How Someli.ai scaled branded content delivery using embedded creative infrastructure

KEY HIGHLIGHTS

50 clients per designer

Efficient backend workflows made possible by automation

3-week integration

From a concept to a working editor in under a month

Fully embedded backend editing layer

No redirects, no external dependencies – everything stays in-platform

50 clients per designer

Efficient backend workflows made possible by automation

3-week integration

From a concept to a working editor in under a month

Fully embedded backend editing layer

No redirects, no external dependencies – everything stays in-platform

COMPANY

Someli.ai Someli.ai is a Dubai-based content automation platform serving financial advisors, recruiters, and accounting firms. Founded in 2021, the company operates with a 35-person team and a distributed delivery network across the UAE, India, the Philippines, Vietnam, and Kenya. The platform combines AI generation with human review to deliver fully branded social media content without requiring clients to design anything themselves.

Challenge

Someli spent 6 months building a static content library before realizing it couldn’t scale personalization. Clients needed editable, brand-locked templates generated dynamically — not fixed assets. At the same time, Someli did not want to expose a design interface to end users. Their model depended on automation-first delivery. They needed a programmable design layer that could operate inside their backend without slowing product velocity or increasing operational complexity.

Solution

Someli embedded Polotno as a backend creative infrastructure layer within three weeks. Instead of exposing an editor, they integrated it directly into their automation pipeline. AI selects layouts and content. Designers review and finalize. Clients receive fully branded posts without touching a design tool. The result is a scalable production system where a single designer can support 50+ clients, with full UX control and no external dependencies.

Challenge

Solution

THE CHALLENGE

Static content models don't scale

Someli initially built a static content library over six months. It quickly became clear that prebuilt assets lacked the flexibility required for personalized branding at scale.

Clients needed dynamic templates with brand constraints embedded into the system. At the same time, Someli did not want to expose a design interface to every user. The product vision was automation-first: AI-generated, brand-aligned, and pre-approved content delivered without user editing.

They didn't need a visible SaaS editor, but a programmable design layer that could run behind the scenes

THE SOLUTION

Embedding a backend design engine

The editor operates invisibly as part of the automation pipeline. AI selects layouts and content. Designers review and finalize. Clients receive scheduled, branded posts without interacting with any design interface.

Polotno became a controlled infrastructure component inside Someli’s system — not an external dependency, not a redirect, not a third-party workflow.

"Our CTO kept on requesting things from Anton (the founder). So he gave us his roadmap, he told us what’s coming, he told us what he can do for us now and what will come later".

Rajiv Shah

Co-founder & CEO @ Someli

THE OUTCOME

Someli integrated Polotno SDK directly into their backend infrastructure within three weeks

Today, designers can manage 50+ clients each because content generation and templating are automated at the infrastructure level.

Operationally, this resulted in:

– Lower production load per designer
– Faster onboarding with pre-configured brand templates
– No editor training required for clients
– Centralized control over UX and content standards

The editing layer does not sit in front of the user – it powers the system behind it.

Infrastructure continuity at scale

As Someli raised external capital, infrastructure risk became a board-level consideration. To eliminate dependency risk and ensure long-term resilience, Someli secured a source code license.

This enabled:

– Full business continuity safeguards
– Investor-grade infrastructure assurance
– Deep customization without platform dependency constraints

The decision was not about ownership for its own sake. It was about controlling a core production layer as the company scales globally.