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Spotfire 15.0 introduces new capabilities that help users investigate larger datasets, apply advanced statistical techniques, accelerate analytical workflows with AI, and work more effectively with industrial and time-series data.
Highlights of this release include Visual AI and Insight Agents, Push Compute for large-scale analytics in cloud data platforms, a new Wafer Map visualization for semiconductor manufacturing workflows, expanded statistical analysis capabilities, improved support for industrial data sources such as AVEVA PI and LAS files, and new features for time-series analysis and visualization.
Spotfire 15.0 continues to enhance the analytical experience with new AI-assisted workflows, improvements to visualization authoring, and usability enhancements that help users move from data to insight more efficiently.
Spotfire AnalyticsSpotfire Industry Pro
Engineers and scientists often spend significant time preparing data, selecting appropriate analytical techniques, and building the visualizations required to investigate a problem. Visual AI helps accelerate this process by combining Spotfire analytics, AI, and domain-specific guidance to assist users throughout their analytical workflow.
Visual AI analyzes the current data, analysis context, and user intent to recommend relevant analytical actions and investigation paths. Depending on the scenario, Visual AI may highlight patterns, trends, anomalies, or opportunities for further investigation, helping users move from data to insight more efficiently.
Visual AI is designed to reduce repetitive analytical tasks, lower the barrier to advanced analytics, and make it easier for subject matter experts to explore data without requiring extensive knowledge of Spotfire functionality or analytical methods.
The following sections describe the key capabilities introduced in Spotfire 15.0.
Insight Agents use data, analysis context, and AI to identify relevant analytical actions and recommendations directly within Spotfire.
Based on the current analysis, an Insight Agent may highlight important findings, suggest additional investigations, recommend suitable visualizations, or help build analytical workflows that support further exploration of the data.
Spotfire 15.0 introduces a growing collection of Insight Agents designed to help users discover insights more quickly and reduce the effort required to perform common analytical tasks.
Insight Agents can be accessed through the new Insights Panel and the Insight Toolbar available directly within the analytical experience.
When data is marked in a visualization, Spotfire can present relevant Insight Agents and recommendations based on the selected data and current analysis context. Users can execute all applicable Insight Agents at once or choose a specific agent when investigating a particular question.
Recommendations are presented alongside the analysis, allowing users to review findings and decide which suggested actions to apply.
Spotfire 15.0 introduces the Agent Registry, a centralized catalog for discovering and installing Insight Agents.
Available through the Add-ons Browser, the Agent Registry allows users to browse, search, and install Insight Agents that address specific analytical tasks and industry workflows. As new Insight Agents become available, they can be added independently of major Spotfire releases, allowing organizations to continuously expand their AI-assisted analytical capabilities.
The Agent Registry includes both general-purpose and industry-specific Insight Agents developed by Spotfire, with additional agents being added over time.
In addition to the agents developed by Spotfire, it is also possible to build your own Insight Agent, that incorporates your own business rules and knowledge, and recommendations exactly tailored to your needs. When you developed a Custom Insight Agent, you can share it in your organization through the Spotfire Library, just like Spotfire Visualization and Action Mods.
See Developing Custom Insight Agents below for more information.
Spotfire AnalyticsSpotfire Industry Pro
Time-based visualizations often require different date and time formats depending on the level of detail being displayed. Fixed axis formats can become difficult to read when users zoom, filter, or move between broad trends and detailed investigations.
Spotfire 15.0 introduces an Adaptive format option for continuous time axes. When enabled, axis labels automatically adjust their formatting based on the granularity of the data currently displayed, helping keep visualizations legible and uncluttered across different levels of detail.
As users zoom or filter data, axis labels update automatically to provide the most appropriate time representation for the current view. Full timestamp information remains available through tooltips when needed.
Adaptive Axis Scales reduce the need for manual axis formatting and help make time-series analysis more intuitive and easier to interpret.
