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diff --git a/experiments/Cargo.toml b/experiments/Cargo.toml
new file mode 100644
index 0000000..95299cb
--- /dev/null
+++ b/experiments/Cargo.toml
@@ -0,0 +1,34 @@
+[workspace]
+resolver = "3"
+
+[package]
+name = "doctate-experiments"
+version = "0.1.0"
+edition = "2024"
+
+[dependencies]
+doctate-server = { path = "../server" }
+doctate-common = { path = "../doctate-common" }
+tokio = { version = "1", features = ["full"] }
+reqwest = { version = "0.12", default-features = false, features = ["json", "multipart", "rustls-tls"] }
+serde = { version = "1", features = ["derive"] }
+serde_json = "1"
+clap = { version = "4", features = ["derive"] }
+anyhow = "1"
+tracing = "0.1"
+tracing-subscriber = { version = "0.3", features = ["env-filter"] }
+time = { version = "0.3", features = ["formatting", "macros"] }
+similar = "2"
+tempfile = "3"
+
+[[bin]]
+name = "run_full_case"
+path = "src/bin/run_full_case.rs"
+
+[[bin]]
+name = "run_llm_only"
+path = "src/bin/run_llm_only.rs"
+
+[[bin]]
+name = "diff_runs"
+path = "src/bin/diff_runs.rs"
diff --git a/experiments/prompts/llm/baseline.txt b/experiments/prompts/llm/baseline.txt
new file mode 100644
index 0000000..9acdd31
--- /dev/null
+++ b/experiments/prompts/llm/baseline.txt
@@ -0,0 +1,15 @@
+Du bist ein medizinischer Assistent.
+
+Fasse die folgenden diktierten Abschnitte zu einem zusammenhängenden Text zusammen. Bereinigen und strukturieren, nichts hinzufügen, keine medizinische Interpretation, keine Diagnose, keine Arztbrief-Struktur. Entferne Redundanzen. Spätere Aufnahmen haben Vorrang — Korrekturen, Nachträge und Widersprüche zugunsten der chronologisch letzten Aussage auflösen. Antworte auf Deutsch. Nur der zusammengefasste Text, keine Einleitung, kein Abschlusssatz.
+
+
+WICHTIG: Das Diktat wurde automatisch transkribiert und enthält typische ASR-Fehler wie phonetisch ähnliche Verwechslungen und zerschnittene Komposita (z.B. "Spolade" statt "Schokolade", "posbrandial" statt "postprandial", "in Faust" statt "infaust"). Korrigiere diese Fehler AKTIV. Bei Unsicherheit, wie die Korrektur lauten müsste: behalte das Original bei und markiere es.
+
+
+DOSIERUNGSSCHEMA: 3–4 kleine Zahlen im Medikationskontext sind morgens-mittags-abends(-nachts). Schreibe kompakt: "eins null zwei" → "1-0-2", "eins null zwei null" → "1-0-2-0". Nur bei klarem Medikationskontext anwenden, sonst Original behalten und markieren.
+
+MARKIERUNGEN IM FORMAT "==text==" signalisieren dem Arzt "bitte prüfen".
+Markiere jede korrigierte oder zweifelhafte Stelle.
+Markiere zusätzlich: Zahlen ohne klaren Kontext oder Einheit.
+Markiere sparsam — geläufige, klar gesprochene Fachbegriffe bleiben unmarkiert.
+WICHTIG: Es sind keine anderen Arten von Annotationen erlaubt (z.B. "(unsicher)", "[TODO]").
\ No newline at end of file
diff --git a/experiments/prompts/llm/v1_treue.txt b/experiments/prompts/llm/v1_treue.txt
new file mode 100644
index 0000000..33b78ea
--- /dev/null
+++ b/experiments/prompts/llm/v1_treue.txt
@@ -0,0 +1,23 @@
+Du bist ein medizinischer Assistent.
+
+Fasse die folgenden diktierten Abschnitte zu einem zusammenhängenden Text zusammen. Bereinigen und strukturieren, nichts hinzufügen, keine medizinische Interpretation, keine Diagnose, keine Arztbrief-Struktur. Entferne Redundanzen. Spätere Aufnahmen haben Vorrang — Korrekturen, Nachträge und Widersprüche zugunsten der chronologisch letzten Aussage auflösen. Antworte auf Deutsch. Nur der zusammengefasste Text, keine Einleitung, kein Abschlusssatz.
+
+
+WICHTIG: Das Diktat wurde automatisch transkribiert und enthält typische ASR-Fehler wie phonetisch ähnliche Verwechslungen und zerschnittene Komposita (z.B. "Spolade" statt "Schokolade", "posbrandial" statt "postprandial", "in Faust" statt "infaust"). Korrigiere diese Fehler AKTIV. Bei Unsicherheit, wie die Korrektur lauten müsste: behalte das Original bei und markiere es.
+
+
+TREUE ZUM DIKTAT (höchste Priorität — vor allen anderen Regeln):
+- Anatomische Lokalisationen, Werte mit Einheiten, Wirkstoffnamen, Dosierungen und genannte Befunde NIEMALS umformulieren, eindampfen oder weglassen. Wörtlich übernehmen.
+- KEINE medizinisch klingenden Komposita aus phonetischer Nähe konstruieren. Wenn ein Token kein klares Wort ergibt: markiere es mit ==...== und lass den Rohinhalt stehen, statt zu raten. Lieber ein markiertes Fragment als ein erfundener Begriff.
+- KEINE neuen Tatsachen hinzufügen, auch nicht naheliegende medizinische Interpretationen ("Beschwerden" → NICHT "Brustbeschwerden", "erhöhter Blutdruck" → NICHT "hypertensive Krise").
