. Will your team be equipped to lead or left scrambling to catch up? Recent data from McKinsey Global Institute paints an intriguing picture: AI could contribute to the creation of 20-50 million new jobs globally by 2030. But here's the catch - these aren't just new jobs; they're entirely new ways of working. The organizations leading this transformation aren't just implementing AI; they're reimagining how their entire workforce operates alongside it.

The Great AI Detective Games: YOLOv8 vs YOLOv11

The Great AI Detective Games: YOLOv8 vs YOLOv11

Meet our two star detectives at the YOLO Detective Agency: the seasoned veteran Detective YOLOv8 (68M neural connections) and the efficient rookie Detective YOLOv11 (60M neural pathways). Today, they're facing their ultimate challenge: finding Waldo in a series of increasingly complex scenes.

1-bit LLMs: The Future of Efficient and Accessible Enterprise AI

1-bit LLMs: The Future of Efficient and Accessible Enterprise AI

As data grows, enterprises face challenges in managing their knowledge systems. While Large Language Models (LLMs) like GPT-4 excel in understanding and generating text, they require substantial computational resources, often needing hundreds of gigabytes of memory and costly GPU hardware. This poses a significant barrier for many organizations, alongside concerns about data privacy and operational costs. As a result, many enterprises find it difficult to utilize the AI capabilities essential for staying competitive, as current LLMs are often technically and financially out of reach.

AI-Powered vs. Traditional Sponsorship Monitoring: Which is Better?

AI-Powered vs. Traditional Sponsorship Monitoring: Which is Better?

Picture this: You, a brand manager, are at a packed stadium, the crowd's roaring, and suddenly you spot your brand's logo flashing across the giant screen. Your heart races, but then a nagging question hits you: "How do I know if this sponsorship is actually worth the investment?" As brands invest millions in sponsorships, the need for accurate, timely, and insightful monitoring has never been greater. But here's the million-dollar question: Is the traditional approach to sponsorship monitoring still cutting it, or is AI-powered monitoring the new MVP? Let's see how these two methods stack up against each other for brand detection in the high-stakes arena of sports sponsorship.

Additional

Your Random Walk Towards AI Begins Now