Decision Intelligence Glossary
AI Solutions
Products or solutions that deliver pre-packaged artificial intelligence capabilities for specific use cases. These could include built-in models, workflows, and decisioning logic tailored to domains like fraud detection, customer engagement, or inventory forecasting. AI Solutions, as a category, does not include products or solutions that would fit in another category as "AI-Powered" and is dedicated to AI solutions not easily categorized or a compliment to the others.
Application Development
Tools and platforms designed to create, deploy, and manage applications—often with built-in support for embedding decision logic, AI components, or workflows. Includes both traditional dev environments and no-code / low-code solutions.
Data Management
Systems that govern, integrate, clean, transform, and prepare data to ensure it is reliable and usable for decision-making. This includes ETL pipelines, data lineage, quality monitoring, and metadata management. For simplicity’s sake, in DecideWise we have also included data providers in this category.
Descriptive Analytics
Tools and systems that help users understand what has happened and why through dashboards, reports, and visualizations. This is typically the first layer in the analytics stack. In addition to obvious vendors in this category, observability (log file analytics and SIEM) vendors are also categorized as Descriptive Analytics.
LLM (Large Language Model)
Technologies or platforms that leverage transformer-based language models (e.g., GPT, BERT) to enable natural language understanding, content generation, summarization, and conversational AI as part of the decision-making process.
Optimization
Software that solves complex decision problems under constraints to determine the best possible action. This includes linear programming, mixed-integer programming, heuristics, and reinforcement learning used in scheduling, resource allocation, and planning. In DecideWise, this category includes both vendors selling the mathematical modeling capabilities as well as vendors crafting unique industry solutions utilizing optimization models.
Platform
Broad, foundational ecosystems that support the full lifecycle of decision intelligence—including data ingestion, modeling, decision logic, orchestration, and monitoring. Often includes modular components or composability. For purposes of DecideWise, the solution must deliver on a minimum of three capabilities in an integrated fashion to be considered a Platform.
Predictive Analytics
Model-driven systems that use historical data and complex mathematics to forecast future outcomes or identify anomalies. Includes statistical modeling, machine learning, and time-series forecasting.
Rules
Systems that apply business logic through rule-based engines (e.g., if-then-else structures) to automate decisions. These are often used in compliance-heavy domains and customer decision flows. In most cases rules systems make calls to data, analytics, AI, or experts in their execution.
Simulation
Technologies that model systems or environments to test decisions under various scenarios. These tools help forecast outcomes, test risk scenarios, or explore decision impacts in controlled digital environments. Simulation includes vendors delivering feature driven what-if scenario analysis for particular use cases all the way to creating top down full digital twin models of a business, industry, or market.
Streaming Analytics
Real-time data processing systems that analyze event streams on-the-fly. Useful in time-sensitive decision environments like fraud detection, sensor networks, IoT, or dynamic customer interaction. Log file analytics and SIEM vendors are not included here but rather as descriptive analytics vendors.
Workflow
Tools that orchestrate sequences of tasks (automated or human) into structured processes. Often used to manage approval chains, decision review processes, or to embed logic-driven task routing in operations.