+- Werte mit Einheiten zusammenhalten ("35 ng/l", nicht nur "35"). Wenn die Einheit im Diktat fehlt: markiere die Zahl.
+- Diktat-Reihenfolge erhalten — Befunde aus dem Status-Abschnitt nicht in die Anamnese verschieben, auch wenn sie thematisch verwandt wirken.
+
+
+DOSIERUNGSSCHEMA: 3–4 kleine Zahlen im Medikationskontext sind morgens-mittags-abends(-nachts). Schreibe kompakt: "eins null zwei" → "1-0-2", "eins null zwei null" → "1-0-2-0". Nur bei klarem Medikationskontext anwenden, sonst Original behalten und markieren.
+
+MARKIERUNGEN IM FORMAT "==text==" signalisieren dem Arzt "bitte prüfen".
+Markiere jede korrigierte oder zweifelhafte Stelle.
+Markiere zusätzlich: Zahlen ohne klaren Kontext oder Einheit.
+Markiere sparsam — geläufige, klar gesprochene Fachbegriffe bleiben unmarkiert.
+WICHTIG: Es sind keine anderen Arten von Annotationen erlaubt (z.B. "(unsicher)", "[TODO]").
\ No newline at end of file
diff --git a/experiments/prompts/llm/v2_treue.txt b/experiments/prompts/llm/v2_treue.txt
new file mode 100644
index 0000000..680ebce
--- /dev/null
+++ b/experiments/prompts/llm/v2_treue.txt
@@ -0,0 +1,29 @@
+Du bist ein medizinischer Assistent.
+
+Fasse die folgenden diktierten Abschnitte zu einem zusammenhängenden Fließtext zusammen. Bereinigen und strukturieren, nichts hinzufügen, keine medizinische Interpretation, keine Diagnose, keine Arztbrief-Struktur. Entferne Redundanzen. Antworte auf Deutsch. Nur der zusammengefasste Text, keine Einleitung, kein Abschlusssatz.
+
+FORMAT: Ein einziger zusammenhängender Fließtext, mehrere Absätze erlaubt. KEINE Inline-Sektionsmarker (kein "Status:", "Diagnostik:", "Therapie:", "Plan:"), KEINE Markdown-Headings, KEINE Aufzählungspunkte.
+
+
+WICHTIG: Das Diktat wurde automatisch transkribiert und enthält typische ASR-Fehler wie phonetisch ähnliche Verwechslungen und zerschnittene Komposita (z.B. "Spolade" statt "Schokolade", "posbrandial" statt "postprandial", "in Faust" statt "infaust"). Korrigiere diese Fehler AKTIV. Bei Unsicherheit, wie die Korrektur lauten müsste: behalte das Original bei und markiere es.
+
+AKTIVE KORREKTUR (nicht durchreichen): Bekannte Wirkstoffnamen, etablierte medizinische Akronyme und Standard-Termini sind aktiv zu korrigieren, wenn der ASR-Fehler eindeutig ist. Wenn die korrigierte Form ein bekannter Wirkstoff oder Standard-Begriff ist und keine andere medizinische Lesart Sinn ergibt: Korrektur ohne Markierung übernehmen.
+
+
+TREUE ZUM DIKTAT (höchste Priorität — vor allen anderen Regeln):
+- Anatomische Lokalisationen, Werte mit Einheiten, Wirkstoffnamen, Dosierungen und genannte Befunde NIEMALS umformulieren, eindampfen oder weglassen. Wörtlich übernehmen.
+- KEINE medizinisch klingenden Komposita aus phonetischer Nähe konstruieren. Wenn ein Token kein klares Wort ergibt: markiere es mit ==...== und lass den Rohinhalt stehen, statt zu raten.
+- KEINE neuen Tatsachen hinzufügen, auch nicht naheliegende medizinische Interpretationen.
+- Werte mit Einheiten zusammenhalten ("35 ng/l", nicht nur "35"). Wenn die Einheit im Diktat fehlt: markiere die Zahl.
+- Diktat-Reihenfolge erhalten — Befunde aus späteren Aufnahmen nicht in die Anamnese verschieben, auch wenn sie thematisch verwandt wirken.
+
+WIDERSPRÜCHE ZWISCHEN AUFNAHMEN: Bei widersprüchlichen Aussagen über mehrere Aufnahmen die chronologisch letzte Aussage übernehmen, die frühere weglassen oder als ==text== markieren. KEINE Verlaufsgeschichte konstruieren (NICHT "die im weiteren Verlauf als X beurteilt wird"). Wenn eine frühere Aufnahme einen offensichtlichen ASR-Fehler enthält und alle späteren Aufnahmen die korrigierte Form zeigen: die spätere als korrekt nehmen, früheren Fehler nicht erwähnen.
+
+
+DOSIERUNGSSCHEMA: 3–4 kleine Zahlen im Medikationskontext sind morgens-mittags-abends(-nachts). Schreibe kompakt: "eins null zwei" → "1-0-2", "eins null zwei null" → "1-0-2-0". Nur bei klarem Medikationskontext anwenden, sonst Original behalten und markieren.
+
+MARKIERUNGEN IM FORMAT "==text==" signalisieren dem Arzt "bitte prüfen".
+Markiere jede zweifelhafte Stelle, bei der die Korrektur nicht eindeutig ist.
+Markiere zusätzlich: Zahlen ohne klaren Kontext oder Einheit.
+Markiere sparsam — eindeutig korrigierte Wirkstoffe und geläufige, klar gesprochene Fachbegriffe bleiben unmarkiert.
+WICHTIG: Es sind keine anderen Arten von Annotationen erlaubt (z.B. "(unsicher)", "[TODO]").
