AI Image Production Services (Managed, On‑Brand, and Ready to Publish)

AI Image Production is the operational process of creating and delivering commercial images using generative AI and AI-assisted editing, but with real-world constraints in mind: brand consistency, channel requirements, realism, deliverable packaging, and review workflows. The goal is not to generate “interesting images”. The goal is to produce publishable assets that look intentional and support conversion.

Many teams try DIY tools first. They get quick outputs, but then hit predictable friction: style drift across a batch, warped logos, unreadable packaging text, artifacts around edges, unrealistic materials, and exports that don’t match Shopify/Amazon/ads specs. At that point, “fast” becomes slow, because the real time cost is iteration, correction, and operational cleanup.

Bastelia treats AI image production as a managed service. We use AI for acceleration, but we control the workflow so your team gets: usable visuals, clearly organized deliveries, and a review system that prevents brand damage. Everything is done online, which removes the classic production bottlenecks (studio time, travel, reshoots) and helps keep pricing accessible.

Tools optimize for speed of generation. Traditional studios optimize for craftsmanship per shot. Bastelia is built for the reality most teams live in: scale, deadlines, and multiple channels. We combine AI-driven production efficiency with human review and operational delivery.

Because we work online and embed AI in every stage (generation, selection, editing, packaging, and consistency checks), we reduce overhead and move faster. That’s why we can often deliver at a much lower cost than traditional production — while keeping a professional standard of review and delivery.

We produce commercial visuals that support eCommerce conversion and marketing performance. The most common deliverables fall into four categories. Each category can be produced as a consistent batch, versioned for different channels, and delivered with organized exports (and metadata if you need it).

If you already have photography, we can also do AI-assisted editing at scale (background replacement, cleanup, compositing, smart crops, upscaling). The point is always the same: outputs should be usable, consistent, and channel-ready.

The fastest projects are the ones with a clear definition of “usable”. Our process is designed to produce a result your team can approve and publish — not a folder of experiments. Because everything is online, collaboration is simple: you send assets, we send structured previews, you approve, we deliver final exports.

• 1 What are we producing, for which channels, and what does “good” look like?

  We align on image types (product, lifestyle, virtual model, ads), your channel specs, and the non-negotiables (brand rules, claims, sensitive elements). This is also where we define your review checkpoints so approvals don’t stall production.

• 2 Build your style system (so images stay consistent at scale)

  We create a repeatable “visual recipe”: references, framing rules, lighting direction, negative constraints, and consistency guardrails. This is the difference between a one-off image and a reliable batch.

• 3 Production sprint (generate, edit, and normalize)

  We produce and refine images using the most controlled approach for your case (generation, transformation from existing assets, compositing, or editing). The goal is to protect product fidelity and brand feel while keeping speed high.

• 4 Human QA (commercial-grade checks)

  We review what AI typically breaks: warped logos, unreadable packaging text, incorrect materials, hands and edges, reflections, and subtle artifacts. If something looks “almost right”, it’s not shipped.

• 5 Delivery packaging (so your team doesn’t waste time)

  You receive organized folders by SKU/campaign/channel, consistent naming, versions, export sizes, and optional metadata for DAM/PIM workflows. This is where managed production saves real operational time.

The key advantage of an online-first workflow is that decisions happen faster and the output is cleaner: less overhead, fewer moving parts, and the ability to produce multiple versions without re-shoot logistics.

Consistency is rarely a model problem. It’s a workflow problem. The reason most AI batches look inconsistent is because they’re produced as disconnected prompts rather than a controlled system. We build that system so that a batch looks like it belongs to the same brand, the same campaign, and the same catalog.

In practice, “on brand” means controlling the variables that influence perception: framing, negative space, shadows, lighting temperature, palette, background textures, realism level, and the amount of visual noise. It also means controlling what must not happen: logo distortion, incorrect claims, unrealistic surfaces, or stylistic drift.

A production service is only valuable if the output integrates into your workflow. That’s why delivery is not an afterthought. We can deliver a single “master” set, but most teams prefer channel-ready exports that reduce internal work.

For teams using DAM/PIM tools (or simply trying to keep order), we can also deliver optional IPTC/XMP metadata such as SKU, collection, campaign, usage notes, and internal rights notes. This becomes valuable as soon as you’re managing hundreds of assets.

If you publish images commercially, rights and IP are not a theoretical topic — they are operational risk. The safe approach is not “ignore it” and not “panic”. The safe approach is to build a workflow that avoids obvious pitfalls and documents decisions.

Our rights-first principles are straightforward: we work from client-owned inputs where possible, we avoid generating content that relies on third-party IP you don’t own, and we avoid risky references (for example, recognizable celebrity likeness or copyrighted characters). If your internal policy requires documentation, we can align delivery packaging and metadata to support it.

• Use controlled inputs: client-supplied packshots, brand elements, and licensed references.
• Avoid lookalikes: no celebrity mimicry, no brand impersonation, no copyrighted characters.
• Design review checkpoints: approvals should happen before scaling a full batch.
• Traceability when needed: versioning and notes help internal governance.

Pricing for AI Image Production is driven by the same reality as traditional production: complexity and volume. The difference is that online-first execution and AI acceleration remove large cost drivers (sets, travel, reshoots, and slow manual iteration). That’s why managed AI production can be dramatically cheaper — especially when you need batches, not one-offs.

The main pricing drivers are:

• Volume: number of SKUs and total images (including variants and crops).
• Complexity: reflective products, liquids, jewelry, hands, text-heavy packaging, strict realism.
• Consistency requirements: how tight the style must remain across a batch.
• Channels: number of export sets and placement-specific requirements.
• Governance: metadata, versioning, and documentation needs.

The simplest way to start is a pilot: a small batch that proves quality and defines the style rules. Once the pilot is approved, scaling is faster and more predictable because you are not reinventing the process for every SKU.

Below are two small tools that make AI Image Production decisions easier: a brief generator (to define scope clearly) and an export helper (to communicate channel deliverables). They are intentionally simple: the goal is to reduce ambiguity and speed up quoting and approvals.