Spotfire AnalyticsSpotfire Industry Pro
When working with logarithmic scales, it can be difficult to accurately interpret values between major scale intervals. Spotfire now displays minor gridlines by default on axes that use logarithmic scaling, making it easier to read and interpret data across a wide range of values.
The visibility of minor gridlines can be configured globally through application preferences or adjusted for individual visualizations through the visualization properties panel.
Spotfire AnalyticsSpotfire Industry Pro
When exploring data, users often want to compare trend lines or fitted curves for a specific subset of observations without changing the overall filtering context of the analysis. Spotfire now provides an option to perform curve fitting using only the currently marked rows in a visualization.
This allows users to quickly evaluate trends within selected groups while keeping the full dataset visible for comparison. The setting is available for Lines and Curves and can be configured through the visualization properties panel.
Spotfire AnalyticsSpotfire Industry Pro
Spotfire 15.0 continues to improve usability, consistency, and feature coverage, making it easier to configure and customize visualizations regardless of where analyses are created and consumed.
This release expands support for additional visualization capabilities and introduces several usability improvements, including:
Support for configuring Lines and Curves directly in the new visualization properties panel
Improvements to the Box Plot statistics table card, making built-in statistical measures easier to discover and select
Additional refinements and enhancements to the overall authoring experience
Together, these enhancements further reduce the need to switch between authoring experiences and help streamline visualization configuration workflows.
Learn how to work with the new visualization properties panel in Spotfire.
Spotfire 15.0 expands support for industry-specific workflows and advanced analytical techniques. New capabilities help engineers, scientists, and analysts investigate large datasets, apply statistical methods, work with industrial data sources, and accelerate domain-specific investigations.
Spotfire Industry Pro
Spotfire 15.0 introduces Insight Agents designed for industry-specific analytical workflows.
These agents incorporate domain knowledge and analytical best practices to assist engineers and scientists with common investigative tasks. Examples include identifying relevant production data in Energy workflows and assisting with wafer data preparation and investigation in semiconductor manufacturing.
Additional Insight Agents will continue to be delivered through the Spotfire Agent Registry.
Spotfire Industry Pro
Organizations increasingly store and manage large volumes of data in cloud data platforms such as Snowflake and Databricks. Moving data out of these platforms for analysis can introduce performance, governance, and scalability challenges.
Spotfire 15.0 introduces Push Compute, enabling analytics and data transformations to execute directly within supported data platforms. By bringing computation to where the data resides, users can investigate larger datasets while continuing to use familiar Spotfire workflows and visual analytics.
Key capabilities include:
Secure connectivity to Snowflake and Databricks using Single Sign-On (SSO)
Execution of supported Spotfire transformations, including joins, pivots, unpivots, and calculated columns, directly within the data platform
Integration of scalable data function workflows with distributed compute environments
Visual management of large-scale analytical workflows through the Spotfire Data Canvas
Movement of data between in-memory and push-compute environments when appropriate
Push Compute helps organizations combine the scalability of modern cloud data platforms with the interactive analytical experience of Spotfire, enabling investigation of large datasets while maintaining existing governance, security, and access controls.
Spotfire Industry Pro
Semiconductor engineers frequently investigate yield loss, defect patterns, process variation, and manufacturing anomalies using wafer-level data. Spotfire 15.0 introduces a dedicated wafer map visualization that brings these workflows directly into Spotfire, enabling interactive spatial analysis of semiconductor manufacturing data.
The wafer map visualization supports yield, defect, process, and quality investigations by allowing engineers to combine die, defect, metrology, and test data in a single analytical experience. Spatial patterns, wafer-level anomalies, and manufacturing variations can be explored alongside the full range of Spotfire visualizations and analytics.