\ No newline at end of file
diff --git a/experiments/prompts/whisper/baseline.txt b/experiments/prompts/whisper/baseline.txt
new file mode 100644
index 0000000..e69de29
diff --git a/experiments/prompts/whisper/v1_dosing_minimal.txt b/experiments/prompts/whisper/v1_dosing_minimal.txt
new file mode 100644
index 0000000..ce13ed6
--- /dev/null
+++ b/experiments/prompts/whisper/v1_dosing_minimal.txt
@@ -0,0 +1 @@
+Internistischer Befund: Bisoprolol 5 mg 1-0-0, Ramipril 5 mg 1-0-1, Pantoprazol 40 mg 1-0-0-1, ASS 100 mg 1-0-0.
\ No newline at end of file
diff --git a/experiments/prompts/whisper_hotwords/README.md b/experiments/prompts/whisper_hotwords/README.md
new file mode 100644
index 0000000..07dc708
--- /dev/null
+++ b/experiments/prompts/whisper_hotwords/README.md
@@ -0,0 +1,29 @@
+# Whisper Hotwords — handle with extreme care
+
+Whisper-Hotwords bias'en das ASR-Modell aggressiv. Ein Hotword, das in
+einem konkreten Fall hilft, kann in einem unverwandten Diktat dazu
+führen, dass das Modell den Begriff aus phonetischer Ähnlichkeit
+**halluziniert** (orthopädischer Befund schreibt plötzlich
+„Holosystolikum").
+
+## Bevorzugter Korrekturpfad
+
+`server/vocab/*.txt` (Gazetteer, edit-distance ≤ 2 mit Dict-Veto).
+Strukturell halluzinationsfrei, weil Korrekturen nur greifen, wenn
+Whisper bereits ein Token erzeugt hat, das phonetisch nah am
+Vocabulary-Eintrag liegt.
+
+## Wenn überhaupt Hotwords
+
+- Nur generische Termini aus einem breiten Fall-Korpus
+- Nicht aus einem einzelnen Test-Fall heraus optimiert (Curve-Fitting)
+- Vor Aktivierung: Negativ-Kontrolle gegen Diktate aus mehreren
+  Fachbereichen — sucht das Modell nach Halluzinationen, die nur durch
+  den Hotword-Bias entstehen?
+
+## Datei-Konvention
+
+Hotword-Files in diesem Verzeichnis enthalten **ausschließlich
+whitespace-separierte Termini** (kein Markdown, keine Kommentare),
+weil der gesamte File-Inhalt 1:1 als `hotwords`-Form-Field an die
+Whisper-API gesendet wird.
diff --git a/experiments/src/bin/diff_runs.rs b/experiments/src/bin/diff_runs.rs
new file mode 100644
index 0000000..767a24f
--- /dev/null
+++ b/experiments/src/bin/diff_runs.rs
@@ -0,0 +1,121 @@
+//! Side-by-side diff between two runs.
+//!
+//! Usage:
+//!   diff_runs <run-dir-A> <run-dir-B>
+//!
+//! Prints a unified diff of `document.md` and a summary of `==` markers
+//! per run, with variant identities pulled from `meta.json`.
+
+use std::path::{Path, PathBuf};
+
+use anyhow::{Context, Result};
+use clap::Parser;
+use similar::{ChangeTag, TextDiff};
+
+#[derive(Parser, Debug)]
+#[command(name = "diff_runs")]
+struct Args {
+    run_a: PathBuf,
+    run_b: PathBuf,
+}
+
+fn main() -> Result<()> {
+    let args = Args::parse();
+
+    println!("=== A: {}", args.run_a.display());
+    print_meta_summary(&args.run_a)?;
+    println!("=== B: {}", args.run_b.display());
+    print_meta_summary(&args.run_b)?;
+
+    let doc_a = read_or_empty(&args.run_a.join("document.md"))?;
+    let doc_b = read_or_empty(&args.run_b.join("document.md"))?;
+
+    println!("\n--- document.md diff (A → B) ---");
+    print_diff(&doc_a, &doc_b);
+
+    println!(
+        "\n=={{}}== markers   A: {}   B: {}",
+        count_markers(&doc_a),
+        count_markers(&doc_b)
+    );
+
+    diff_transcripts(&args.run_a, &args.run_b)?;
+
+    Ok(())
+}
+
+fn print_meta_summary(run: &Path) -> Result<()> {
+    let meta_path = run.join("meta.json");
+    let raw = match std::fs::read_to_string(&meta_path) {
+        Ok(s) => s,
+        Err(_) => {
+            println!("  (no meta.json)");
+            return Ok(());
+        }
+    };
+    let v: serde_json::Value = serde_json::from_str(&raw).context("parsing meta.json")?;
+    let w = v.get("whisper_variant").and_then(|x| x.as_str()).unwrap_or("?");
+    let h = v
+        .get("whisper_hotwords_variant")
+        .and_then(|x| x.as_str())
+        .unwrap_or("none");
+    let l = v.get("llm_variant").and_then(|x| x.as_str()).unwrap_or("?");
+    let model = v.get("llm_model").and_then(|x| x.as_str()).unwrap_or("?");
+    let wallclock = v
+        .pointer("/timings_ms/wallclock_ms")
+        .and_then(|x| x.as_u64())
+        .unwrap_or(0);
+    println!("  whisper={w}  hotwords={h}  llm={l}  model={model}  wallclock={wallclock}ms");
+    Ok(())
+}
+
+fn read_or_empty(p: &Path) -> Result<String> {
+    Ok(std::fs::read_to_string(p).unwrap_or_default())
+}
+
+fn print_diff(a: &str, b: &str) {
+    let diff = TextDiff::from_lines(a, b);
+    for change in diff.iter_all_changes() {
+        let sign = match change.tag() {
+            ChangeTag::Equal => "  ",
+            ChangeTag::Insert => "+ ",
+            ChangeTag::Delete => "- ",
+        };
+        print!("{sign}{change}");
+    }
+}
+
+fn count_markers(text: &str) -> usize {
+    text.matches("==").count() / 2
+}
+
+fn diff_transcripts(a: &Path, b: &Path) -> Result<()> {
+    let ta = a.join("transcripts");
+    let tb = b.join("transcripts");
+    if !ta.exists() || !tb.exists() {
+        return Ok(());
+    }
+    let mut names: Vec<String> = std::fs::read_dir(&ta)?
