FAQ from SJinn
What is SJinn?
SJinn is not just another generative tool—it’s a context-aware AI creative agent trained to unify visual, temporal, auditory, and spatial intelligence. It interprets descriptive language holistically, preserving stylistic coherence, semantic continuity, and production fidelity across image, video, audio, and 3D outputs.
How to use SJinn?
Describe what you envision—no technical jargon required. SJinn parses nuance (emotion, pacing, texture, perspective), selects appropriate multimodal models, and generates synchronized outputs. You can iterate, combine modalities (e.g., generate a character image → animate it → add voice narration → export as 3D-ready mesh), and maintain asset lineage throughout.
How is SJinn priced?
SJinn uses a transparent, usage-based credit system with tiered subscriptions (Starter, Creator, Pro, Ultra, Enterprise). Each plan includes monthly credits, priority queue access, and API allowances. All plans include a 20% bonus credit launch offer—and unused credits roll over for 30 days.
Does SJinn support enterprise-level team plans?
Yes. The Enterprise plan includes dedicated infrastructure, SSO integration, custom model fine-tuning, role-based permissions, audit logs, SLA guarantees, and a white-glove onboarding experience—including co-developing domain-specific agents (e.g., “SJinn for Architecture” or “SJinn for EdTech”).
Are projects created in SJinn private?
Absolutely. All user inputs, generated assets, and project metadata are encrypted in transit and at rest. By default, nothing is shared, scraped, or used for model training—unless explicitly opted-in under strict compliance (GDPR/CCPA). Private cloud deployment is available for regulated industries.
Who should use SJinn?
Creative professionals who demand speed *and* control: indie filmmakers, social media strategists, product designers, educators, game developers, marketing agencies, and studios seeking to compress production timelines without sacrificing originality or quality.
How does SJinn work?
At its core, SJinn leverages a proprietary multimodal alignment architecture—trained on aligned image/video/audio/3D datasets—to map linguistic intent to cross-format representations. It doesn’t chain separate models; instead, it reasons jointly across modalities, ensuring consistent lighting, tone, motion timing, and spatial logic in every output.
What makes SJinn different from other AI tools?
Most AI tools excel in *one* modality—or stitch together siloed models. SJinn was architected as a unified agent: it understands that a “vintage jazz café” isn’t just a photo—it’s a mood (audio), a space (3D layout), movement (video pan), and texture (image grain). That holistic understanding enables true creative orchestration—not just generation.
What types of content can SJinn create?
Everything from photorealistic stills and lip-synced talking-head videos to immersive 3D scenes with physics-aware materials—and original music, ASMR triggers, voiceovers, ambient soundscapes, and even multilingual dubbing—all generated natively within a single workflow.
Do I need technical skills to use SJinn?
No coding, no CLI, no rendering queues. SJinn is designed for intuitive, browser-native creation—yet offers advanced controls (prompt weighting, motion curves, depth maps, audio spectrogram editing) for power users who want granular refinement.
Can I refine the results if they don't match my vision?
Yes—through iterative prompting, multimodal feedback loops (e.g., edit audio waveform → auto-adjust video mouth movement), and visual/audio/3D parameter sliders. SJinn remembers your preferences, learns from corrections, and surfaces contextual suggestions to accelerate iteration.
What credit system does SJinn use?
Credits reflect computational complexity: simple image generation = 1 credit; 10-second HD video with motion + voice = 12 credits; batch 3D model export with PBR textures = 25 credits. Real-time credit estimation appears before generation—and detailed usage reports are available per project.