Key capabilities include:
Wafer-aware rendering with wafer outlines, notch orientation, die grids, and cross-air
Multi-layer visualization of die, defect, metrology, and marker-based datasets
Continuous and categorical coloring for yield, measurements, classifications, and bin data
Interactive marking, zooming, panning, and linked analysis across visualizations
Trellised comparison of multiple wafers
Layer-specific filtering and visualization controls for complex investigations
By bringing wafer-level spatial analysis into Spotfire, engineers can investigate yield excursions, defect clusters, process variations, and quality issues without relying on external tools or custom visualizations.
Spotfire Industry Pro
Preparing semiconductor wafer data for analysis often requires validating data quality, resolving data inconsistencies, and enriching datasets with additional contextual information. These preparation steps can be time-consuming and may impact the accuracy of downstream analysis.
The Wafer Data Preparation Agent helps engineers prepare wafer data for investigation by automatically identifying common data issues and recommending corrective actions. The agent can detect missing data, identify coordinate system mismatches, and assist with enriching datasets through the calculation of wafer zones.
By reducing manual data preparation effort, the Wafer Data Preparation Agent helps engineers move more quickly from raw data to wafer-level analysis and investigation.
Spotfire Industry Pro
Engineers and scientists frequently need to determine whether observed differences in data are meaningful or simply the result of normal variation. Spotfire 15.0 expands the statistical capabilities available in the Spotfire expression language, making it easier to evaluate assumptions, compare groups, analyze distributions, and assess statistical significance directly within Spotfire.
The new functions are available across visualizations, calculated columns, data transformations, and interactive analytical workflows.
Key capabilities include:
Normality testing using Anderson-Darling, Shapiro-Wilk, and Kolmogorov-Smirnov methods
Distribution analysis through skewness and kurtosis metrics
Parametric and non-parametric hypothesis testing, including t-tests, ANOVA, and Kruskal-Wallis tests
Variance comparison using Levene and Brown-Forsythe tests
Distribution comparison using one-sample and two-sample Kolmogorov-Smirnov tests
Additional probability and distribution functions for Beta and Kolmogorov-Smirnov distributions
These capabilities support a wide range of quality, process, yield, scientific, and operational investigation workflows, helping users make more informed decisions based on statistical evidence.
See the product documentation for the complete list of functions, syntax, and usage examples.
Spotfire Industry ProComing Soon
Selecting the appropriate statistical method is often one of the most challenging aspects of analytical investigations. Engineers and scientists must determine which tests are applicable, verify underlying assumptions, and correctly interpret results before drawing conclusions from data.
The Analyze Category Profiles Agent helps users apply statistical methods with greater confidence by providing contextual guidance directly within Spotfire. Based on the data, visualizations, and analytical workflow, the agent can recommend suitable statistical techniques, identify potential issues, and explain the implications of statistical results.
The agent can assist users by:
Recommending appropriate statistical methods for a given analytical question
Identifying situations where statistical assumptions may be violated
Suggesting alternative approaches when selected methods are not appropriate
Highlighting potential issues related to sample size, distributions, or significance
Explaining statistical findings in the context of the current investigation
For example, the agent may recommend a non-parametric test when normality assumptions are not met, identify insufficient sample sizes for a planned comparison, or suggest additional analyses to help investigate the drivers behind an observed pattern.
By embedding statistical guidance directly into the analytical workflow, the Statistical Test Advisor Agent helps users apply advanced statistical techniques more effectively while accelerating investigation and decision-making processes.
Spotfire Industry Pro
Spotfire 15.0 expands the collection of Statistica Data Functions available for advanced analytical and machine learning workflows. The release introduces more than 15 new algorithms and enhancements spanning statistical analysis, predictive modeling, feature selection, and data preparation.
New capabilities include:
Normality testing by groups
Partial Least Squares (PLS) classification and regression model training and scoring
Advanced feature selection techniques
Lasso linear and logistic regression
Model comparison workflows for classification and regression
Sparse data filtering
These additions provide analysts and data scientists with a broader set of tools for building, evaluating, and operationalizing predictive and statistical models directly within Spotfire.
