Scaling creative production with AI, templates and automation

Executive summary

Modern marketing demands speed, scale and strategic thinking. Yet many teams remain bogged down by inefficient, manual workflows, especially when managing high-volume, always-on campaigns across regions and verticals. This whitepaper outlines how UNCANNY partnered with a leading Southeast Asian fintech company to architect a creative automation system that dramatically improved output, quality and performance.

Over six months, we scaled production from hundreds to thousands of assets per month, reduced turnaround time by over 60%, and tripled campaign CTR without growing the internal team. This is a blueprint for marketing teams that want to scale without burnout.

The challenge: always-on, always behind

Our client operates a multi-market financial platform offering credit cards, insurance, loans and investment products. With performance marketing running 24/7, they faced mounting pressure to:

• Refresh and localise creatives constantly
• Deliver thousands of assets per month across platforms
• Maintain consistency while balancing market nuances
• Reduce turnaround times without sacrificing quality

What should have been a data-driven, digital-first process had become slow, manual and increasingly unsustainable.

The solution: automation built for creative operations

UNCANNY’s role was to rethink, not just speed up, the production workflow. We built a custom automation framework using Jira, n8n and bespoke code, tailored precisely to the team’s operational realities.

1. Automated brief intake and routing

We developed a dynamic briefing system that collects structured information and routes it directly into Jira via n8n automations. This included:

• Logic-based flows for different campaign types
• Automated tagging by market, vertical and asset type
• Built-in asset upload and reference collection
• Instant queue assignment to the correct creative or producer

This eliminated briefing inconsistencies and significantly reduced time lost to clarification and rework.

2. Template-driven design system

To meet scale demands, we created modular Figma templates for each product vertical:

• Tokenised layers allowed instant localisation (e.g. rates, promos, disclaimers)
• Templates covered banners, social, CRM and landing page assets
• Version-controlled components enabled consistency across all markets

This allowed the team to launch multi-market campaigns with speed and precision.

3. AI and automation for copy and quality control

We introduced automation at critical points in the workflow:

• Custom GPT agents generated and localised copy variations on demand
• Translation tools adjusted tone and language by region
• Computer vision and metadata scripts performed QC on resolution, layout and file formats

This enabled high-volume execution while reducing errors and human fatigue.

4. Performance feedback and creative testing

Beyond production, we embedded analytics and experimentation into the system:

• Every month, the team hypothesised what creative elements might improve CTR (e.g. headline framing, CTA contrast, design hierarchy)
• These ideas were tested in controlled batches across selected campaigns
• Top-performing elements were incorporated into templates and automation logic

As a result, CTR improved from 1% to 3% on average, demonstrating that automation doesn’t just drive efficiency, but performance uplift too.

Results

Metric	Before	After
Avg. asset turnaround	5–7 days	1–2 days
Assets shipped / month	~150	3,200+
Manual QC hours / week	12+	<4
Creative error rate	~11%	<3%
Internal hours saved	–	100+ hrs / month
Avg. CTR	~1%	3%
Performance testing	Ad hoc	Structured, monthly cycles

Strategic takeaways

1. Workflows come before AI.
2. Templates unlock creativity, not limit it. By handling routine executions through templates, creative energy can be focused on high-impact ideas.
3. The best automations are invisible. We built the system around tools the team already used, Jira and Slack, minimising friction and maximising adoption.
4. Performance should shape production. Data isn’t just for reporting. It should feed back into design systems, creative decisions and campaign logic.
5. Automate the doing, optimise the thinking. By freeing the team from repetitive tasks, we unlocked space for experimentation, insights and strategic lift.

Conclusion

Automation in creative production isn’t about cutting corners. It’s about building systems that let teams do more of what matters. With the right foundation, you can increase output, improve performance and reduce waste without burning out your team or compromising brand quality.

If your organisation is struggling to keep pace with the demands of digital marketing, automation may not be your risk. It might be your most strategic advantage.