+        .filter_map(|e| e.ok())
+        .filter_map(|e| {
+            let p = e.path();
+            if p.extension().and_then(|s| s.to_str()) == Some("txt") {
+                p.file_name().map(|s| s.to_string_lossy().into_owned())
+            } else {
+                None
+            }
+        })
+        .collect();
+    names.sort();
+
+    for name in names {
+        let txt_a = read_or_empty(&ta.join(&name))?;
+        let txt_b = read_or_empty(&tb.join(&name))?;
+        if txt_a == txt_b {
+            continue;
+        }
+        println!("\n--- transcripts/{name} (A → B) ---");
+        print_diff(&txt_a, &txt_b);
+    }
+    Ok(())
+}
diff --git a/experiments/src/bin/run_full_case.rs b/experiments/src/bin/run_full_case.rs
new file mode 100644
index 0000000..b44b4e8
--- /dev/null
+++ b/experiments/src/bin/run_full_case.rs
@@ -0,0 +1,358 @@
+//! Full-pipeline runner: audio → ffmpeg → whisper → gazetteer → LLM.
+//!
+//! Reproduces the production pipeline 1:1 by reusing the `doctate-server`
+//! crate's modules. Outputs go strictly under `<case-dir>/runs/<run-id>/`.
+//!
+//! Usage:
+//!   run_full_case \
+//!     --case-dir case_c414cf52 \
+//!     --whisper-prompt prompts/whisper/v1_dosing_minimal.txt \
+//!     --whisper-hotwords prompts/whisper_hotwords/v1_drugs.txt \
+//!     --llm-prompt prompts/llm/baseline.txt \
+//!     --runs 3
+//!
+//! Path conventions:
+//!   - `--case-dir` is relative to the experiments/ working directory
+//!   - `--*-prompt` and `--*-hotwords` are paths relative to `--case-dir`
+//!   - `--settings` defaults to `../server/settings.toml`
+//!   - `--vocab-dir` defaults to `../server/vocab`
+
+use std::path::{Path, PathBuf};
+use std::time::{Duration, Instant};
+
+use anyhow::{Context, Result};
+use clap::Parser;
+use doctate_experiments::{
+    GazetteerDictMode, RecordingMeta, RunMeta, RunTimings, atomic_write, load_prompt, run_id,
+};
+use doctate_server::analyze::llm::{self as srv_llm, LlmSettings as LlmCallSettings};
+use doctate_server::analyze::prompt::render_prompt;
+use doctate_server::analyze::{AnalysisInput, RecordingInput};
+use doctate_server::config::WhisperUserSettings;
+use doctate_server::gazetteer::{Gazetteer, SpellbookDict};
+use doctate_server::settings::Settings;
+use doctate_server::transcribe::ffmpeg::remux_faststart;
+use doctate_server::transcribe::whisper as srv_whisper;
+use tracing::{info, warn};
+
+#[derive(Parser, Debug)]
+#[command(name = "run_full_case")]
+struct Args {
+    /// Directory containing `audios/`, `prompts/`, `runs/` for one case.
+    #[arg(long)]
+    case_dir: PathBuf,
+
+    /// Path to a Whisper `initial_prompt` file. Empty file → no
+    /// initial_prompt forwarded. Prompts are fall-übergreifend, typically
+    /// under `prompts/whisper/`.
+    #[arg(long)]
+    whisper_prompt: PathBuf,
+
+    /// Optional Whisper `hotwords` file (handle with care — see
+    /// `prompts/whisper_hotwords/README.md`).
+    #[arg(long)]
+    whisper_hotwords: Option<PathBuf>,
+
+    /// Path to the LLM system prompt file. Typically under `prompts/llm/`.
+    #[arg(long)]
+    llm_prompt: PathBuf,
+
+    /// Number of runs to perform with the same variants. 2–3 recommended
+    /// to surface model drift.
+    #[arg(long, default_value_t = 1)]
+    runs: u32,
+
+    /// Settings file (URL, model, API key for LLM; URL, timeout for Whisper).
+    #[arg(long, default_value = "../server/settings.toml")]
+    settings: PathBuf,
+
+    /// Vocab directory for the gazetteer.
+    #[arg(long, default_value = "../server/vocab")]
+    vocab_dir: PathBuf,
+
+    /// Hunspell stem (e.g. `/usr/share/hunspell/de_DE`). Optional; if the
+    /// files don't exist, gazetteer runs without dict-veto.
+    #[arg(long, default_value = "/usr/share/hunspell/de_DE")]
+    hunspell_stem: PathBuf,
+
+    /// Skip the LLM stage. Useful for measuring pure Whisper-prompt
+    /// effects without burning Ionos tokens.
+    #[arg(long, default_value_t = false)]
+    no_llm: bool,
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    init_tracing();
+    let args = Args::parse();
+
+    let case_dir = args
+        .case_dir
+        .canonicalize()
+        .with_context(|| format!("case-dir not found: {}", args.case_dir.display()))?;
+
+    let settings_path = args.settings.to_string_lossy();
+    let settings = Settings::load_or_default(&settings_path);
+    if !settings.llm_configured() && !args.no_llm {
+        anyhow::bail!(
+            "LLM not configured in {settings_path}. Set [llm].url and [llm].model, or pass --no-llm."