Spotfire Industry Pro
Geologists and reservoir engineers frequently evaluate uncertainty when estimating reserves, production potential, and asset value. Understanding the probability distribution of subsurface properties is an important part of assessing risk and supporting investment decisions.
Spotfire 15.0 introduces a Probit Plot visualization that helps users analyze distributions and assess uncertainty directly within Spotfire. The visualization supports probability-based analysis using normal and lognormal distributions, making it easier to evaluate ranges, identify outliers, and understand the likelihood of different outcomes.
Key capabilities include:
Probability-based visualization using a Probit scale
Support for normal and lognormal distributions
Reference lines for common percentile values such as P10, P50, and P90
Distribution fitting and outlier identification
Interactive analysis integrated with Spotfire filtering and marking
By bringing probabilistic analysis into the Spotfire analytical workflow, users can evaluate uncertainty and risk alongside other operational, geological, and production data.
Spotfire Industry Pro
Reservoir engineers frequently analyze production decline trends to estimate future production and reserves. Spotfire 15.0 introduces built-in Arps decline curve fitting, enabling production forecasting directly within visual analytics workflows.
The feature supports exponential, hyperbolic, and harmonic decline models and integrates with Spotfire filtering, marking, and trellising capabilities. Engineers can interactively evaluate production trends, compare wells, and estimate reserves without leaving the analytical environment.
By bringing decline curve analysis into Spotfire, users can combine forecasting, operational analysis, and production data in a single workflow.
Spotfire Industry Pro
Reference layers help provide context by overlaying additional information such as targets, thresholds, benchmarks, events, and other supporting data directly on visualizations. Spotfire 15.0 expands the flexibility of reference layers, making it easier to combine multiple sources of contextual information within a single analysis.
Reference layers can now:
Use data tables that are independent of the primary visualization data
Apply categorical groupings independently of the primary visualization
Configure styling and color rules separately for each layer
These enhancements make it easier to create richer visualizations that combine operational data with contextual information, helping users compare observations against targets, benchmarks, and other reference data without requiring additional visualizations.
Spotfire Industry Pro
Operational and process data stored in AVEVA PI is critical for monitoring, investigating, and optimizing industrial operations. Spotfire 15.0 introduces a connector for AVEVA PI, enabling engineers and analysts to access time-series and operational technology (OT) data directly within Spotfire.
The connector supports browsing AVEVA Asset Framework (AF) hierarchies and PI Data Archive tags, making it easy to locate and import data required for analysis. Users can configure data retrieval settings such as time ranges, sampling intervals, and retrieval modes to match the needs of their investigation.
Key capabilities include:
Access to AVEVA Asset Framework (AF) hierarchies and PI Data Archive tags
Search for tags, elements, and attributes using native PI search syntax
Paste lists of tags or attributes to quickly select the data you need
Configurable data retrieval settings for each tag table using native PI query syntax
Support for dynamic query configuration using document properties
Windows Integrated Authentication using Kerberos
The connector enables engineers to combine operational data from AVEVA PI with Spotfire analytics and visualizations, enhancing process monitoring, investigation, and optimization workflows.
Spotfire AnalyticsSpotfire Industry Pro
Analytical investigations often focus on periods, intervals, or regions of interest rather than individual observations. When exploring time-series, depth-based, or other continuous data, users frequently need to select and compare ranges that exhibit unusual behavior, trends, or anomalies.
Spotfire 15.0 introduces Range-Based Marking, allowing users to mark and interact with intervals of continuous data directly within visualizations. Marked ranges can be used to drive filtering, comparison, and drill-down workflows across the analysis.
Key capabilities include:
Mark intervals of time, depth, or other continuous measures
Select and compare multiple ranges simultaneously
Drive filtering and linked analysis across visualizations
Create interactive master-detail investigation workflows
By enabling users to work with ranges instead of individual data points, Range-Based Marking makes it easier to investigate patterns, compare events, and explore complex time-series and continuous datasets.
