Roadmap & Releases
Preparing the tester's toolkit of tomorrow
The rapid evolution of development and testing practices is transforming the needs of QA teams. Our roadmap reflects this momentum by strengthening AI integration, test automation, alignment with DevOps pipelines, and traceability and collaboration capabilities.
It is also shaped by feedback from our user community, addressing the concrete needs encountered in the field.
Our goal is to offer a modern, scalable platform able to support organisations over the long term in their software quality challenges.
Strategic themes
Three main directions guide the evolution of SquashTM in 2026 and 2027.
AI integration
We are developing AI features designed to assist testers while leaving them in control. Our approach favors transparency, traceability, and integration into existing processes, putting AI at the service of software quality.
Develop generation capabilities among the most advanced on the market, with full control over prompts, enrichment through multimodal context (documents, images, requirements, existing test assets…) and support for various output formats: classic test cases, BDD/Gherkin, datasets, and other test artifacts.
Strengthen governance of AI usage through logging of model interactions, usage monitoring, and traceability mechanisms that allow generated content to be identified and audited.
Integrate with third-party execution agents capable of interacting directly with application interfaces, to run end-to-end scenarios written in natural language from SquashTM and centralise their results there.
DevOps ecosystem integration
SquashTM is committed to openness and interoperability, integrating naturally with the tools and processes used by development and QA teams.
Provide native integration with OpenProject to strengthen interoperability with the open-source and sovereign ecosystem. This integration will make it easier to align project management and testing activities within a coherent toolchain.
Enable launching and monitoring pipelines directly from SquashTM, bringing testing activities closer to continuous delivery processes and simplifying the orchestration of automated campaigns.
Provide an MCP server to allow AI assistants and third-party tools to interact with SquashTM in a secure, standardised way. This approach will make it easier to integrate SquashTM into new AI-driven workflows.
Governance, trust and data value
We want to make SquashTM a reference platform guaranteeing the integrity, traceability, and value of test data. The information it produces must be reliable, secure, and actionable, meeting regulatory requirements, supporting decision-making, and helping organisations in their continuous improvement efforts.
Strengthen end-to-end traceability to guarantee transparency of activities, justification of decisions, and compliance with regulatory and normative requirements. The goal is to give organisations what they need to demonstrate control of their quality processes during audits or inspections.
Develop a robust platform ensuring the availability, integrity, and protection of test data. This includes strengthening security mechanisms, managing data-related risks, and maintaining operations even in the event of an incident or changes to the technical environment.
Turn test data into a management lever by developing advanced analysis, reporting, and integration capabilities with decision-support ecosystems. The goal is to give teams and leaders reliable indicators, consolidate data into their analytics platforms, and inform decisions through better use of the information produced by SquashTM.
Timeline
- AI test case generation (GA)
- Simplified AI server configuration
- Improved assistance for selecting test cases to automate
- Admin trash and restoration of deleted test cases
- Enriched AI context
- Generation of parameterised test cases
- Default prompts
- Sprint display in Xsquash DC
- Advanced dataset management
- Project-level AI prompt management
- AI usage oversight
- Automated test reporting
- Gherkin test case generation
- Jira service account
- OAuth 2.0 for Jira Cloud
- Dataset import/export
- Per-project cleanup preferences
- Lynqa integration
- MCP server
- CI/CD triggering
- OpenProject bugtracker
- Synchronise requirements with OpenProject
- Saved searches
- One-time password
- Change history
- Xray project import
- JUnit execution results ingestion
- Data security
- Multi-instance deployment
- Test case comments
- SquashTM project import/export
- User notifications
Detailed roadmap
Browse all planned features, organised by version.
Previous releases
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