What Is the FirstMark 2025 MAD Landscape and How Does It Map the ML, AI, and Data Market?
The FirstMark 2025 MAD (ML/AI/Data) Landscape is a market map of companies and products across machine learning, artificial intelligence, and data, compiled by FirstMark. It is useful when you need a structured view of who operates in a given layer of the modern data and AI stack — for competitive research, category orientation, or tracking where new entrants are appearing. It is a map, not a buyer's guide: inclusion signals that a company is active in a category, not that it has been evaluated, ranked, or recommended.
What "MAD" covers
MAD stands for Machine Learning, Artificial Intelligence, and Data. The landscape treats these as one connected market rather than three separate ones, because the same companies often span them — a vector database sits in data infrastructure but exists mainly to serve AI applications, and an agent platform is an AI product built on data plumbing.
The map is organized as a stack, from the infrastructure that moves and stores data up to the applications end users touch.
How the landscape is structured
The excerpt shows the landscape split into roughly 50% infrastructure and the remainder across AI build/validate layers and applications. The main groupings are:
| Layer | What it covers | Example categories |
|---|---|---|
| Infrastructure — Integrate & Operate | Moving, governing, and monitoring data | ETL/ELT, data integration, governance & catalog, orchestration, data quality & observability, privacy & security, compute |
| Infrastructure — Store & Stream | Where data lives and how it flows | Data lakes/lakehouses, data warehouses, event brokers & messaging, stream processing, relational & distributed SQL, NoSQL, real-time analytics/HTAP, graph, vector, GPU, and multi-model databases |
| Analytics | Turning stored data into insight | BI & analytics platforms, headless/embedded BI & semantic layer, experimentation & causal, product analytics |
| ML & AI — Build | Tools for constructing AI systems | AI developer platforms, local/on-device LLM runtimes, agent platforms, agent infra/tooling |
| ML & AI — Validate & Secure | Making AI systems reliable and safe | AI observability & evaluation, AI safety & security, routing/prompt management & experimentation, AI & agent governance |
| Applications — Enterprise | Function-specific AI products | Customer experience & support agents, sales & marketing AI (GTM), automation & operations (agentic RPA), human capital & talent, legal AI, FinOps & risk |
| Applications — Horizontal | Cross-industry AI products | Code AI & agents, text/docs & knowledge agents, media generation, 3D/animation/gaming, audio & voice agents |
| Applications — Industry | Sector-specific AI | Healthcare & life sciences, finance, robotics/autonomy/industrial, aerospace/defense/govtech |
Two cross-cutting categories also appear: Data & AI Consulting, and Cloud Observability.
Reading the "New" markers
The "New" labels scattered through the excerpt mark categories or entries that are new to this edition of the landscape. They are the fastest way to see where the market is shifting. In the 2025 map, dense clusters of "New" appear around agent platforms, agent infra/tooling, AI observability & evaluation, AI safety & security, and AI & agent governance — signaling that the agent and AI-reliability layers are where the most new company formation is happening. Older, more settled categories such as data warehouses and relational SQL show fewer or no new markers.
Treat "New" as a directional signal about category momentum, not as a quality judgment about any individual company.
How to use it for research or selection
- Competitive mapping: Locate your product's category, then scan adjacent boxes to see who else is positioned near you. Companies appearing in multiple categories often indicate converging markets.
- Category discovery: If you are scoping a build-vs-buy decision, use the layer structure to find the specific category (e.g., "vector databases" or "routing, prompt management & experimentation") rather than searching generically for "AI tools."
- Trend tracking: Compare the density of "New" markers across layers over time to see which parts of the stack are expanding fastest.
- Vendor shortlisting: Use the map to build a candidate list, then evaluate each company on its own pricing, documentation, and fit — the landscape itself does not provide those details.
Limits to keep in mind
The landscape is a snapshot compiled by FirstMark, and inclusion is editorial. It does not rank companies, publish pricing, or indicate which products are free or require login. Categories reflect how FirstMark chose to segment the market, and other analysts may draw the boundaries differently. Use it as a starting orientation, and verify any specific company's capabilities and commercial terms directly.