Spotfire Industry Pro
Operational and manufacturing systems generate large volumes of time-series data that are critical for monitoring, investigating, and optimizing industrial processes. Spotfire 15.0 introduces an OPC UA connector, enabling engineers and analysts to access data directly from OPC UA-compatible historians, SCADA systems, and Manufacturing Execution Systems (MES).
The connector simplifies access to operational technology (OT) data by allowing users to browse OPC UA server hierarchies, select tags for analysis, and configure data retrieval settings appropriate for their investigation.
Key capabilities include:
Browsing OPC UA server hierarchies and selecting tags for import
Support for raw, interpolated, and aggregated data retrieval modes
Configurable time windows and aggregation intervals
Support for multiple authentication methods, including certificate-based authentication
The OPC UA connector helps organizations combine operational data with Spotfire analytics to support process monitoring, investigation, and optimization workflows.
Spotfire Industry Pro
Production forecasting and reserves evaluation often require engineers to combine operational data, production forecasts, and economic scenarios to understand asset performance and support investment decisions. Spotfire 15.0 introduces a connector for ComboCurve, enabling users to access forecast and economic planning data directly within Spotfire.
The connector allows engineers to import key project information from ComboCurve and combine it with Spotfire analytics and visualizations to support production, reserves, and economic analysis workflows.
Key capabilities include:
Access forecasts, type curves, and economic scenarios
Import well information and production metrics
Retrieve forecasted production data for analytical workflows
Combine forecast and operational data within a single analytical environment
By bringing ComboCurve data into Spotfire, engineers can evaluate production forecasts, compare development scenarios, and better understand the economic performance of their assets.
Spotfire Industry Pro
Well log data is a critical input for subsurface analysis, reservoir characterization, and asset valuation workflows. Spotfire 15.0 introduces support for Log ASCII Standard (LAS) v2 files, making it easier to import and analyze well log data directly within Spotfire.
The LAS file reader simplifies the process of working with well log datasets by automatically extracting both curve data and well metadata. This reduces data preparation effort and enables users to quickly begin analyzing and visualizing subsurface information.
Key capabilities include:
Import one or more LAS files in a single operation
Automatic extraction of well metadata, including identifiers and location information
Built-in handling of missing values and common data preparation challenges
Direct integration with the Well Log visualization add-on
By streamlining the import and preparation of well log data, the LAS file reader helps geoscientists and engineers move more quickly from raw data to analysis and interpretation.
Spotfire Industry Pro
Geospatial analysis workflows often require data to be shared with GIS applications and mapping tools. Spotfire 15.0 introduces support for exporting data tables containing geometry data to the Esri Shapefile (.shp) format.
This makes it easier to exchange spatial datasets with other geospatial systems and workflows while preserving geographic information stored in Spotfire analyses.
By supporting the widely used Esri Shapefile format, Spotfire helps users integrate analytical and GIS workflows more seamlessly.
Spotfire Industry Pro
Several Spotfire visualization add-ons have been updated to take advantage of the layering capabilities introduced in recent Spotfire releases. These enhancements simplify configuration and make it easier to combine multiple data sources within a single visualization. Updated add-ons include:
Formation data and well spacing data can now be managed independently through separate layers, making it easier to configure and maintain complex visualizations.
The 3D visualization now supports independent layers for surfaces, wells, perforations, markers, and planes. This simplifies data preparation by allowing each visualization element to be sourced from its own data table and configured independently.
The Wellbore Diagram now supports layered configuration and introduces enhancements to trajectory calculations and marker placement. Marker layers allow users to display custom annotations and events at arbitrary locations along the wellbore.
Together, these enhancements improve usability, reduce data preparation effort, and provide greater flexibility when building complex subsurface visualizations.
Spotfire Industry Pro
Spotfire 15.0 expands the collection of analytical action mods. These action mods help users quickly perform common analytical workflows and generate interactive visualizations without requiring extensive manual configuration.
