A company with over ten years behind it. We're helping them work with AI workflows across the whole team: more speed, more quality and an infrastructure ready for ISO 27001.
- modfie.com
9:41●●●●🔒www.modfie.com
Modfie is the casting and production management platform for film, production and advertising companies.
The challenge
A mature product and a team that knows it inside out, held back by four things:
- A stack with ten-plus years of evolution and all the complexity that comes with it.
- A team working with a pre-AI workflow.
- Little culture of development and delivery metrics.
- Outdated infrastructure with many single points of failure.
What we did
- 01
Technical due diligence and roadmap
We audited the real state of platform, infrastructure, processes and team, and set a roadmap of improvements to bring the company to a more mature level of security and scalability.
- 02
New infrastructure from scratch
Redesigned on AWS best practices: separate accounts per environment, private networking, high availability and all of it as code. No single points of failure, and ready for ISO 27001 certification.
- 03
The team on an agentic system with Claude Code
We applied gocimit's own operating workflow at Modfie: from planning to deployment, everything goes through an AI agent. We did it forward deployed: a senior engineer embedded in the team, aligning product, technology and management, and staying until the new workflow and the infrastructure were in production.
Planning is part of development
Tasks are created and specified from the agent, atomic and with context, and land on the team's board ready to work on.
Other areas open projects
Product, operations or the casting team can create projects that reach development without a technical translator in between.
The team no longer codes by hand
All code is written through agents on Claude Code. Unit tests, documentation, commits and code review are part of the automated flow, not extra work.
Agents inside the product
We also built agents into Modfie's own stack, making the casting features far more efficient.
The change is cultural: everything becomes agentic, and the team gets further with the same people.
Workflow
- 01Create issue
- 02Triage
- 03Branch per issue
- 04Agent-driven development
- 05Commit
- 06Pull request
- 07AI review
- 08Comments resolved
- 09Automated tests
- 10Merge & tag
- 11Build & deploy
How we work: what a forward deployed engineer (FDE) is and why it matters →
Speed, practicality and peace of mind. Speed because we fly through development. Practicality because I, as CPO, hand over the polished concept knowing the result will be what I expect, without hours of meetings and of doing and undoing. Peace of mind from the security of a process built on ISO standards.
Milestones we worked on
Transition to AI workflows
The team moves to working with agents: planning, code, tests, documentation and review.
Infrastructure as code
All the infrastructure in Terraform on AWS, deployed by the pipeline, no manual changes.
Compliance
Infrastructure and processes ready for ISO 27001 certification.
AI across the rest of the organisation
Product, operations and casting open projects and work with agents, not just the tech team.
This case shows how we bring a company with a mature product to work with AI without stopping the business: first understand the real state, then a solid base, and on top a team that works with agents.
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