Maciej Saganowski is the Director of AI Merchandise at Appfire.
Appfire is a number one supplier of enterprise software program options designed to reinforce collaboration, streamline workflows, and enhance productiveness throughout groups. Specializing in instruments that combine with platforms like Atlassian, Salesforce, and Microsoft, Appfire affords a sturdy suite of apps tailor-made for mission administration, automation, reporting, and IT service administration. With a world presence and a dedication to innovation, the corporate has grow to be a trusted associate for organizations in search of to optimize their software program ecosystems, serving a variety of industries and empowering groups to attain their objectives effectively.
Appfire is understood for offering enterprise collaboration options, are you able to introduce us to Appfire’s strategy to growing AI-driven merchandise?
Over the previous yr, the market has been flooded with AI-powered options as firms pivot to remain related and aggressive. Whereas a few of these merchandise have met expectations, there stays a possibility for distributors to really tackle actual buyer wants with impactful options.
At Appfire, we’re targeted on staying on the forefront of AI innovation, enabling us to anticipate and exceed the evolving wants of enterprise collaboration. We strategy AI integration with the intention of delivering actual worth reasonably than merely claiming “AI-readiness” just for the sake of differentiation. Our strategy to growing AI-driven merchandise facilities on creating seamless, impactful experiences for our clients.
We wish AI to mix into the person expertise, enhancing it with out overshadowing it or, worse, creating an additional burden by requiring customers to be taught solely new options.
“Time to Value” is likely one of the most important goals for our AI-powered options. This precept focuses on how rapidly a person—particularly a brand new person—can begin benefiting from our merchandise.
Appfire has partnered with Atlassian to launch WorkFlow Professional as a Rovo agent. What makes this AI-powered product stand out in a market crammed with comparable merchandise?
This class of merchandise is comparatively unusual. We’re one of many first firms to ship a Jira-class software program automation configuration assistant—and that is solely the start.
WorkFlow Professional is an AI-powered automation assistant for Jira that’s reworking how groups arrange and handle their automation workflows. Powered by Atlassian’s Rovo AI, it assists customers in configuring new automations or troubleshooting present ones.
Traditionally, Jira automation merchandise have been complicated and required a selected stage of experience. WorkFlow Professional demystifies these configurations and permits new or less-experienced Jira admins to perform their duties with out spending time on product documentation, boards, or risking expensive errors.
A brand new Jira admin can merely ask the agent the way to carry out a process, and based mostly on the automation app put in (JMWE, JSU, or Energy Scripts), the agent supplies a step-by-step information to reaching the specified final result. It’s like having a Michelin-star chef in your kitchen, able to reply any query with exact directions.
At Appfire, we’re dedicated to simplifying the lives of our clients. Within the subsequent model of WorkFlow Professional, customers will be capable to request new automations in plain English by merely typing the specified final result, with out the necessity to navigate the configurator UI or know any scripting language. Returning to our chef analogy, the subsequent model will permit the person not solely to ask the chef the way to cook dinner a dish however to arrange it on their behalf, liberating them as much as concentrate on extra essential duties.
How do you contain person suggestions when iterating on AI merchandise like WorkFlow Professional? What function does buyer enter play in shaping the event of those instruments?
At Appfire, we keep very near our customers. Not solely do our designers and product managers interact usually with them, however we even have a devoted person analysis group that undertakes broader analysis initiatives, informing our imaginative and prescient and product roadmaps.
We analyze each quantitative information and person tales targeted on challenges, asking ourselves, “Can AI help in this moment?” If we perceive the person’s downside nicely sufficient and imagine AI can present an answer, our crew begins experimenting with the know-how to handle the difficulty. Every characteristic’s journey begins not with the know-how however from the person’s ache level.
For example, we discovered from our customers that new admins face a major barrier when creating complicated automations. Many lack the expertise or time to review documentation and grasp intricate scripting mechanisms. WorkFlow Professional was developed to ease this ache level, serving to customers extra simply be taught and configure Jira.
Past WorkFlow Professional, Appfire plans to develop extra AI-driven purposes. How will these new merchandise remodel the way in which customers set objectives, observe work, and harness information extra successfully?
AI can have a profound affect on what future data staff can accomplish and the way they work together with software program. Organizations will evolve, changing into flatter, extra nimble, and extra environment friendly. Tasks would require fewer folks to coordinate and ship. Whereas this appears like a daring prediction, it’s already taking form by means of three key AI-powered developments:
Offloading technically complicated or mundane duties to AIInteracting with software program utilizing pure languageAgentic workflows
We’re already seeing AI cut back the burden of mundane duties and ease new customers into these merchandise. For example, AI assistants can take assembly notes or record motion objects. For instance this on the Appfire instance, when a supervisor creates a brand new Key End result inside their OKR framework, the AI will counsel the Key End result wording based mostly on business greatest practices and the corporate’s distinctive context, easing the psychological load on customers as they be taught to outline efficient OKRs.
Pure language interfaces symbolize a serious paradigm shift in how we design and use software program. The evolution of software program over the previous 50 years has created just about limitless capabilities for data staff, but this interconnected energy has introduced vital complexity.
Till lately, there wasn’t a simple solution to navigate this complexity. Now, AI and pure language interfaces are making it manageable and accessible. For instance, one in every of Appfire’s hottest app classes is Doc Administration. Many Fortune 500 firms require doc workflows for compliance or regulatory assessment. Quickly, creating these workflows may very well be so simple as chatting with the system. A supervisor would possibly say, “For a policy to be approved and distributed to all employees, it first needs to be reviewed and approved by the senior leadership team.” AI would perceive this instruction and create the workflow. If any particulars are lacking, the AI would immediate for clarification and provide suggestions for smoother flows.