Generate Statistical Process Control (SPC) charts directly from existing analyses. The action mod creates interactive X and R/S charts that help quality engineers monitor process stability and identify out-of-control conditions.
Compute and visualize correlation matrices for numeric datasets. The action mod generates coordinated heatmaps and scatter plots, making it easier to identify relationships and dependencies between variables.
Explore temporal dependencies within time series data by computing autocorrelations, partial autocorrelations, and cross-correlations. The action mod helps users identify periodic patterns, seasonal effects, and relationships between multiple variables.
Together, these action mods make advanced analytical techniques more accessible by automating workflow creation and providing purpose-built visualizations for common investigation scenarios.
Spotfire 15.0 introduces new administrative capabilities that simplify user management, improve governance of library content, and provide greater control over storage and operational management.
Spotfire Enterprise
Enterprise adoption of AI requires visibility, control, and governance. Spotfire 15.0 introduces administrative capabilities that allow organizations to manage access to AI services while maintaining existing security and compliance requirements.
Administrators can configure approved AI services, control which user groups are allowed to use them, and monitor usage across the organization. These capabilities help organizations adopt AI while maintaining appropriate governance and operational oversight.
Additional capabilities for configuring AI services and monitoring usage are described below.
Spotfire administrators can configure connections to approved Large Language Models (LLMs) directly from the administration interface.
Access to individual AI services can be managed at the user and group level, allowing organizations to align AI usage with internal security, compliance, and governance policies.
Spotfire provides visibility into how AI capabilities are being used across the organization.
Administrators can monitor AI activity, track token consumption, and review usage trends by model and user group. Spotfire Deployment Reports have been updated with additional AI-related metrics to support operational monitoring and governance workflows.
Spotfire Enterprise
Managing users and groups is a common administrative task when deploying, maintaining, or migrating Spotfire environments. Spotfire 15.0 introduces support for exporting and importing users and groups directly from the web administration interface.
Administrators can use these capabilities to transfer user and group information between environments, perform bulk administrative operations, and simplify environment setup and maintenance workflows.
By bringing user and group import and export capabilities to the web administration experience, administrators can perform these tasks without relying on the installed client.
Spotfire Enterprise
Information Services administrators regularly manage database configurations to ensure seamless data connectivity across environments. Spotfire 15.0 introduces a web-based administration interface that enables the direct management of data source templates without requiring access to the server configuration tool or command-line interface.
The new interface provides a centralized environment for administrators to streamline their daily workflows:
Create and deploy new templates directly on the server
Modify template XML and control active deployment statuses
Validate compatibility against database drivers installed on the server
Govern configurations using integrated version history and dependency management
Import templates efficiently from alternative servers
By bringing template management capabilities into the web administration console, Spotfire simplifies how power users maintain and update data source configurations.
Spotfire Enterprise
Different library assets often have different retention and governance requirements. While version history can be valuable for preserving important content, some library items may not require version tracking and can contribute to unnecessary storage growth.
Spotfire 15.0 introduces more granular control over library version history. Now administrators can override the previous default global setting and custom default settings per library type, and enable or disable version history for individual library items directly from the web administration interface or from the installed client.
This flexibility makes it easier to align version history policies with organizational requirements and specific usage scenarios, such as project workspaces, shared resources, or automated processes.
Spotfire Enterprise
Library version history provides valuable protection against accidental changes and enables users to restore previous versions of content. Over time, however, version histories can grow significantly and increase storage requirements.
Spotfire 15.0 introduces automatic library pruning, allowing administrators to define the maximum number of unnamed versions retained for each library item. Older unnamed versions are automatically removed when the configured limit is exceeded, helping organizations manage storage growth and reduce administrative overhead.
Named versions are preserved and excluded from automatic pruning, ensuring that important milestones and releases remain available for future reference.
For advanced version management scenarios, administrators can continue to use existing library version management tools and commands.
