Managed & in-region
Models run as a managed service in the AWS Regions you choose, so inference stays within your selected geography rather than crossing arbitrary boundaries.
CineCLI does not train or host its own foundation models. Instead, it routes each task to a suitable model from Amazon Bedrock — Anthropic Claude for language and reasoning, the Amazon Nova family for understanding, image and video generation, Amazon Titan for embeddings, and Stability AI for imagery. Every call runs under Amazon Bedrock Guardrails and our own governance controls.
CineCLI selects a model per task rather than relying on a single model for everything. The table below summarizes how each model is used today.
| Model | Provider | Used in CineCLI for | Notes |
|---|---|---|---|
| Claude (Opus, Sonnet, Haiku family) | Anthropic | Script writing, story and scene development, reasoning, and content classification that supports moderation. | Larger models for complex writing; smaller, faster models for classification and routing. |
| Amazon Nova Pro / Lite / Micro | Amazon | Text and multimodal understanding — analyzing scripts and reference media, structuring scenes, and assisting moderation. | Tiered for cost and latency: Micro for fast text tasks, Pro for richer multimodal understanding. |
| Amazon Nova Canvas | Amazon | Image generation for storyboards, key frames and scene visuals. | Image-generation model with built-in safety features such as watermarking. |
| Amazon Nova Reel | Amazon | Short video generation for scenes and motion shots. | Video-generation model; outputs pass output screening and receive provenance credentials. |
| Amazon Titan (Embeddings, Image) | Amazon | Text and multimodal embeddings for search, continuity and retrieval; image generation where applicable. | Embeddings power continuity look-ups and asset search across a project. |
| Stability AI models | Stability AI | Alternative image generation for storyboards and scene imagery. | Used where its style or controls suit a shot; subject to the same guardrails and provenance. |
Building on Amazon Bedrock lets CineCLI reach leading models through one managed interface, while keeping data handling, security and content controls consistent across providers.
Models run as a managed service in the AWS Regions you choose, so inference stays within your selected geography rather than crossing arbitrary boundaries.
Data is encrypted in transit and at rest. As described by AWS, content sent to Amazon Bedrock is not used to train the underlying base models.
Configurable content filters apply policies for harmful content and denied topics, so the same safety rules can wrap every model regardless of provider.
Bedrock's evaluation tooling helps us compare models on quality and safety for a given task before promoting one into the pipeline.
For production workloads we can reserve dedicated capacity, giving predictable latency and throughput during peak production runs.
A single managed API spanning Anthropic, Amazon, Stability AI and others lets us choose the best model per task without bespoke integrations.
No model is called directly. Each request is wrapped in Amazon Bedrock Guardrails and our own policy checks, and every generated asset is screened again before it can be used. Media that models produce carries provenance signals so it can be recognized as AI-generated.
We treat model selection as a governed decision, with records of which model and version produced each result.
Talk to us about model selection, in-region deployment and how CineCLI governs every generation, or request access to try it.