Say hi to Appfire AI
AI-powered features, embedded across our products — secure, scalable, and designed to optimize workflows with intelligent automation, all while keeping data secure.
AI built for real work
AI is reshaping the way teams work — and at Appfire, we see it as a catalyst for thoughtful, lasting transformation. Appfire AI features are built into the tools teams already trust, helping them move faster, automate tasks, and onboard with ease. Always private, always transparent, and never trained on your data - these features bring intelligence into workflows without disruption.
Boost productivity without giving up control
Built to integrate with your existing ecosystem, Appfire’s AI features follow strict data practices and are built with enterprise security and transparency in mind — so you can innovate with confidence.
Smarter workflows, without added complexity
AI embedded into the platforms your teams already use. Automate manual work, uncover insights, and speed up decision-making — without disrupting existing processes.
Faster time-to-value for your teams
From AI-powered automation to intelligent recommendations, our AI features help teams reduce unnecessary work and focus on strategic priorities — without requiring process changes.
Built to scale with your business
As teams grow and workflows evolve, our AI features adapt — helping you handle complexity without slowing down. It’s AI that grows with you.
Canned Responses Pro
Canned Responses Pro uses AI to surface the most relevant templates and generate personalized replies — helping agents respond faster, with less effort. By streamlining support, teams improve customer experiences and scale with confidence.

Live Fields for Jira Cloud
Customize field behavior with AI. As you create a ticket, AI checks your input, corrects grammar, and translates when needed — meaning fewer edits, fewer errors, and clearer communication across teams. Included free with JMWE or Power Scripts.

Agile Poker for Jira Cloud
Agile Poker uses AI to guide faster, smarter estimations. It scans issue details to surface risks, dependencies, and related work — then suggests a realistic effort estimate based on past data. Teams get full context and smarter starting points, streamlining sprint planning.

FAQ’s
The Appfire AI label identifies AI-powered features thoughtfully embedded in our existing products. Below are answers to common questions about how these features work, how they’re governed, and how to start using them.
Appfire AI is the label for AI-powered features embedded across our portfolio of apps, using machine learning (ML) and large language models (LLMs) to solve real customer challenges. Each feature is designed to streamline work, enhance usability, and help teams move faster with less effort. Our AI features support faster onboarding for new users and gives experienced users more speed and confidence in their day-to-day workflows. Powered by Azure AI, Microsoft’s industry-leading platform, Appfire AI is built with enterprise-grade security, reliability, and performance — and never uses customer data to train external models.
All of our AI features, including the ones listed on this page, are available to all users. Please refer to Appfire Product Documentation to learn more about a specific AI feature.
We use multiple large language models depending on the task. Appfire ensures that none of the providers train their models based on our customer data. For details on how each one works, please refer to our subprocessors list.
Our AI features undergo extensive testing and evaluations before being published. However, we cannot guarantee 100% accuracy or relevancy of AI-generated answers due to the inherent lack of full predictability in AI technologies. To ensure transparency, each AI feature is clearly marked with a distinct color scheme, symbol, and the “Appfire AI” label — so users always know when AI is being used. We recommend that users double-check the AI output or recommendations for correctness. Despite these limitations, we continually monitor our AI features for potential misalignment and take prompt action to reduce or eliminate them when identified.
The features marked “beta” are continuously improving and undergo regular testing and evaluations. As such, they are subject to change, suspension, or removal. Our intention with marking our AI features as “beta” is to notify our customers that these features are still evolving and might produce occasional errors. Once the work on a feature is complete, the label “beta” will be removed.
There’s currently no additional charge for using our AI features. However, some features may have monthly usage limits or be available only on higher pricing tiers to help manage resource usage.
If you can’t find a particular AI feature in your app — even though it’s advertised on this page, the product page, or in documentation — it may still be rolling out across our user base. We use gradual rollouts to launch new features, if you’d like to be included in the rollout sooner, contact our support team.
If your usage exceeds the monthly quota of AI credits, the AI feature may temporarily disable itself. We strive to provide enough credits for every customer and actively monitor how quickly those quotas are reached. If a feature is disabled due to exceeded credits, it will automatically re-enable at the start of the next month. These measures are provisional and may be changed in the future. If you need help with a feature that has been limited, don’t hesitate to contact our support team.
We use our standard data protection practices to keep your data protected and private. Please refer to our Trust Center for more details. We use your data in accordance with our Gen AI terms, only to the extent required to deliver the AI services to you and to monitor and improve the quality of our products.
Administrators can turn individual AI features on or off, or configure them further. This control is available in the app configuration screen (also known as app settings).
No. We don’t use your data, your prompts (questions submitted to AI features), or the AI-generated responses to train large language models. We have contractual agreements with our AI sub-processors that prohibit the use of customer data for model training. Please refer to our Trust Center for more information about data processing and sub-processors.
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