A walkthrough of an AI-powered project management tool for SQL work. Shows how to define projects, collaborate with stakeholders, set goals, get AI solution proposals, and generate reports.
Hi. I'm going to walk you through our agent experience for SQLs with creating a new project. We're going to guide the user in how to organize for the project, collaborate with stakeholders for compelling overviews and then match dynamically with the right vendors and experts. They need to know as they define the project based upon the project context. First you do is you click define a new project. If you're going to start a new project, I'll call this one CRM Sales. I'll enter a project product description. We want to deploy sales focus CRM that drives modern automation AI pipeline. Great project project. It's creating the user to do and guide them through is defining the project in detail. What are they trying to accomplish with the project? Stakeholder mapping. Who are the relevant people that need to collaborate with and get insight from to be successful with the project? This will be defining what we need to accomplish and then how we accomplish it with technology. And the resulting requirements for the project will fall from fall out of that engagement and then the reports and insights. This is where it brings everything together so that we can communicate effectively across the different organizations that you need to to get approved for a product. So start here with the problem definition. This is an area where we're guiding the user through thinking through what is the problem that they're trying to solve. What are the primary strategic benefits the CRM Sales project aims to deliver to the organization? We are using our agenic agent suggest what we found to be impactful ways to articulate this problem from other projects. So improve team efficiency, productivity, enhanced customer engagement, accelerate revenue growth, better pipeline management. Let's select that as one. Let's suggest additional so efficiency, productivity, customer accelerating revenue growth through automation that as a particular goal. Let's add another one here, a custom one and it'll say drive pipeline faster by leveraging AI. Submit answer. What this does is it starts to define what this problem is and the system will continuously guide me through getting more intelligence that I might want to add to the problem definition. After I'm done with that, I can move on to stakeholder mapping. This is where I can add different stakeholders. I can use AI to recommend different stakeholders. AI will use or will suggest stakeholders based upon what what type of project this is, what type of software you'd be deploying, what type of business strategy you need to engage with. Here it's suggesting you need to get people from the sales leadership team IT marketing because it's still related to pipeline generation. Once you create a stakeholder, it creates a little icon you can then too give minimal effort, keep satisfied key players, keep informed as well as assign different stakeholders to different goals, requirements, et cetera throughout the project. The next step would be goals. This is where I can add a new goal that I define. AI will also create suggestions, accelerate revenue growth. Leveraging AI automation to streamline sales processes. Yeah, let's make that part of this particular goal. Add enhanced sales team efficiency. Yep, let's do that. Let's improve data driven decision making. Reduce sales cycle time. Through doing this. Let me add a new goal that I come up with myself. Let's call this one AI pipeline. Right. High priority description. Leverage AI to drive new pipeline. Okay, so let me add that. Who's it assigned to, who's it suggested by? I can add those. Where am I in the process? I'm going to add that goal. All right, so once I got goals added, we then are going to propose solutions. I can create one myself and add it in here. I can also use AI to suggest, to suggest goals. So I'm going to use a pipeline. The system was going to then. AI driven lead scoring and prioritization, predictive sales forecasting, automated outreach and engagement. We add that as one of the projects. AI driven lead scoring. Let me add that as one of the solutions. So I'm then adding the proposed solutions that need to be part of this project. I can move those from proposed to under review to. If I moved it to under review, it'll come over here, I can approve it. These will be based upon who's assigned to the particular solution. You can move them from this proposed state to an approved state. All right, so then let me just do a high level sum up. If I go to the AI reports and insights, let me just look at the problem solution report and generate that that will provide me with a report. The report's been generated directly from the data and insights that I've added based upon the context that was gathered, what we know about creating successful report projects and then articulating from the information we have that our customers have had the KPIs, the success that they've had with similar projects in the marketplace. So here are some quantitative impact statements. The financial impact that's anticipated from this project based upon what I defined the risk and out assessment. Why now? Rapid digitization, Increased competition require immediate adoption of AI driven sales processes. Competitors are leveraging advanced CRM and automation, creating urgency to modernize Blue's market share. CRM sales aligns tightly with organizational goals to drive revenue growth, etc. The proposed solutions are presented here. The success criteria Build versus Buy analysis of this particular project and then highlight highlight implementation strategy. So this is a high level overview of the problem solution analysis. As you can see the different reports cross Executive Summary, Problem Solution Report Infrastructure Discovery, Business Case, Financial highlights, Build versus Buy requirements and details.