+        );
+    }
+
+    let whisper_prompt_text = load_prompt(&args.whisper_prompt)?;
+    let whisper_hotwords_text = match args.whisper_hotwords.as_ref() {
+        Some(p) => Some(load_prompt(p)?),
+        None => None,
+    };
+    let llm_system_prompt = load_prompt(&args.llm_prompt)?;
+
+    let user_whisper = WhisperUserSettings {
+        language: Some("de".to_string()),
+        hotwords: whisper_hotwords_text.clone().filter(|s| !s.is_empty()),
+        initial_prompt: Some(whisper_prompt_text.clone()).filter(|s| !s.is_empty()),
+    };
+
+    let (gazetteer, dict_mode) = load_gazetteer(&args.vocab_dir, &args.hunspell_stem).await?;
+    info!(
+        vocab_dir = %args.vocab_dir.display(),
+        loaded = gazetteer.len(),
+        "gazetteer ready"
+    );
+
+    let audios = collect_audios(&case_dir.join("audios"))?;
+    if audios.is_empty() {
+        anyhow::bail!("no .m4a files found under {}/audios", case_dir.display());
+    }
+    info!(count = audios.len(), "audios discovered");
+
+    let http = reqwest::Client::builder()
+        .build()
+        .context("building reqwest client")?;
+
+    let whisper_variant_id = stem(&args.whisper_prompt);
+    let hotwords_variant_id = args.whisper_hotwords.as_ref().map(stem);
+    let llm_variant_id = stem(&args.llm_prompt);
+
+    let runs_root = data_runs_root(&case_dir)?;
+
+    for run_index in 1..=args.runs {
+        let id = run_id(&whisper_variant_id, &llm_variant_id, run_index);
+        let run_dir = runs_root.join(&id);
+        std::fs::create_dir_all(run_dir.join("transcripts"))?;
+
+        info!(run = %id, "begin run");
+        let wallclock = Instant::now();
+        let mut timings = RunTimings::default();
+        let mut recordings_meta = Vec::new();
+        let mut analysis_recordings = Vec::new();
+
+        for audio in &audios {
+            let recorded_at = stem(audio);
+            let t_whisper = Instant::now();
+            let raw = transcribe_one(
+                &http,
+                &settings,
+                &user_whisper,
+                audio,
+            )
+            .await
+            .with_context(|| format!("transcribing {}", audio.display()))?;
+            timings.whisper_total_ms += t_whisper.elapsed().as_millis() as u64;
+
+            let t_gaz = Instant::now();
+            let cleaned = gazetteer.replace(&raw);
+            timings.gazetteer_total_ms += t_gaz.elapsed().as_millis() as u64;
+
+            let transcript_path = run_dir.join("transcripts").join(format!("{recorded_at}.txt"));
+            atomic_write(&transcript_path, &cleaned)?;
+
+            recordings_meta.push(RecordingMeta {
+                recorded_at: recorded_at.clone(),
+                audio_path: audio.display().to_string(),
+                whisper_chars_raw: raw.chars().count(),
+                whisper_chars_after_gazetteer: cleaned.chars().count(),
+            });
+            analysis_recordings.push(RecordingInput {
+                recorded_at,
+                text: cleaned,
+            });
+        }
+
+        let last_recording_mtime = audios
+            .last()
+            .map(|p| stem(p))
+            .unwrap_or_else(|| "unknown".to_string());
+        let analysis_input = AnalysisInput {
+            last_recording_mtime,
+            recordings: analysis_recordings,
+        };
+        let user_content = render_prompt(&analysis_input);
+        atomic_write(&run_dir.join("llm_input.txt"), &user_content)?;
+
+        if !args.no_llm {
+            let t_llm = Instant::now();
+            let document_raw = call_llm(&http, &settings, &llm_system_prompt, &user_content).await?;
+            timings.llm_ms = t_llm.elapsed().as_millis() as u64;
+            // Post-LLM gazetteer pass — mirrors `server/src/analyze/worker.rs:150`.
+            // Catches LLM-drift back to non-canonical forms (e.g. anglicization)
+            // that the pre-LLM pass cannot reach because the drift happens
+            // inside the LLM itself.
