Planivia

Planivia is an AI-powered, multi-tenant project management platform that the author describes as converting unstructured information into actionable work. The product is presented as a SaaS solution built with React, Node.js, and GPT-5.6, designed to streamline planning from documents and meeting notes to execution in tools like Jira.

The description states that Planivia supports uploading project briefs or meeting notes, generating structured plans and tasks, and integrating with existing workflows through AI-assisted review before task entry into the system.

Key claims include:

• The platform works with English, Spanish, or French
• It integrates with Jira
• It uses GPT-5.6 for planning and document analysis
• It supports multi-tenant isolation and role-based access control

The author reports that Planivia is a working production application covering the full journey from signup to reporting, but no revenue, customer data, or traction metrics are provided.

The description states that Planivia is:

• An AI-powered, multi-tenant project management platform
• Designed to turn unstructured information into actionable work
• Built with React, Node.js, Express, SQLite, and GPT-5.6
• Capable of generating phases, milestones, tasks, dependencies, risks, and roadmaps from project briefs
• Able to process meeting notes and generate structured minutes, decisions, risks, blockers, action items, and proposed tasks
• Integrated with Jira for task synchronization
• Supporting dashboards, task lists, Kanban boards, timelines, risk management, and reporting
• Available in English, Spanish, or French

The author describes it as a working production application covering the full journey from organization signup to planning, execution, meetings, risks, AI assistance, and executive reporting.

The description states that Planivia was built to address:

• Time lost translating documents, meeting notes, emails into executable plans
• Fragmented information leading to missed tasks and late-discovered risks
• Outdated reports due to lack of integration between understanding and execution

Positioning claims include:

• Connecting project understanding with project execution
• Being an AI-powered platform that turns unstructured information into actionable work
• Supporting both project briefs and meeting notes as input sources
• Providing AI Copilot for next action recommendations
• Offering structured output through validation, review steps, and duplicate prevention

The author emphasizes that Planivia is not just an AI demonstration but a working application covering the full project lifecycle.

The description states that Planivia targets:

• Project teams who lose time translating documents and meeting notes into executable plans
• Organizations needing to manage execution through dashboards, task lists, Kanban boards, timelines, risk management, and reporting
• Users requiring multi-tenant isolation with roles, permissions, and organization-level subscriptions

The author mentions that the platform supports multiple organizations with tenant isolation, roles, permissions, invitations, and organization-level subscriptions.

Not evidenced. The description does not contain any information about pricing models, subscription tiers, or monetization strategies.

The description states that Planivia was built using:

• Frontend: React and Vite
• Backend: Node.js and Express
• Database: SQLite
• AI: GPT-5.6 for planning, document analysis, project assistance, risk analysis, meeting intelligence, and reporting
• Integration: Jira for task synchronization

The author reports that Codex was used as an engineering collaborator throughout the development process, helping with repository-wide audits, implementation, debugging, test creation, internationalization, multi-tenant authorization, prompt refinement, production hardening, and deployment verification.

The description states:

• Planivia is a working production application covering the full journey from organization signup to planning, execution, meetings, risks, AI assistance, and executive reporting
• The meeting-to-execution workflow is especially valuable: teams can record what happened in a meeting and turn it into reviewed, traceable project tasks within minutes
• The next stage is a real customer pilot
• Adoption, time saved, completion rates, accepted AI recommendations, and workflow friction will be measured during the pilot

No revenue, customer data, or traction metrics beyond the hackathon submission are provided.

Not evidenced. The description does not mention any competitors or competitive positioning.

The description states:

• One major challenge was making AI output reliable enough to become real project data
• Another challenge was maintaining strict multi-tenant isolation while allowing one user to belong to multiple organizations with different roles
• Internationalization was particularly demanding, requiring architectural corrections to maintain language consistency

Key risks include:

• Reliability of AI-generated content for actual project execution
• Maintaining multi-tenant isolation and role-based access control
• Language consistency in AI outputs across different interface languages
• Lack of evidence for real-world usage or customer validation beyond the hackathon submission

1. What specific problems are you solving that existing project management tools don't address?
2. How do you plan to validate the reliability and accuracy of AI-generated tasks before they enter execution workflows?
3. What is your timeline for the customer pilot, and what metrics will you use to measure success?
4. How do you intend to scale beyond a single developer's capacity?
5. What are your plans for monetization and pricing strategy?
6. How do you plan to handle data privacy and security concerns in multi-tenant environments?
7. What specific feedback have you received from potential users during the hackathon phase?