AI accelerates a 3D pipeline when you know where to plug it.
Production teams want to integrate generative AI and autonomous agents. Most don't know where to start, and naïve attempts cost dearly. Midgarr combines 3D foundations with daily AI practice to support this transition without the buzzword.
AI without pipeline understanding destroys value
Off-brand asset generation, automatic texturing that breaks UVs, assisted level design producing unplayable scenes, autonomous agents regressing production code. AI answers isolated technical questions; it doesn't take accountability for a pipeline. Teams that integrate it blind pay for it several times.
AI injected — detail — 02 · Retopology
Clean topology generated from scan / raw CAD, validated manually. Edge cases stay human.
Who it's for
- Creative studios and agencies looking to industrialise production with AI without losing artistic coherence
- Production directors of large groups facing the "automate which tasks, keep which ones human" trade-off
- Software vendors integrating AI into their product who need an architecture that holds
- Dev teams using Claude Code or equivalent who want to move from individual use to multi-agent orchestration
Who it isn't for
- Silver-bullet seeking — AI doesn't replace domain understanding
- Marketing chatbot integration
- AI projects unrelated to a 3D or creative pipeline
- Proof-of-concepts with no intent to operate
How we intervene
Audit, integration, training. Three modalities, often combined.
- 01
Pipeline audit & AI opportunity mapping
2 to 4 weeks
Review of the current pipeline, identification of tasks where AI brings real gain (and those where it destroys value), option sizing. Written deliverable that prioritises interventions.
- 02
AI integration & tool development
4 to 12 weeks
Development of AI bricks in the pipeline: bounded asset generation, assisted texturing, automated QA, agent orchestration for repetitive work. Integration with existing tools. Deliverable: a pipeline measurably faster on target tasks.
- 03
Training & autonomy hand-off
by session
Training of internal teams on AI tools in production (Claude Code, agent orchestration, technical prompts). Progressive maintenance hand-off. Goal: the team leaves autonomous, not dependent.
Client references
30-minute diagnosis
Describe your pipeline. In thirty minutes we pinpoint the two or three places where AI would create real gain.