The Cinematic AI Engine
Programmable, Stateful, and Model-Agnostic
Orchestration for High-Fidelity Video Production
Solve the consistency problem. Ship cinematic AI videos.
The Consistency Problem
Traditional AI video generation creates beautiful individual shots, but fails at storytelling
Character Drift
Emma looks different in every shot. Her hair color changes. Her clothing morphs. The AI forgets who she is.
Environment Shimmer
The laboratory background shifts between frames. Walls move. Objects disappear. Spatial consistency is lost.
Result: Disjointed, unprofessional videos that break immersion
You can't tell a coherent story when your characters and environments change every 8 seconds
How MiniStudio Solves This
A three-layer architecture that treats video generation like code
Identity Grounding 2.0
Master Reference portraits are injected into every generation step. Your character Grandfather Elias maintains consistent white beard, wise blue eyes, and moss-green cardigan across all 60 shots.
The Invisible Weave (State Machine)
Remembers environment geometry and character state. The Victorian study with oak paneling and bookshelves maintains spatial consistency. Grandfather stays in his mahogany armchair, Young Maya on the rug.
Sequential Memory
Each generation is grounded by the final frames of the previous shot. When the Villain moves to the warehouse, the lighting, characters, and spatial continuity carry forward seamlessly.
Simple, Powerful API
Generate consistent multi-shot sequences with just a few lines of code
from ministudio import Ministudio, Character, Environment
# Define Grandfather - persistent across all shots
GRANDFATHER = Character(
name="Grandfather Elias",
identity={
"hair_style": "thick white messy hair and matching white beard",
"eye_color": "bright wise blue eyes",
"clothing": "moss-green wool cardigan over white shirt"
},
voice_id="en-US-Neural2-D",
voice_profile={"style": "warm and academic", "pitch": -2.0}
)
# Define the consistent study environment
STUDY = Environment(
location="Victorian study with oak paneling",
identity={
"architecture": "floor-to-ceiling bookshelves",
"base_color": "warm browns, brass, velvet greens"
}
)
# Generate teaching sequence - 60+ shots, perfect consistency
studio = Ministudio(provider)
results = await studio.generate_film({
"title": "Quantum Mechanics Masterclass",
"characters": [GRANDFATHER],
"environment": STUDY,
"scenes": [
{"action": "Grandfather explains Double-Slit Experiment"},
{"action": "Grandfather demonstrates with visual aids"},
{"action": "Grandfather concludes the lesson"}
]
})Built for Developers
Pythonic API, model-agnostic design, and production-ready infrastructure
Pythonic API
Clean, intuitive Python interface. Define characters once, use everywhere. No complex configuration.
Model Agnostic
Works with Vertex AI (Veo 3.1), OpenAI Sora, or custom providers. Switch models without changing code.
State Machine Driven
Stateful orchestration ensures consistency. The engine remembers context across generations.