Projekts AI
Last Updated
Overview
Projekts AI helps teams turn ideas and requirements into structured specifications, user stories, and sprint plans within a shared workspace. Although documentation gaps may affect workflows, its flexible AI model options and cost-tracking dashboards help teams maintain visibility and control over AI-assisted software delivery.
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Starting Price
$500
per year
Projekts AI Specifications
- Task Management
- Reporting
- Budget Management
- Resource Allocation
What Is Projekts AI?
Pojekts AI is an AI-powered software development workspace that helps product, design, and engineering teams coordinate planning and delivery. Guided workflows turn ideas and requests for proposals (RFPs) into product requirements documents (PRDs), user experience (UX) specifications, architecture documents, and sprint plans, keeping project information accessible across development stages.
The platform also offers specialized AI agents, persistent chat sessions, and shared project documents. Its dashboards track AI usage, costs, and delivery progress across projects and teams, helping engineering leaders monitor development activities and resource consumption.
What Is Projekts AI Best For?
Projekts AI stands out for its PRD Generator, which creates structured product requirements documents in real time from an initial idea. These documents cover user personas, goals, functional requirements, and success metrics. Each PRD is saved as a live project artifact, giving teams a shared reference before development tickets are created.
How Much Does Projekts AI Cost?
Projekts AI pricing starts at $500/year for its on-premises solution, allowing organizations to run the software on their own Infrastructure with control over servers, databases, and LLM APIs.
Following are the additional estimated costs you need to consider before planning:
- Server And Infrastructure: $100–$1,000/month for server hosting and maintenance
- LLM API Usage: $50–$500/month, depending on AI model usage
- Workflow Configuration: $500–$3,000 one-time for customizing project workflows
- Integrations: $50–$300/month for third-party tool connections and data synchronization
Disclaimer: The pricing is subject to change.
Projekts AI Integrations
Projekts AI integrates with various platforms, such as:
How Does Projekts AI Work?
Here is how you can get started with the software by following the steps below:
- Log in to the Projekts AI workspace using authorized credentials
- Access the Engineering Dashboard to view AI workflows, sessions, agents, and project documents
- Organize development activities across businesses, domains, projects, and teams
- Assign team members to relevant projects and configure role-based access permissions
- Select AI workflows for generating product requirements documents (PRDs), architecture specifications, user stories, and sprint plans
- Configure access to supported AI models based on workspace requirements
- Review automatically saved documents and persistent AI sessions to track project decisions and development requirements
- Monitor sprint health, delivery progress, and team performance through KPI dashboards
- Track AI token consumption, session costs, and available credit limits to oversee resource usage
Who Is Projekts AI For?
Projekts AI is suitable for organizations managing software development projects across the following sectors and industries:
- Information technology
- Software development
- Financial services
- Healthcare
- Education
- Telecommunications
- Ecommerce
Projekts AI Use Cases
Based on our analysis of Projekts AI's capabilities, we have identified key scenarios where this software is a strong fit for product, design, and engineering teams:
Engineering Directors Monitoring Delivery Across Multiple Projects
Engineering directors overseeing multiple software projects may struggle to identify declining sprint performance or uneven workloads across teams. Projekts AI's KPI Dashboards provide domain-level visibility into project health, sprint velocity, and team assignments. Directors can identify projects with declining performance and drill down into project-level dashboards to investigate delivery bottlenecks and review assigned work without switching between separate reporting tools.
Scrum Masters Managing Stalled Sprint Tasks
Scrum Masters overseeing active development sprints may struggle to identify stories stuck in review or tasks without assigned owners. Projekts AI's Kanban Board displays stories across workflow stages, with assignees, priority indicators, and story points visible on each card. Scrum Masters can review stalled tasks, examine acceptance criteria, and move stories between stages using drag-and-drop functionality to maintain visibility into sprint progress.
