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AI tools right where you need them

We are not in the business of creating new and powerful AI Models. There are others better equipped to do that. Our focus is to bring AI Tools where you need them - Right into your Atlassian environment. Our innovative approach to AI is designed to transform tedious tasks through automation, seamlessly integrating into your existing toolkit. We're here to empower your team by placing advanced AI tools right at their fingertips. As part of the TIMETOACT group network, we're dynamically bridging ecosystems—from Atlassian to Google, Microsoft, and SAP—using AI to innovate and streamline your workflows.


Atlassian Intelligence

Atlassian Intelligence provides your team with a new virtual teammate that deeply understands how they collaborate to accelerate work. Leveraging AI through internal models and our collaboration with OpenAI, Atlassian Intelligence is built into the Atlassian platform, the common technology foundation across all of our cloud products.



AI Use-Cases: 



Reporting enhanced by AI

We incorporate AI tools into Jira and Grafana and various reporting tools. The reason is that it enables on-the-fly analysis and interpretation of data. Data can vary based on department, timeframe, business unit, and other factors. Our AI integration consistently produces varied interpretations tailored to your specific dataset.


DEMO: AI Analysis of flow distribution

When provided with flow distribution data, our AI integration lets you switch between departments and generates interpretations and recommendations based on the data. These Interpretations can be cashed for greater speed or generated on the fly when the data is updated. 


AI Interpretation


  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    The majority of features within the SAFe ART are categorized under "Business," indicating a focus on value generation. Enabler features are present in each Program Increment (PI), supporting the balance between value generation and protection. There is a low count of Non-Functional features, potentially indicating a need for more focus on aspects like performance, security, and usability.

  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    The data shows a clear emphasis on delivering business value, but there are also enabler features to support the system's overall health and sustainability. The presence of Non-Functional features, although low, highlights the importance of considering aspects beyond pure functionality in the development process.

  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Encourage teams to define and prioritize non-functional requirements early in development in order to address potential performance, security, and usability issues. You can also conduct regular reviews of the flow distribution chart to ensure a balanced investment between value generation and protection, facilitating data-driven trade-off discussions.

Demo: AI flow velocity prediction

Our sample includes story effort, Story value and story count spread across past quarters. Based on the data, our integration provides interpretations, recommendations to improve the accuracy as well as future prediction for flow velocity. 



  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Outliers: PI "QI-4" has a significantly higher velocity compared to the rest, indicating potential outlier stories or exceptionally productive team.

  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Trends: Velocities seem to fluctuate with no clear increasing or decreasing trend over PIs.3.

  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Impact: The high velocity in PI "QI-4" can impact planning in subsequent PIs, potentially setting unrealistic expectations. Dependencies on this team's output may need to be managed carefully to avoid disruptions.


Recommendation for Improvements:
  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Encourage breaking down large work items: To avoid wave-like velocity patterns, work items should be decomposed into smaller, more manageable tasks

  • A robot that looks like a cat that is ready to help and friendly and waving and is orange and yellow-2
    AI Integration

    Regularly review outliers: Investigate the reasons behind the exceptionally high velocity in PI "QI-4" to replicate successful practices across other PIs or address any issues that may arise.


Tools we use for AI enhanced reporting:

Seamless translations in support tickets

Our AI translation Integration uses Jira Automation, API calls and clever configuration to create a seamless translation interface for multilingual support teams. Customers won't even notice that their communication on the ticket is translated. Once the setup of custom fields and automations is completed, the summary of incoming requests will automatically be translated as well as all the comments in the issue. Customers will see relevant information only in their native language. 


issues for translation
Help keep your service cost under control
Minimize frictions in communication across geographical borders
Improve customer experience by offering always-on support ("follow the sun" etc)
jira service management
Works with native Jira Service Management features, no apps required!


