Flexible product data
Task cards with custom fields, checklists, attachments and comments, without a schema change for every new field.
MongoDB development
MongoDB for flexible product data.
We use MongoDB where records vary a lot in shape. It holds the boards, task cards, custom fields and time logs of a Scrum and Kanban workspace built on Node.js and React, and data for AI automation services written in Python.
What we build with MongoDB
Where MongoDB earns its place.
The kinds of work we use MongoDB for, based on the projects below rather than a list of everything the technology can do.
Paired with search and cache
MongoDB for core data, Elasticsearch for search and Redis for hot reads in one product.
AI and analytics data
Storing events and model outputs from AI services next to relational data where it makes sense.
2 client projects
How MongoDB fit into each project.
Which part of the system it ran, and what it worked with. Every row links to the full case study.
AI wired into CRM, ERP and support to cut manual work across operations
DatabaseMongoDB
Together withFastAPI, Flask, PostgreSQL, TensorFlow, PyTorch, Scikit-learn
One workspace for Scrum, Kanban and time tracking, built for daily use
DatabaseMongoDB
Together withNode.js, React, Redux, Redis, Elasticsearch
MongoDB case studies
Results from these projects.
Each one with the client’s problem, our approach and what changed.
AI2025–2026
Cross-industry
AI wired into CRM, ERP and support to cut manual work across operations
AI services connected to existing CRM, ERP and marketing tools: 24/7 chatbots, sentiment analysis, fraud alerts and predictive insights.
2xbusiness efficiency
80%data processing accuracy
Web platforms2026
Project management
One workspace for Scrum, Kanban and time tracking, built for daily use
A task and project workspace with Scrum and Kanban boards, detailed task cards, time tracking and live updates for teams of any size.
85%project visibility
70%team adoption
Related services
MongoDB is a tool. These are the jobs it does.
We do not sell hours of a technology. We take on a result, and choose the stack with you. These are the services where MongoDB usually comes in.
Technologies
Other technologies we have shipped with.
Each one backed by at least one published client project.
Backend
MongoDB FAQ
MongoDB questions we hear.
Anything missing? Send us your question and an engineer will answer, usually within one business day.
Contact usWhen is MongoDB a good choice?+
When records vary in shape and you rarely need joins across many tables, as in task cards with custom fields. For accounting and orders we prefer a relational database.
Can MongoDB handle search?+
For simple filters, yes. For full-text search across large volumes we add Elasticsearch, as on the task manager project.
Do you use MongoDB with .NET?+
We can, but our MongoDB projects so far use Node.js and Python back ends.
Start a project
Tell us what you are building with MongoDB. We come back with a plan and a price.
A spec, a Figma file or three paragraphs is enough to start.
- First reply · from an engineer, not a sales rep
- 30-min call · with Roman, our CTO, to clarify scope
- After the call · a written proposal with plan, team and price
Roman Oleksuk, CTOPrefer to talk? Pick a slot in Roman's calendar