TechCrunch
React and WordPress engineers embedded with the publishing team to rebuild front-end components, improve search, and optimize site performance.
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The people behind
the software.
We build custom software and AI systems for startups and established businesses. As an embedded engineering team or a delivery partner, we take responsibility from discovery through launch.
Built on ownership,
not tickets.
Imversion was founded in 2018 with a simple conviction: good software needs people who take responsibility for the whole problem, from the first conversation to the system running in production.
That approach connects our work across publishing platforms, digital products, and AI systems. We work alongside existing teams or bring together the engineering needed to take a product from idea to launch.
The technology changes with the challenge. The commitment stays the same: clear decisions, visible progress, and software your team can keep building on.
See that approach in practice- Building since
- 2018Software and AI engineering.
- Based in
- Bangalore, IndiaWorking with teams internationally.
- Ways to work together
- Embedded or end to endExtend your team or build with ours.
Our approach.
In production.
Different products. Different challenges. Explore what we built, how we worked, and the engineering behind each project.
State Affairs
A full-stack team supporting a news and government intelligence platform through feature development, integrations, and performance improvements.
Explore State Affairs
Ajentic
An AI agent platform built with backend infrastructure, admin dashboards, third-party integrations, and an embeddable chatbot experience.
Explore AjenticResponsibility,
made practical.
What ownership means in the day-to-day work, from the first technical decision to the final handover.
Own the problem
Start with the business goal. Agree the scope, surface constraints early, and keep delivery tied to the problem the product needs to solve.
Make the work visible
Share progress through working software, clear milestones, and documented technical decisions. Make trade-offs understandable before committing to them.
Use AI where it helps
Choose AI when it improves the workflow. Consider reliability, cost, and human oversight alongside the capabilities of the model.
Build for the next team
Treat maintainability as part of delivery. Document the system, test important workflows, and make handover part of the plan from the start.
Good work starts with good people.
If you care about thoughtful engineering and taking responsibility for what you build, we’d like to hear from you.