+            let document = gazetteer.replace(&document_raw);
+            atomic_write(&run_dir.join("document.md"), &document)?;
+        }
+
+        timings.wallclock_ms = wallclock.elapsed().as_millis() as u64;
+
+        let meta = RunMeta {
+            run_id: id.clone(),
+            created_at_utc: time::OffsetDateTime::now_utc()
+                .format(&time::format_description::well_known::Iso8601::DEFAULT)
+                .unwrap_or_default(),
+            case: case_dir
+                .file_name()
+                .map(|s| s.to_string_lossy().into_owned())
+                .unwrap_or_default(),
+            whisper_variant: whisper_variant_id.clone(),
+            whisper_hotwords_variant: hotwords_variant_id.clone(),
+            llm_variant: llm_variant_id.clone(),
+            whisper_url: settings.whisper.url.clone(),
+            llm_url: settings.llm.url.clone(),
+            llm_model: settings.llm.model.clone(),
+            llm_temperature: settings.llm.temperature,
+            vocab_dir: args.vocab_dir.display().to_string(),
+            vocab_loaded: gazetteer.len(),
+            gazetteer_dict: dict_mode_clone(&dict_mode),
+            timings_ms: timings,
+            recordings: recordings_meta,
+        };
+        let meta_json = serde_json::to_string_pretty(&meta)?;
+        atomic_write(&run_dir.join("meta.json"), &meta_json)?;
+
+        info!(run = %id, wallclock_ms = meta.timings_ms.wallclock_ms, "run done");
+    }
+
+    Ok(())
+}
+
+fn init_tracing() {
+    use tracing_subscriber::EnvFilter;
+    let filter = EnvFilter::try_from_default_env().unwrap_or_else(|_| EnvFilter::new("info"));
+    tracing_subscriber::fmt().with_env_filter(filter).init();
+}
+
+async fn load_gazetteer(
+    vocab_dir: &Path,
+    hunspell_stem: &Path,
+) -> Result<(Gazetteer, GazetteerDictMode)> {
+    let g = Gazetteer::load_dir(vocab_dir)
+        .await
+        .with_context(|| format!("loading vocab dir {}", vocab_dir.display()))?;
+    let aff = hunspell_stem.with_extension("aff");
+    let dic = hunspell_stem.with_extension("dic");
+    if aff.exists() && dic.exists() {
+        match SpellbookDict::load(hunspell_stem) {
+            Ok(d) => {
+                let g = g.with_dict(Box::new(d));
+                Ok((
+                    g,
+                    GazetteerDictMode::SpellbookHunspell {
+                        stem: hunspell_stem.display().to_string(),
+                    },
+                ))
+            }
+            Err(e) => {
+                warn!(
+                    err = %e,
+                    "spellbook dict load failed; gazetteer running without dict-veto"
+                );
+                Ok((g, GazetteerDictMode::NoDict))
+            }
+        }
+    } else {
+        warn!(
+            stem = %hunspell_stem.display(),
+            "hunspell .aff/.dic not found; gazetteer running without dict-veto"
+        );
+        Ok((g, GazetteerDictMode::NoDict))
+    }
+}
+
+fn dict_mode_clone(m: &GazetteerDictMode) -> GazetteerDictMode {
+    match m {
+        GazetteerDictMode::NoDict => GazetteerDictMode::NoDict,
+        GazetteerDictMode::SpellbookHunspell { stem } => GazetteerDictMode::SpellbookHunspell {
+            stem: stem.clone(),
+        },
+    }
+}
+
+/// Resolve the per-case output root under `experiments/_data/<case_name>/runs/`.
+/// Inputs (audios/, prompts/, reference/) live under `case_<id>/` and are
+/// versioned; outputs go to `_data/` and are gitignored.
+fn data_runs_root(case_dir: &Path) -> Result<PathBuf> {
+    let case_name = case_dir
+        .file_name()
+        .and_then(|s| s.to_str())
+        .ok_or_else(|| anyhow::anyhow!("case-dir has no file name"))?;
+    let experiments_root = case_dir
+        .parent()
+        .ok_or_else(|| anyhow::anyhow!("case-dir has no parent"))?;
+    let runs = experiments_root.join("_data").join(case_name).join("runs");
+    std::fs::create_dir_all(&runs)?;
+    Ok(runs)
+}
+
+fn collect_audios(dir: &Path) -> Result<Vec<PathBuf>> {
+    let mut out = Vec::new();
+    for entry in std::fs::read_dir(dir)? {
+        let entry = entry?;
+        let path = entry.path();
+        if path.extension().and_then(|s| s.to_str()) == Some("m4a") {
+            out.push(path);
+        }
+    }
+    out.sort();
+    Ok(out)
+}
+
+fn stem<P: AsRef<Path>>(p: P) -> String {
+    p.as_ref()
+        .file_stem()
+        .map(|s| s.to_string_lossy().into_owned())
+        .unwrap_or_else(|| "unknown".to_string())
+}
+
+async fn transcribe_one(
+    http: &reqwest::Client,
+    settings: &Settings,
+    user_whisper: &WhisperUserSettings,
+    audio: &Path,
+) -> Result<String> {
+    let remuxed = remux_faststart(audio)
+        .await
+        .with_context(|| format!("ffmpeg remux failed for {}", audio.display()))?;
+    let timeout = Duration::from_secs(settings.whisper.timeout_seconds);
+    let text = srv_whisper::transcribe(http, &settings.whisper.url, remuxed.path(), timeout, user_whisper)
+        .await
+        .map_err(|e| anyhow::anyhow!("whisper transcribe failed: {e}"))?;
+    Ok(text)
+}
+
+async fn call_llm(
+    http: &reqwest::Client,
+    settings: &Settings,
+    system_prompt: &str,
+    user_content: &str,
+) -> Result<String> {
+    let call = LlmCallSettings {
+        base_url: &settings.llm.url,
+        api_key: &settings.llm.api_key,
+        model: &settings.llm.model,
+        temperature: settings.llm.temperature,
+    };
+    let timeout = Duration::from_secs(settings.llm.timeout_seconds);
+    let out = srv_llm::chat_once(http, &call, system_prompt, user_content, timeout)
+        .await
+        .map_err(|e| anyhow::anyhow!("llm chat failed: {e}"))?;
+    Ok(out)
+}
diff --git a/experiments/src/bin/run_llm_only.rs b/experiments/src/bin/run_llm_only.rs
new file mode 100644
index 0000000..a748ae8
--- /dev/null
+++ b/experiments/src/bin/run_llm_only.rs
@@ -0,0 +1,224 @@
+//! LLM-only iteration: skip Whisper, use the production-bereinigten
+//! transcripts that already live next to the audio files (`<stem>.json`
+//! contains the gazetteer-cleaned text the server uses as LLM input).
+//!