Moreover, “agentic workflows” are the subsequent frontier of the AI revolution, and we’re embracing this at Appfire with our agent WorkFlow Professional. Sooner or later, AI brokers will act extra like human collaborators, able to tackling complicated duties comparable to conducting analysis, gathering info from a number of sources, and coordinating with different brokers and other people to ship a proposal inside hours or days. This agent-run strategy will transcend easy interactions like these with ChatGPT; brokers will grow to be proactive, maybe suggesting a draft presentation deck earlier than you even notice you want one. And voice interactions with brokers will grow to be extra frequent, permitting customers to work whereas on the go.
In abstract, the place we’re heading with AI in data work is akin to how we now function automobiles: we all know the place we need to go however sometimes don’t want to know the intricacies of combustion engines or fine-tune the automotive ourselves.
You’re additionally enhancing present Appfire merchandise utilizing AI. Are you able to give us examples of how AI has supercharged present Appfire apps, boosting their performance and person expertise?
Every of our apps is exclusive, fixing distinct person challenges and designed for varied person roles. Consequently, using AI in these apps is tailor-made to reinforce particular features and enhance the person expertise in significant methods.
In Canned Responses, AI accelerates buyer communication by serving to customers rapidly formulate responses based mostly on the content material of a request and present templates. This AI characteristic not solely saves time but in addition enhances the standard of buyer interactions.
In OKR for Jira, for instance, AI may help customers who’re new to the OKR (Goal and Key Outcomes) framework. By simplifying and clarifying this usually complicated methodology, AI may present steering in formulating efficient Key Outcomes aligned with particular goals, making the OKR course of extra approachable.
Lastly, WorkFlow Professional represents an progressive solution to work together with our documentation and exemplifies our dedication to agentic workflows and pure language automation requests. This AI-driven strategy reduces the barrier to entry for brand new Jira admins and streamlines workflows for knowledgeable admins alike.
Shared AI companies, such because the summarization characteristic, are being developed throughout a number of Appfire apps. How do you envision these companies impacting person productiveness throughout your platform?
At Appfire, we have now a broad portfolio of apps throughout a number of marketplaces, together with Atlassian, Microsoft, monday.com, and Salesforce.
With such a big suite of apps and numerous use circumstances for AI, we took a step again to design and construct a shared inside AI service that may very well be leveraged throughout a number of apps.
We developed a platform AI service that permits product groups throughout our apps to connect with a number of LLMs. Now that the service is reside, we’ll proceed increasing it with options like regionally run fashions and pre-packaged prompts.
With the speedy evolution of AI applied sciences, how do you make sure that Appfire’s strategy to AI growth continues to fulfill altering buyer wants and market calls for?
At Appfire, a product supervisor’s high precedence is bridging the hole between technical feasibility and fixing significant buyer issues. As AI capabilities advance quickly, we keep updated with market traits and actively monitor the business for greatest practices. On the client aspect, we frequently interact with our customers to know their challenges, not solely inside our apps but in addition within the underlying platforms they use.
Once we determine an overlap between technical feasibility and a significant buyer want, we concentrate on delivering a safe and sturdy AI characteristic. Earlier than launching, we experiment and take a look at these options with customers to make sure they genuinely tackle their ache factors.
Appfire operates in a extremely aggressive AI-driven SaaS panorama. What steps are you taking to make sure your AI improvements stay distinctive and proceed to drive worth for customers?
Appfire’s strategy to AI focuses on objective. We’re not integrating AI simply to examine a field; our objective is for AI to work so naturally inside our merchandise that it turns into nearly invisible to the person. We wish AI to handle actual challenges our clients face—whether or not it’s simplifying workflows in Jira, managing complicated doc processes, or streamlining strategic planning. Ideally, utilizing AI ought to really feel as intuitive as selecting up a pen.
Many SaaS merchandise have historically required specialised experience to unlock their full potential. Our imaginative and prescient for AI is to scale back the educational curve and make our apps extra accessible. With the launch of our first Rovo agent, WorkFlow Professional, we’re taking an essential step on this journey. Finally, we intention to make sure AI inside our apps permits customers to attain worth extra rapidly.
Wanting forward, what traits in AI growth do you suppose can have the best affect on the SaaS business within the coming years?
Two main AI traits that can form the SaaS business within the coming years are the rise of AI-powered brokers and rising issues about safety and privateness.
Some argue that agent know-how has but to reside as much as its hype and stays comparatively immature. To those skeptics, I’d say that we frequently overestimate what know-how will obtain in 1–2 years however vastly underestimate what it’s going to accomplish over a decade. Whereas present agent use circumstances are certainly restricted, we’re witnessing large investments in agentic workflows all through the software program worth chain. Foundational fashions from firms like OpenAI and Anthropic, together with platforms Appfire at present operates or plans to function on, are making intensive investments in agent know-how. OpenAI, as an illustration, is engaged on “System 2” brokers able to reasoning, whereas Anthropic has launched fashions able to utilizing common apps and web sites, emulating human actions. Atlassian has launched Rovo, and Salesforce has launched Agentforce. Every week brings new bulletins in agentic progress, and, at Appfire, we’re enthusiastic about these developments and sit up for integrating them into our apps.
On the similar time, as AI capabilities increase, so do the dangers related to information safety and privateness. Enterprises should make sure that any AI integration respects and protects each their belongings and people of their clients, from delicate information to broader safety measures. Balancing innovation with sturdy safety practices can be important to unlocking AI’s full worth in SaaS and enabling accountable, safe developments.
Thanks for the good interview, readers who want to be taught extra ought to go to Appfire.
