Roadmap

Centralized Authentication

Users currently may encounter different authentication mechanisms across individual ADITO services. A shared authentication foundation will provide a consistent user identity across connected services and enable permissions to be applied reliably.

Entity Model Performance

The entity model is a central foundation for business logic across the ADITO platform and supports a wide range of use cases. This initiative focuses on identifying and resolving performance bottlenecks while maintaining the flexibility of the existing model.

• Establish meaningful performance metrics
• Identify bottlenecks based on real usage scenarios
• Optimize model structures and execution where improvements have the greatest impact

Dedicated Background Server

Background processes currently run on servers that provide more functionality than these workloads actually require. A dedicated background server will provide a more focused environment for scheduled processes and other backend workloads, helping to use server resources more efficiently.

Centralized System Configuration

System configuration is currently closely tied to the Designer and, for some changes, direct database access. Moving configuration into a central environment will simplify administration, reduce technical dependencies, and make configuration easier to manage across system versions.

• Central management instead of direct database configuration
• Guided and easier configuration workflows
• Reduced coupling between Designer and server
• Foundation for easier upgrades through more version-independent configuration

Accessible Client Experience

Core client components are being improved to provide a more accessible and responsive experience for all users, including people who rely on assistive technologies or keyboard navigation. Existing components will be reviewed and adapted where necessary while preserving the functionality users already rely on.

• Improved accessibility of record previews
• Better keyboard navigation and support for assistive technologies
• Responsive layouts for narrow screen sizes

Advanced Table Column Management

The new table will gain the column management capabilities users already expect from the existing table. Users will be able to configure how columns are displayed and how data is sorted while retaining accessible operation.

• Show, hide, and reorder columns
• Sort by one or multiple columns
• Accessible column management

Accessible Filtering

Filtering is a central part of working with business data. The standard filtering experience will be redesigned so that existing filtering capabilities remain available in a more accessible and responsive interface, including on narrow screen sizes.

Improved Lookup Tables

The new BasicTable will also become available in lookup dialogs, providing a consistent and accessible way to find and select records from responsive tables with multiple rows and columns.

Secure AI Chat

A standalone AI chat provides a controlled and data-sovereign way to use language models within the ADITO environment. It serves as the foundation for future AI capabilities while remaining independent from the existing CRM frontend.

Enhanced AI Infrastructure

ADITO is expanding its own AI infrastructure with dedicated high-performance servers. The additional computing capacity will enable significantly more powerful AI models to be hosted and operated within the ADITO environment, creating the foundation for more advanced AI capabilities in the future.

ADITO MCP Server

The ADITO MCP Server will connect AI capabilities with ADITO data and functionality through the Model Context Protocol. It provides a common foundation for future AI use cases that go beyond standalone conversations and interact with the Adaptive Business Platform.

AI-Powered Company Data Search

Semantic search will make it possible to find relevant company information based on meaning rather than exact keywords. This helps users discover related records, documents, or other business information even when different terminology is used.

• Find related information based on meaning and context
• Go beyond exact keyword matches
• Create a foundation for AI-assisted access to company data

AI-Assisted YAML Customizing

YAML-based customizing offers flexibility, but translating functional requirements into the right technical changes can be challenging. AI-assisted customizing will help developers turn requirements into suitable YAML changes while keeping every modification transparent, reviewable, and under their control.

• Translate functional requirements into suggested YAML changes
• Consider project structures, references, and dependencies
• Validate generated or modified YAML before changes are applied

Advanced YAML Editing

Experienced developers often prefer working directly with YAML. Improved editor capabilities will make this workflow faster and more reliable by providing contextual assistance and easier navigation across connected project files.

• Context-aware snippets and code completion
• Quick navigation to referenced definitions and linked YAML files
• Integrated documentation and validation

YAML Overrides

Changes to existing modules currently create multiple modifications that can become difficult to understand and maintain over time. A simplified override concept is intended to make custom changes easier to organize, review, and maintain.

• One structured override per data model and module
• Clear visual representation of customized elements
• Reduced complexity when maintaining existing projects

Visual YAML Model Editor

Working directly in YAML requires understanding its structure and syntax. A side-by-side editor will provide a visual representation that stays synchronized with the YAML source in real time, making data models easier to work with without giving up source-level control.

• Graphical editing of objects, fields, and relationships
• Real-time synchronization between visual view and YAML source
• Templates, visual guidance, and intuitive editing for getting started