From brief to on-brand visuals with Amazon Nova on Bedrock - Part 1

Accelerating your marketing ideation with generative AI - Part 1: From idea to generation with the Amazon Nova foundation models

Marketing moves fast. Budgets don't. Teams are expected to ship on-brand, scroll-stopping visuals across channels-without dragging through long feedback loops or agency delays. Generative AI changes the pace of ideation and production, but it still rewards teams who set up the right workflow.

Here's a clear path: use Amazon Nova to go from a campaign idea to production-ready visual assets in minutes, not weeks.

Why speed is the new advantage

Campaigns miss their moment when timelines stretch. News cycles shift, trends fade, and a slower competitor wins attention. Meanwhile, budgets are getting tighter. In 2024, marketing spend as a share of company revenue fell from 9.9% to 7.7%-forcing teams to do more with less.

Source: Gartner CMO Spend Survey

Meet Amazon Nova (available through Amazon Bedrock)

Amazon Nova is a family of foundation models you can call through APIs. For marketers, here's the simple breakdown:

• Understanding models (Nova Micro, Lite, Pro, Premier): take text, image, or video as input and generate text-great for prompt creation, concept refinement, and instructions.
• Creative models:
  • Nova Canvas: text-and-image to image (up to 2K x 2K), plus image editing.
  • Nova Reel: text-and-image to video.
• Speech-to-speech:
  • Nova Sonic: real-time, humanlike voice conversations with text output.

From campaign idea to on-brand visuals: a 4-step flow

• Describe your campaign: goal, audience, vibe, and platform formats.
• Retrieve reference images: pull proven visuals from past campaigns via an image database.
• Generate a refined prompt: use Nova Pro to transform your brief + references into a strong text-to-image prompt (English works best).
• Create the visuals: send the prompt to Nova Canvas to generate up to five options-fast.

Reference image recommendation

This step uses multimodal embeddings and a vector database to find similar, high-performing images from your history. You select the best matches to guide the new assets. This preserves brand consistency and speeds alignment across teams. We'll go deeper on this technique in Part 2 of the series.

Let an LLM write better image prompts for you

Even experienced teams waste time tweaking prompts for creative models. The fix: metaprompting. In short, you ask Nova Pro to write a concise, high-signal prompt for Nova Canvas based on your campaign description and chosen references. Keep prompts in English for best results.

Example (for a Colombian small-coffee-producers credit campaign):

Prompt: Vibrant scene of small coffee growers on Colombia's green mountain slopes at sunrise; farmers in traditional clothing handpicking ripe red coffee cherries among glossy leaves; warm, welcoming mood; rustic wooden baskets, burlap sacks, dirt paths; sweeping Andean ridgelines and low morning mist; cinematic lighting, rich textures, brand-safe.

What this looks like in production

Under the hood, the stack is straightforward:

• Amazon Bedrock to call Nova Pro (prompt generation) and Nova Canvas (image generation).
• AWS Lambda to run metaprompting, image generation, retrieval, and campaign writes.
• Amazon DynamoDB for campaign metadata and asset references.
• Amazon API Gateway for APIs and Amazon Cognito for user auth.

How Bancolombia is speeding up creative alignment

Bancolombia has been testing this workflow to shorten the gap between the brief and stakeholder alignment. They start with clear goals, audience, and message. Then they add visual references-some pulled from previous campaigns-and quickly generate high-quality concepts for early feedback.

The impact: fewer meetings, faster validation, and a stronger base for the creative team. As generative models improve, they expect more of the design work-resizing, formatting, and platform-ready output-to be handled automatically, so the team can move faster on publishing and iteration.

Implementation best practices

• Architecture
  • Keep it modular: separate retrieval and generation services.
  • Go serverless first with Lambda and API Gateway for scale without overhead.
  • Track model versions for reproducibility.
• Security
  • Apply least-privilege IAM roles for all components.
  • Encrypt in transit and at rest (use KMS).
  • Validate inputs in briefs and prompt editors.
  • Protect APIs with Cognito.
• Performance
  • Cache popular queries and reference images (ElastiCache).
  • Use asynchronous processing for longer image jobs.
  • Enable auto scaling for bursty demand.
• Monitoring and QA
  • Centralize logs in CloudWatch and alert on key metrics.
  • Plan for graceful degradation if a model is temporarily unavailable.
  • Run periodic content audits for brand and compliance.

What this unlocks next

• Direct integration with your marketing automation stack.
• Personalized visuals using customer insights.
• Multi-channel asset generation from a single prompt.
• Automated A/B testing for creative variations.

Quick start for marketing teams

• Define two pilot use cases: one net-new campaign, one seasonal refresh.
• Collect 30-100 high-performing past visuals for reference retrieval.
• Adopt a simple metaprompt template for Nova Pro and standardize prompt fields (subject, scene, lighting, mood, details).
• Set guardrails: brand colors, disallowed elements, platform formats.
• Measure time-to-first-concept, approval cycles, and lift in engagement.

Level up your team

If you want a structured way to build these skills, explore this practical pathway for marketers: AI Certification for Marketing Specialists. For deeper prompt tactics, see our prompt-focused resources: Prompt Engineering.

Conclusion

This workflow helps you move from a simple campaign idea to strong, on-brand visuals in minutes. Use Nova Pro to write better prompts. Use Nova Canvas to produce consistent image sets. Tie it together with retrieval, a clean API layer, and clear guardrails. Speed wins-and now, you can build for it.