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Seshira // AI-native SaaS

Building an AI-Native Project Management Platform That Thinks Like Your Best Engineering Manager

Morphlix designed and built Seshira, an AI-native project management platform on AWS that combines collaborative workspaces with autonomous AI agents capable of planning sprints, triaging issues, automating workflows, and helping engineering teams ship faster.

Timeline

3 months

Team

4 engineers

Industry

AI-native SaaS

Services

Product Strategy, Cloud Architecture

0 Days

From first commit to public launch

0 AI Tools

Shared agent and human capability registry

0% Reduction

Notification polling using Server-Sent Events

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The Challenge

Traditional project management platforms force teams to coordinate work manually across tasks, documentation, messaging, and reporting. While many products have added AI features, they remain workflow assistants rather than intelligent collaborators.

Seshira set out to solve a different problem: build an agent-first project management platform where AI actively participates in planning, execution, and project coordination while remaining transparent, auditable, and fully integrated into the same workflows used by human team members.

To achieve this, the platform needed to deliver:

  • Real-time collaboration for distributed engineering teams

  • AI-powered sprint planning and workflow automation

  • Secure multi-tenant SaaS architecture

  • Elastic cloud infrastructure capable of scaling with customer growth

  • Enterprise-grade security and operational visibility

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The Solution

Morphlix architected and implemented a cloud-native AWS platform that combines modern SaaS infrastructure with generative AI capabilities.

The solution includes:

  • AI-powered sprint planning using Amazon Bedrock

  • Event-driven workflow orchestration

  • Containerized backend services running on Amazon ECS

  • Global frontend delivery through AWS Amplify and CloudFront

  • Managed PostgreSQL databases with Amazon RDS

  • Redis-powered caching and real-time collaboration

  • Secure authentication using Amazon Cognito

  • Background processing using EventBridge, Lambda, and Amazon SQS

  • Infrastructure as Code using Terraform

  • CI/CD pipelines powered by GitHub Actions and AWS

The resulting platform enables AI agents and human users to operate from the same project data model, allowing automated task creation, intelligent prioritization, workflow recommendations, and collaborative project execution.

Technology Stack

Next.js • React • TypeScript • Go • Terraform • Docker • Redis • PostgreSQL • GitHub Actions • AWS

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