Spotfire Enterprise
The undo stack helps users recover from mistakes and experiment safely when working with analyses. In long-running or frequently edited analyses, however, the undo history can grow and consume additional storage.
Spotfire 15.0 introduces configurable undo stack pruning, allowing administrators to automatically remove older undo history entries after a defined period of time.
This capability provides greater control over storage consumption while preserving the benefits of the undo experience for day-to-day analytical work. Administrators can configure retention policies to balance storage requirements with user needs.
By default, undo history remains unlimited, preserving existing behavior unless pruning is explicitly enabled.
Spotfire Enterprise
Managing Spotfire deployments often involves coordinating multiple server-side components and services. Identifying compatible versions and locating the appropriate documentation can become more complex as deployments grow.
Starting with Spotfire 15.0 and the latest Spotfire 14.6 LTS service pack, several Spotfire server-side components now share the same major and minor version number as the Spotfire Server, including:
Spotfire Server
Spotfire Web Player
Spotfire Automation Services
Spotfire Service for Python
Spotfire Service for R
Spotfire Service for TERR
By aligning version numbers across these components, Spotfire simplifies deployment planning, documentation lookup, and version management for administrators and operations teams.
Spotfire 15.0 expands extensibility options with support for Custom Insight Agents, enabling organizations to embed domain knowledge, automate analytical workflows, and tailor AI-assisted analytics to their specific needs.
Spotfire AnalyticsSpotfire Industry Pro
Spotfire 15.0 introduces support for Custom Insight Agents, enabling organizations and partners to extend Spotfire AI with their own domain knowledge, business rules, and analytical workflows.
Custom Insight Agents integrate directly into the Spotfire analytical experience and can assist users by identifying findings, recommending next steps, and automating analytical tasks tailored to specific business needs. This allows organizations to capture institutional knowledge and make it available directly within Spotfire investigations.
Custom Insight Agents are developed using the Spotfire Mods framework and can leverage Spotfire data, calculations, library assets, data functions, and approved AI services to perform analysis, generate recommendations, and modify objects in the Spotfire analysis.
Developers can create agents that:
Analyze data and identify patterns, anomalies, or opportunities
Recommend visualizations, workflows, or analytical actions
Automate repetitive investigation tasks
Incorporate proprietary business knowledge and decision logic
Interact with Spotfire analyses through the Mods API
Through the API an insight agent can use:
Data in the Spotfire Analysis data tables
Custom Logic and calculations it implements itself
Calculations by the Spotfire Data Engine using data in the data tables of the analysis
The LLM API (new Mods API)
Built in data functions to run calculations
Normal data functions on the Spotfire library
Data in files on the Spotfire library
Information links on the Spotfire library to load data
Library search to find and use library assets
Insight agents run in two distinct phases, the Insight phase and the Action phase. In the Insight phase, the agent works with a read only copy (a "snapshot") of the Spotfire analysis and can leverage the LLM, Spotfire data engine, data functions and its own calculations to analyze the data and assess the data and/or the Spotfire Analysis. In addition the Insight agent can also prompt the user to provide additional input or make choices. Based on what it finds, it can decide to suggest one or more actions to the user. In the Action phase the agent works with the Spotfire analysis just as if it was a human user and can add, delete and modify any objects in the Spotfire analysis through the Mods API.
Custom Insight Agents participate in the same Insight Agent experience as built-in Spotfire agents, providing a consistent user experience while allowing organizations to tailor AI-assisted analytics to their specific needs.
Developer documentation for Custom Insight Agents is available on the Spotfire Mods GitHub repository.
Spotfire 15.0 continues to expand support for modern enterprise platforms and technologies. This release includes updates to supported software versions and platform compatibility.
Spotfire Enterprise
Spotfire 15.0 adds support for Oracle Database 26ai as the Spotfire database.
For the complete list of supported platforms, operating systems, browsers, databases, and third-party software, see the Spotfire System Requirements documentation.