How It Works
Autoretto runs a verifiable 20-step loop for every release. Here's exactly what happens - from setup through publish and self-optimization - with no black boxes.
Start automating your channel →Write out your genre, BPM range, visual mood, artistic references, and content exclusions. Optionally paste a YouTube channel URL to clone its packaging style. Upload up to 3 reference images for thumbnail matching.
One-click OAuth on Google's standard consent screen. Each permission is explained before you grant it. No API keys, no developer console. Your credential is encrypted with AES-256-GCM on Autoretto's server.
Full autopilot publishes directly on your optimized schedule. Hold-for-review builds every complete release and waits for your approval before uploading. Change modes any time.
Every release - whether triggered automatically by your schedule or on demand from the studio - runs the same full pipeline:
Locks your stated channel goal as the imperative the whole loop optimizes toward.
Pulls live subscribers, views, and recent uploads from your connected channel so decisions sit on real numbers.
Reads how your most recent release performed to find what already worked.
Carries forward durable learnings from the optimizer memory so the loop never repeats last cycle's misses.
Scans packaging patterns currently trending in your niche.
Reads your cloned reference channel's title energy, voice, and thumbnail mood to copy its vibe while staying original.
Synthesises telemetry, analytics, and trends into the single highest-leverage move for this release.
Locks tone, exclusions, BPM, references, and art direction toward your goal and the opportunity brief.
Writes an optimized title, description, and tags benchmarked against proven performers in your niche.
Generates and masters a full instrumental from a style-locked prompt.
Probes real duration, sample rate, bitrate, and frame count - broadcast-ready or the loop stops here.
Renders a cinematic 16:9 hero frame, style-matched to your reference images and channel look.
Scores luminance and edge energy. Flat AI-slop frames are rejected before they reach the render stage.
Composes a broadcast MP4 with genre-fit beat-sync and pulsing edges. Studio can toggle Sora 2 Pro to animate the hero frame into a seamless, beat-locked looping video.
A strict MP4 gate - nothing downstream runs without a real, verified video artifact.
Automated quality checks plus a built-in policy reviewer covering hate, violence, sexual content, dangerous acts, misinformation, and copyright risk. Anything that fails is held.
Picks the optimal publish slot from your audience's learned best days and hours.
Ships on full autopilot when eligible, or holds for your approval. A publish is only claimed after a real, verified YouTube upload.
Watches how the new release tracks toward your channel goal from real analytics data.
Folds CTR, retention, and watch-time into the next brief and writes a traceable mutation log. The loop compounds: every cycle makes the next one smarter.
Autoretto is a closed-loop decision system, not a one-shot generator. Several models read your channel's REAL performance and steer the next release - and they get measurably sharper with every upload. A live, read-only ML dashboard tab shows the virality predictor and the content-lane bandit learning in real time.
A discounted, contextual, hierarchical Thompson-sampling bandit - real Bayesian reinforcement learning - picks each autopilot release's content lane (tempo band and energy tier). Every lane carries a Beta posterior over its breakout odds; the model samples each posterior and plays the strongest, so it provably concentrates on your channel's winning lanes over time while still probing under-measured ones. Partial pooling lets each lane borrow strength from others that share its tempo or energy factor, so it generalizes ("high energy wins", "drive tempo wins"), learns from far fewer uploads, and reports the best tempo and energy it has found; it folds the full 0-1 percentile of every outcome (continuous reward), and decays old evidence so it keeps adapting as your audience and the algorithm shift instead of converging once and going stale. It maximizes your odds of a breakout - no system can guarantee a viral hit.
Before publish, a per-channel predictor turns the run's pre-publish signals (the dynamic Autoretto score, viral-intuition readiness, opportunity confidence, quality-gate pass ratio, and live-market copy-confidence) into a predicted 24-hour view percentile, then folds the real outcome back with a gradient weight update - so it learns which signals actually predict virality on YOUR channel. A privacy-safe cross-channel prior makes a brand-new channel predictive on day one.
A z-score model clusters your uploads into winners and underperformers and distils what each shares, while a multi-armed-bandit title optimiser learns which title FORMAT wins on your channel from real 24-hour view outcomes.
An in-dashboard assistant grounded in your channel's live state and the same models that drive the loop. Ask why a release was held, what to change next, or to compose and run a release in plain language - it reads your real metrics, optimizer memory, and the bandit's learned lanes, and on Studio can execute approved branding, title, description, and thumbnail actions straight from the sidebar.