One AI foundation.
Five apps in production.
A creative operations platform needed AI in its product and in the tools its customers already used. Six IgniteIQ engineers became its embedded AI team, building the foundation and continuing to ship new capabilities.
- Full-time embedded engineers
- 6
- Initial production rollout
- ~3 months
- Partnership at time of reporting
- 1.5 years
Reported at the time of this case study. Results describe this engagement.
Connect the client’s platform to AI.
We built the AI foundation and Model Context Protocol layer to reach into the client’s content, assets and workflows.
The client’s creative operations platform
Illustrated connections · Named integrations include those shown
production
6 full-time engineers.
A partnership spanning 1.5+ years with continued delivery on the original foundation.
Customers expected AI
inside their workflow.
The platform serves in-house marketing and creative teams across intake, workflow, review, digital asset management and brand governance. Content creation and review were outpacing its manual workflows.
The client needed a foundation for many AI capabilities and integrations with tools such as PowerPoint and Canva. It lacked the in-house AI and machine-learning engineering depth to build that foundation at the required pace.
A common base for
each new capability.
- A Model Context Protocol (MCP) layer connects AI capabilities to the client’s content, assets and workflows.
- Shared AI foundation code underpins the AI features shipped since the initial rollout.
- Production apps bring the client’s AI into Claude, Microsoft Office, a browser extension and Canva.
- A dedicated team continues to build new capabilities on the original foundation.
A first launch that kept expanding.
Build
AI foundation + MCP
Create the shared code and connections that subsequent capabilities use.
Launch · ~3 months
First production rollout
Put the foundation and first AI capability into customers’ hands.
Expand · 1.5 years
Five production apps
Continue shipping into the tools creative teams use, supported by six embedded engineers.
AI reaches customers
where they already work.
The client gained an ongoing AI development team and an in-production foundation for new features. Each new capability extends a common base, while the edge apps bring the client’s AI beyond its own interface.
Five apps were in production at the time of reporting. The named integrations illustrate where they run; they are not a complete app inventory.
Build AI into your product.
Bring your roadmap and existing stack. We can scope a first capability and the engineering team to deliver it.