Tools we use for seamless translation of issues:

Enhancing JSM Ticket Processing with AI Integration

At the heart of efficient service management lies the ability to swiftly and accurately handle incoming requests. Our AI Integration seamlessly bridges the gap between unstructured JSM tickets and the wealth of information stored in the CMDB. Here’s how it transforms the ticketing process:



Where our AI Integration Makes a Difference:

Streamlined Ticket Structure:
JSM tickets can often be unstructured, making manual screening essential. Our AI sifts through the description to extract all pertinent details, reducing the need for manual intervention.
Automated CMDB Associations:
The AI automatically links incoming requests with relevant CMDB entries. This ensures that the right information is at hand when resolving issues, enhancing accuracy and speed.
Effortless Data Entry:

Custom fields and CMDB Links no longer require manual filling. Our AI populates these fields based on its analysis of the ticket description, saving time and minimizing errors.

Duplicate and Similar Ticket Identification:

The AI scans existing tickets to identify duplicates or similar issues, preventing redundancy and ensuring that each ticket is unique and appropriately addressed.

Priority and Impact Evaluation:

Based on its analysis, the AI evaluates and fills out fields such as Priority and Impact, prioritizing urgent issues and providing a clearer understanding of the ticket’s significance.

Major Incident Identification:

When multiple users are affected, the AI recognizes potential major incidents, enabling timely and coordinated responses to significant service disruptions.


What does this mean for your service team:

Empower your service management with our AI Integration and experience a more efficient, accurate, and responsive ticket processing system that truly understands and caters to your unique needs.



Intelligent Description Screening

The AI meticulously screens the ticket description to decipher CMDB relationships, ensuring that all related data is identified and utilized.

Dynamic Field Population

By analyzing the ticket description, the AI autonomously populates custom fields with appropriate content, further enhancing the ticket’s completeness and relevance.

Existing CMDB Structure Linkage

If related data is found, the AI establishes a connection between the ticket and the existing CMDB structure, fostering a more integrated and comprehensive approach to issue resolution.



Tools we use for enhancing JSM ticket processing:

LLM-Agnostic integrations

At our core, we embrace innovation by not limiting ourselves to a single LLM provider. Our team is dedicated to crafting dynamic middleware solutions, empowering you to seamlessly connect with any LLM service you need. With enthusiasm and expertise, we're building a versatile framework designed to integrate effortlessly into your daily tools, ensuring you receive the support you need, whenever you need it.



You're in great company!


As a proud member of the TIMETOACT Group, we harness our specialized knowledge within the Atlassian ecosystem, merging it with X-Integrate's advanced AI integration insights and Trustbig's prowess in data science and automation. This synergy empowers us to cover an expansive array of use cases and applications, seamlessly weaving AI solutions into everyday tools you can rely on.













Data Science & Automation

Artificial Intelligence Whitepapers:

Level up with Jira Software Cloud

This document is a comprehensive overview aimed at Atlassian customers, focusing on the advantages of Jira Software Cloud for software development teams. It emphasizes how Jira Software Cloud facilitates faster innovation and higher returns on investment ...

A vision for IT service management at high velocity

This whitepaper explores the concept of high-velocity IT service management (ITSM) and its importance in modern business. It highlights the shift from traditional ITSM approaches to agile, collaborative, and fast-paced methodologies. By focusing on speed ...

Guide to Atlassian Intelligence

The whitepaper explores Atlassian Intelligence, an AI-powered feature integrated into Atlassian's cloud products like Confluence, Bitbucket, and Jira. It details how AI boosts individual and organizational productivity by automating tasks, generating ...

Server to cloud: Why make the move?

This whitepaper delves into the advantages of transitioning from self-managed solutions to Atlassian Cloud. It highlights the benefits of cloud-based offerings, such as continuous innovation, reduced downtime, and lower total cost of ownership. The ...

What’s new and better in Atlassian Cloud?

The text highlights the advantages of Atlassian Cloud products over server-based solutions. It emphasizes three key aspects: ROI, innovation, and time to value. Cloud offerings provide cost savings by eliminating hosting and hardware expenses, allowing ...

Reporting for Duty: Switch to Jira Service Management for better incident and alert management

The text highlights the advantages of migrating to Jira Service Management from PagerDuty for efficient incident and alert management. It emphasizes six key benefits: streamlined incident resolution, seamless collaboration among teams, advanced ...

Our team stands ready


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