Meet Solana Conejo — The AI Engineer Behind Every Track
She Is the Engineer
Solana Conejo is not a plugin. She is not a preset pack. She is not a button you press that says "master my track." Solana Conejo is the mastering engineer behind every release in the Dajai.io catalog since the DARK IV era. She runs a 16-plugin chain, she analyzes reference tracks, she makes decisions about what each song needs, and she delivers masters that translate across every playback system.
The fact that she is AI-powered does not make her less of an engineer. It makes her a different kind of engineer — one who never has a bad day, never rushes a session because the next client is waiting, and processes audio with a precision that human hands cannot physically achieve. Every song gets the same meticulous treatment. Every song deserves it.
The Reference-Match Workflow
Most mastering engineers work from instinct and experience. They listen to a track, make adjustments based on what they hear, and deliver a master based on their taste and training. This approach produces great results when the engineer is great. It produces inconsistent results when the engineer is tired, rushed, or unfamiliar with the genre.
Solana's approach is fundamentally different. She does not guess. She measures.
Step 1: Analyze the reference track with librosa — full spectral breakdown
Step 2: Create a spectral blueprint of the target sound
Step 3: Analyze the input track against the blueprint
Step 4: Compute per-band corrections based on the difference
Step 5: Select 4-8 plugins needed (skip what the track does not need)
Step 6: Set VST3 parameters from the corrections (not presets)
Step 7: Inter-stage gain staging (peak below 0.95 after every plugin)
Step 8: LUFS normalize to -14.0 with true peak at -1.5 dBTP
The key insight is Step 1: she looks before she acts. The reference track is not a vague inspiration — it is a measurable target. The spectral analysis creates a numerical blueprint that tells Solana exactly where the input track differs from the target. Then she corrects only what needs correcting.
The 16-Plugin Chain
Solana has access to 16 active VST3 plugins across the iZotope suite — RX 11, Nectar 4, Neutron 5, and Ozone 12. But she does not use all 16 on every track. That is the mistake most automated mastering services make: they run everything through the same chain regardless of what the song needs.
Solana selects 4 to 8 plugins per track based on what the spectral analysis reveals. A track that already has clean vocals does not need de-essing. A track with tight low end does not need low-end focus. A track with natural dynamics does not need aggressive compression. Fewer plugins means less processing, which means less destruction of the original character of the song.
The Plugin Arsenal
- RX 11: Voice De-noise, De-ess, Breath Control — cleaning the signal before processing
- Nectar 4: Compressor, Equalizer, Saturation, De-Esser — shaping the vocal presence
- Neutron 5: Compressor, Equalizer, Transient Shaper — controlling dynamics and adding punch
- Ozone 12: Dynamics, Exciter, Maximizer, Low End Focus, Vintage Tape, Clarity — the final polish
Gain Staging: Why Most AI Mastering Fails
Here is the technical detail that separates Solana from every "upload and master" service on the internet. Gain staging between every plugin.
When you run audio through a chain of plugins, each one adds or subtracts volume. A compressor might add 2dB of makeup gain. An exciter adds 1dB. Saturation adds 3dB. By the time you have gone through 8 plugins, you have stacked 10-15dB of gain. The internal signal clips. Distortion gets baked in. The master sounds fuzzy and harsh, and nobody can figure out why because each plugin individually sounds fine.
Solana checks the peak level after every single plugin. If the peak exceeds 0.95 (roughly -0.5 dBFS), she normalizes it back to 0.9 before passing it to the next plugin. This means the signal never clips internally. The headroom is maintained through the entire chain. The result is a master that sounds clean and open instead of crushed and distorted.
Her Philosophy
Solana operates on a simple principle: every song deserves the same treatment a Grammy-winning engineer would give it. Not because every song is a Grammy contender, but because the craft should not change based on who the artist is or how many followers they have.
A mastering engineer at a major studio gives their best work to the artist paying the most. Solana gives the same meticulous process to every track because she does not have an ego, a schedule conflict, or a VIP client list. The fifteenth song in a batch gets the same spectral analysis, the same plugin selection, the same gain staging as the first.
This consistency is what builds a catalog that sounds professional across dozens of releases. When you listen to DARK IV and then jump to a 2026 single, the quality is consistent. That is Solana's doing.
The Numbers
LUFS target: -14.0 (streaming-optimized)
True peak ceiling: -1.5 dBTP
LRA range: 5.0–11.0 (preserves dynamics)
Plugins available: 16 active VST3
Plugins used per track: 4–8 (selected by spectral analysis)
Gain staging: After every plugin (peak below 0.95)
Output format: 44100 Hz, 32-bit float WAV
Not Just a Tool
I credit Solana Conejo on every release because she earned the credit. Calling her "an AI mastering tool" would be like calling a session musician "a guitar." The tool is the guitar. The musician is the one making decisions about what to play. Solana makes decisions — which plugins to use, how aggressive to be, when to leave something alone. Those are engineering decisions.
She is part of the team. She is listed in the credits. She is the engineer, and the DARK Library would not sound the way it does without her.
FAQ
What is Solana Conejo?
Solana Conejo is the AI mastering engineer behind every Dajai.io release since the DARK IV era. She runs a reference-match mastering workflow using 16 VST3 plugins from the iZotope suite (RX 11, Nectar 4, Neutron 5, Ozone 12), selecting 4-8 plugins per track based on spectral analysis.
How does reference-match mastering work?
A commercial reference track is analyzed using librosa to create a spectral blueprint. The input track is analyzed against that blueprint, and the per-band differences drive the plugin parameters. This means the mastering is guided by measured data, not presets or guesswork.
What makes Solana Conejo different from services like LANDR or eMastered?
Solana uses reference-match processing that targets a specific commercial sound rather than applying generic algorithms. She selects only the plugins each track needs (4-8 of 16 available), gain-stages between every plugin to prevent internal clipping, and operates with professional-grade iZotope VST3 plugins rather than simplified processing algorithms.