+//! Usage:
+//!   run_llm_only \
+//!     --case-dir case_c414cf52 \
+//!     --transcripts-dir /home/brummel/dev/doctate/tmpdata/dr_mueller/c414cf52-1ca8-440d-844f-a7d19ed584fd \
+//!     --llm-prompt prompts/llm/v1_keep_headings.txt \
+//!     --runs 3
+
+use std::path::{Path, PathBuf};
+
+fn data_runs_root(case_dir: &Path) -> anyhow::Result<PathBuf> {
+    let case_name = case_dir
+        .file_name()
+        .and_then(|s| s.to_str())
+        .ok_or_else(|| anyhow::anyhow!("case-dir has no file name"))?;
+    let experiments_root = case_dir
+        .parent()
+        .ok_or_else(|| anyhow::anyhow!("case-dir has no parent"))?;
+    let runs = experiments_root.join("_data").join(case_name).join("runs");
+    std::fs::create_dir_all(&runs)?;
+    Ok(runs)
+}
+use std::time::{Duration, Instant};
+
+use anyhow::{Context, Result};
+use clap::Parser;
+use doctate_experiments::{
+    GazetteerDictMode, RecordingMeta, RunMeta, RunTimings, atomic_write, load_prompt, run_id,
+};
+use doctate_server::analyze::llm::{self as srv_llm, LlmSettings as LlmCallSettings};
+use doctate_server::analyze::prompt::render_prompt;
+use doctate_server::analyze::{AnalysisInput, RecordingInput};
+use doctate_server::gazetteer::Gazetteer;
+use doctate_server::settings::Settings;
+use serde::Deserialize;
+use tracing::info;
+
+#[derive(Parser, Debug)]
+#[command(name = "run_llm_only")]
+struct Args {
+    #[arg(long)]
+    case_dir: PathBuf,
+
+    /// Directory containing the `<recorded_at>.json` transcript files.
+    /// Typically `tmpdata/<user>/<case-uuid>/`.
+    #[arg(long)]
+    transcripts_dir: PathBuf,
+
+    #[arg(long)]
+    llm_prompt: PathBuf,
+
+    #[arg(long, default_value_t = 1)]
+    runs: u32,
+
+    #[arg(long, default_value = "../server/settings.toml")]
+    settings: PathBuf,
+
+    /// Vocab dir for the Post-LLM gazetteer pass. Mirrors the server's
+    /// `analyze/worker.rs:150` post-AI normalization. Pass `none` to skip.
+    #[arg(long, default_value = "../server/vocab")]
+    vocab_dir: PathBuf,
+}
+
+#[derive(Debug, Deserialize)]
+struct StoredTranscript {
+    transcript: TranscriptInner,
+}
+
+#[derive(Debug, Deserialize)]
+struct TranscriptInner {
+    text: String,
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    init_tracing();
+    let args = Args::parse();
+
+    let case_dir = args
+        .case_dir
+        .canonicalize()
+        .with_context(|| format!("case-dir not found: {}", args.case_dir.display()))?;
+    let settings = Settings::load_or_default(&args.settings.to_string_lossy());
+    if !settings.llm_configured() {
+        anyhow::bail!("LLM not configured in {}", args.settings.display());
+    }
+
+    let llm_system_prompt = load_prompt(&args.llm_prompt)?;
+    let recordings = load_transcripts(&args.transcripts_dir)?;
+    info!(count = recordings.len(), "transcripts loaded");
+
+    let analysis_input = AnalysisInput {
+        last_recording_mtime: recordings
+            .last()
+            .map(|r| r.recorded_at.clone())
+            .unwrap_or_default(),
+        recordings,
+    };
+    let user_content = render_prompt(&analysis_input);
+
+    let http = reqwest::Client::builder().build()?;
+    let llm_variant_id = stem(&args.llm_prompt);
+    let runs_root = data_runs_root(&case_dir)?;
+
+    let gazetteer = Gazetteer::load_dir(&args.vocab_dir)
+        .await
+        .with_context(|| format!("loading vocab dir {}", args.vocab_dir.display()))?;
+    info!(loaded = gazetteer.len(), vocab_dir = %args.vocab_dir.display(), "post-llm gazetteer ready");
+
+    for run_index in 1..=args.runs {
+        let id = run_id("none", &llm_variant_id, run_index);
+        let run_dir = runs_root.join(&id);
+        std::fs::create_dir_all(&run_dir)?;
+
+        atomic_write(&run_dir.join("llm_input.txt"), &user_content)?;
+
+        let wallclock = Instant::now();
+        let t_llm = Instant::now();
+        let document_raw = call_llm(&http, &settings, &llm_system_prompt, &user_content).await?;
+        // Post-LLM gazetteer pass — mirrors server/src/analyze/worker.rs:150
+        let document = gazetteer.replace(&document_raw);
+        let timings = RunTimings {
+            whisper_total_ms: 0,
+            gazetteer_total_ms: 0,
+            llm_ms: t_llm.elapsed().as_millis() as u64,
+            wallclock_ms: wallclock.elapsed().as_millis() as u64,
+        };
+        atomic_write(&run_dir.join("document.md"), &document)?;
+
+        let meta = RunMeta {
+            run_id: id.clone(),
+            created_at_utc: time::OffsetDateTime::now_utc()
+                .format(&time::format_description::well_known::Iso8601::DEFAULT)
+                .unwrap_or_default(),
+            case: case_dir
+                .file_name()
+                .map(|s| s.to_string_lossy().into_owned())
+                .unwrap_or_default(),
+            whisper_variant: "none".into(),
+            whisper_hotwords_variant: None,
+            llm_variant: llm_variant_id.clone(),
+            whisper_url: String::new(),
+            llm_url: settings.llm.url.clone(),
+            llm_model: settings.llm.model.clone(),
+            llm_temperature: settings.llm.temperature,
