endorsedOngoing

Microservices Migration & AI Product Development for Fabriq

Services Covered:

Custom Software Development • AI and Machine Learning

Industry

Information Technology

Duration

13 months

Budget

Confidential

Start Date

1 July 2025

Team Size

1-5 Employees

Engagement Model

Nearshore

Project Capability Score (PCS)

83/100

Strong

Project Capability Score (PCS) estimates how capable Django Stars is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Fabriq

Stavanger, Norway

Project Summary

Django Stars provided software development services to Fabriq, an AI-products company, migrating a monolithic Django app to microservices, building frontend UI/UX, and implementing CI/CD. The engagement covered multiple AI-enabled projects — including a clinical decision support system deployed to 28 US hospitals, a personalised fan engagement solution for Major League Baseball, and a research assistant for a geoscience publisher — all leveraging Fabriq's orchestration framework. Django Stars integrated with the client's teams and consistently met deliverables on time and on budget while communicating via Jira, Slack, and Teams.

Key Challenges

Move from a monolithic Django application to microservices
Implement DevOps and CI/CD to increase deployment speed
Build a distributed, event-driven architecture for an agentic AI platform
Design and deliver frontend UI and UX
Provide client-facing engineers as forward-deployed team members

Project Deliverables

Data transformation
Agentic harnesses
Traces and logging
Event-driven architecture
UI and UX
CI/CD pipelines
Integration with customer delivery teams

Project Solution

Django Stars was engaged to migrate a monolithic Django application to microservices, implement DevOps practices including CI/CD, and build frontend UI/UX while providing client-facing engineering support. The vendor assigned a small cross-functional team (2–5 employees) to deliver three AI-enabled projects — a clinical decision support system, a personalised fan engagement solution, and a research assistant — all leveraging Fabriq's orchestration and execution framework. Deliverables included data transformation, agentic harnesses, tracing and logging, an event-driven architecture, UI/UX work, CI/CD pipelines, and integrated collaboration with the client's delivery teams.

Project Outcome

Deliverables met on time and on budget
Django Stars integrated effectively with the client's team and participated in client-facing work
Communication was strong via Jira, Slack, and Microsoft Teams
The offering scaled from a small initial engagement to a growing collaboration over time

Platforms

AI/ML Platform
Web

Tech Stack

Django
Python

Client Endorsement

Overall Review Rating

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Django Stars has met all the deliverables on time and within the budget. The team has integrated well with the client's team and has joined them in client-facing work. They have also demonstrated exceptional communication skills through Jira, Slack, and Microsoft Teams.”
Jesse Lord
Co-Founder
Date: 04/17/2026