AI terminology expands faster than most teams can keep track. This infographic breaks the entire stack into a clean layered model anyone can understand. You’ll see exactly how ML, DL, GenAI, XAI, and AGI relate, and where today’s real capabilities stop. A clarity-first guide for teams aligning strategy and expectations. Ideal for onboarding, training, and executive communication.

Strong AI intuition starts with understanding core ML algorithms. This infographic covers 20 must-know algorithms across supervised, unsupervised, and deep learning. Each entry is designed to help with faster model selection and clearer reasoning. A practical reference for practitioners, students, and cross-functional teams. If you want ML fundamentals without the noise, this is it.

Choosing the wrong model can quietly cost teams hours and accuracy. This infographic breaks down what each leading model does best — from reasoning and research to multimodal tasks and real-time insight. It also explains why multi-model stacking now outperforms any single-model approach. A clear, strategic guide for leaders making decisions about AI adoption. If reliability matters to you, this framework will help.

Successful AI products aren’t built on technical skills alone. They rely on clarity, communication, framing, experimentation, ethics, and team alignment. This infographic outlines the 20 non-technical capabilities every AI product team must master. Use it as a guide for training, hiring, or elevating cross-functional collaboration. A practical resource for leaders who want to build better products, faster.

ChatGPT can transform daily operations when teams know where to apply it. This infographic highlights ten practical, high-impact use cases across communication, research, reporting, and workflow automation. It’s built for teams ready to move beyond experimentation into structured adoption. Clear, actionable, and grounded in real business needs. A practical guide for leaders driving responsible AI usage.

Agentic AI requires far more than a strong model — it needs a complete architecture. This infographic simplifies that architecture into seven clear layers, from problem definition to deployment. It helps teams understand memory, reasoning loops, workflows, UX, infrastructure, and distribution. If you’re building next-generation AI systems, this is your blueprint. Clear, structured, and ready for implementation.

AI roles are evolving, and the skills that matter in 2026 look very different from today. This infographic highlights nine practical, high-impact capabilities that create real leverage. From agents to automation and multimodal reasoning, these skills help teams move faster with clarity. A forward-thinking reference for professionals preparing for the next era of work. If you’re planning your growth path, start here.

The open-source AI world evolves faster than most teams can keep up. Models, data stores, training frameworks, orchestration tools — they all sit in different layers. This infographic organizes the entire ecosystem into a clear, unified architecture. A reference point for engineers, product leaders, and strategists designing AI systems with intention. If your team wants clarity, this is the map you start with.

Most ML projects fail before they ever reach deployment — and the root cause is almost always data. Teams skip the critical step of understanding the structure, behavior, and quality of the data they rely on. This infographic breaks down the 12 core data types that shape every ML decision. If you’re building real systems, this is the starting point for clarity and long-term reliability. A foundational guide for architects, analysts, and leaders driving ML outcomes.

An OKR framework linking goals to outcomes, data, AI enablers, owners, and milestones, with RAG dashboards and examples.