Engineering Teams Tracking Tasks Across Multiple Development Tools
Engineering teams managing tasks in Jira and code changes in GitHub may struggle to maintain consistent project records across separate platforms. Projekts AI's integration capabilities are designed to consolidate issue updates, pull requests, commits, and review activity into a shared workspace. Through webhook-based synchronization and periodic polling, teams can keep project information updated without manually transferring records between systems.
Is Projekts AI Right For You?
Looking for software that keeps requirements, architecture, and user stories in one shared workspace instead of scattered chat windows? Projekts AI suits product and engineering teams that need consistent project context across planning and delivery.
Role-aware access and workspace boundaries help organize project knowledge, while enterprise single sign-on (SSO) supports centralized access management.
Teams can also choose on-premises deployment to retain control over their server, database, and AI model APIs. Its Data Processing Agreement outlines data-handling practices and ongoing work toward GDPR alignment.
Still not sure if the software is right for you? Contact us at (661) 384-7070, and we will help you make the best decision regarding Projekts AI features and more.
Projekts AI Features
Kanban Board
This feature allows teams to organize development tasks through a visual Kanban board. Users can move stories between workflow stages using drag-and-drop functionality, with status changes synchronized in real time. Each card links to its source requirement, helping project managers and developers track task progress while maintaining access to relevant project context.
AI Cost Tracking
Projekts AI tracks token consumption and associated costs at the project level in real time. Administrators can configure credit caps for individual users or entire workspaces to manage spending. This functionality provides engineering leaders with visibility into AI resource consumption and helps organizations monitor costs across software development activities.
Engineering Dashboard
The platform provides a centralized dashboard displaying software development lifecycle (SDLC) phases, specialized AI agents, chat sessions, and generated documents. Teams can monitor blocked user stories, sprint health, velocity trends, and outstanding decisions from the same workspace. This consolidated view helps engineering managers evaluate delivery progress and access project information.
Architecture Documents
Projekts AI generates architecture decision records (ADRs), system diagrams, and application programming interface (API) contracts based on existing project context. Software architects can revisit these documents as development progresses, helping maintain consistency between technical decisions and evolving project requirements. The generated documentation remains connected to the relevant project workspace.
Epics And Story Breakdown
The software breaks down product requirements documents (PRDs) into epics and user stories with defined acceptance criteria. Each story maintains a connection to its original requirements, allowing development teams to understand the scope and purpose of assigned work. This structured approach supports backlog preparation and helps teams manage project requirements.
Pros And Cons of Projekts AI
Pros
Improves visibility into ongoing software development activities
Helps teams maintain consistent project documentation
Reduces confusion during development task handoffs
Cons
Occasional downtime may disrupt operations
Support documentation may not cover all scenarios
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Frequently Asked Questions
How long does it take to set up a Projekts AI workspace?
Most organizations can complete initial workspace setup in under one hour. The guided process covers workspace configuration, project creation, and connecting the first integration, although individual setup requirements may differ between organizations.
Which AI model providers does Projekts AI support?
Projekts AI supports models from DeepSeek, Claude, OpenAI, xAI, and Mistral. Teams can switch between these providers based on their requirements without being restricted to a single AI model provider.
Can multiple team members access the same AI-generated documents in Projekts AI?
Yes, Projekts AI stores workflow-generated documents in a shared project Documents Library accessible to members with appropriate permissions. However, AI sessions are created individually for each user rather than shared across accounts.
Who owns the project documents and AI conversations stored in Projekts AI?
Projekts AI treats requirements, user stories, documents, sprint notes, and AI conversations as customer-owned project artifacts. Its stated approach emphasizes respecting ownership and avoiding unauthorized exposure or repurposing of project information.
Which document formats can users preview in Projekts AI?
Projekts AI's Documents Library supports previews of Markdown files with formatting, HTML documents rendered as web content, and images. These preview capabilities allow project members to examine supported artifacts within the platform.
What is the difference between workflows and agents in Projekts AI?
Workflows follow predefined software development phases to generate specific outputs, such as product requirements documents or sprint plans. Agents support open-ended conversations within specialized domains without requiring predefined structures or deliverables.