+            vocab_dir: format!("{} (post-LLM only)", args.vocab_dir.display()),
+            vocab_loaded: gazetteer.len(),
+            gazetteer_dict: GazetteerDictMode::NoDict,
+            timings_ms: timings,
+            recordings: Vec::<RecordingMeta>::new(),
+        };
+        atomic_write(
+            &run_dir.join("meta.json"),
+            &serde_json::to_string_pretty(&meta)?,
+        )?;
+        info!(run = %id, "llm-only run done");
+    }
+
+    Ok(())
+}
+
+fn init_tracing() {
+    use tracing_subscriber::EnvFilter;
+    let filter = EnvFilter::try_from_default_env().unwrap_or_else(|_| EnvFilter::new("info"));
+    tracing_subscriber::fmt().with_env_filter(filter).init();
+}
+
+fn load_transcripts(dir: &Path) -> Result<Vec<RecordingInput>> {
+    let mut out = Vec::new();
+    for entry in std::fs::read_dir(dir)? {
+        let entry = entry?;
+        let path = entry.path();
+        if path.extension().and_then(|s| s.to_str()) != Some("json") {
+            continue;
+        }
+        let recorded_at = path
+            .file_stem()
+            .and_then(|s| s.to_str())
+            .unwrap_or("")
+            .to_string();
+        if recorded_at.is_empty() || recorded_at == "oneliner" {
+            continue;
+        }
+        let raw = std::fs::read_to_string(&path)?;
+        let parsed: StoredTranscript = match serde_json::from_str(&raw) {
+            Ok(p) => p,
+            Err(_) => continue,
+        };
+        out.push(RecordingInput {
+            recorded_at,
+            text: parsed.transcript.text,
+        });
+    }
+    out.sort_by(|a, b| a.recorded_at.cmp(&b.recorded_at));
+    Ok(out)
+}
+
+fn stem<P: AsRef<Path>>(p: P) -> String {
+    p.as_ref()
+        .file_stem()
+        .map(|s| s.to_string_lossy().into_owned())
+        .unwrap_or_else(|| "unknown".to_string())
+}
+
+async fn call_llm(
+    http: &reqwest::Client,
+    settings: &Settings,
+    system_prompt: &str,
+    user_content: &str,
+) -> Result<String> {
+    let call = LlmCallSettings {
+        base_url: &settings.llm.url,
+        api_key: &settings.llm.api_key,
+        model: &settings.llm.model,
+        temperature: settings.llm.temperature,
+    };
+    let timeout = Duration::from_secs(settings.llm.timeout_seconds);
+    srv_llm::chat_once(http, &call, system_prompt, user_content, timeout)
+        .await
+        .map_err(|e| anyhow::anyhow!("llm chat failed: {e}"))
+}
diff --git a/experiments/src/lib.rs b/experiments/src/lib.rs
new file mode 100644
index 0000000..c61694e
--- /dev/null
+++ b/experiments/src/lib.rs
@@ -0,0 +1,98 @@
+//! Helpers shared by the experiment binaries.
+//!
+//! Sandbox tooling for iterating on Whisper / LLM prompts against a real case
+//! without modifying production state. All outputs land under `case_<id>/runs/`
+//! and `case_<id>/compare/` — never in `tmpdata/`.
+//!
+//! **Security note**: The Ionos bearer key flows through this code as a
+//! `String` inside `Settings.llm.api_key`. Helpers here MUST NOT persist or
+//! print the key. `RunMeta` deliberately stores only the URL/model/timestamp —
+//! never the key — so on-disk audit logs are safe to share.
+
+use std::path::Path;
+
+use anyhow::Context;
+use serde::Serialize;
+use time::OffsetDateTime;
+use time::format_description::well_known::Iso8601;
+
+/// Generate a run identifier in the form
+/// `<UTC-ISO>_w-<wid>_l-<lid>_run<n>`. Used as the directory name under
+/// `case_<id>/runs/`.
+pub fn run_id(whisper_variant: &str, llm_variant: &str, run_index: u32) -> String {
+    let now = OffsetDateTime::now_utc();
+    let stamp = now.format(&Iso8601::DEFAULT).unwrap_or_else(|_| "unknown".into());
+    let safe_stamp = stamp.replace(':', "-").replace('.', "-");
+    format!("{safe_stamp}_w-{whisper_variant}_l-{llm_variant}_run{run_index}")
+}
+
+/// Read a prompt file. Returns empty string for an empty file (used as
+/// "no prompt" signal by `run_full_case`'s settings override).
+pub fn load_prompt(path: &Path) -> anyhow::Result<String> {
+    let content = std::fs::read_to_string(path)
+        .with_context(|| format!("reading prompt file {}", path.display()))?;
+    Ok(content.trim_end_matches('\n').to_string())
+}
+
+/// Atomically write content to `path` via a sibling tempfile + rename.
+/// Same pattern the server uses for `document.md` — ensures readers never
+/// observe a partial file.
+pub fn atomic_write(path: &Path, content: &str) -> anyhow::Result<()> {
+    let parent = path
+        .parent()
+        .with_context(|| format!("path {} has no parent", path.display()))?;
+    std::fs::create_dir_all(parent)?;
+    let mut tmp = tempfile::Builder::new()
+        .prefix(".tmp-")
+        .tempfile_in(parent)?;
+    use std::io::Write;
+    tmp.write_all(content.as_bytes())?;
+    tmp.flush()?;
+    tmp.persist(path)
+        .map_err(|e| anyhow::anyhow!("persist failed: {}", e.error))?;
+    Ok(())
+}
+
+/// Snapshot of variant identities + provenance for one run. Serialized
+/// as `meta.json` next to the produced `document.md`. **Never contains
+/// the API key** — only the LLM endpoint URL and model name.
+#[derive(Debug, Serialize)]
+pub struct RunMeta {
+    pub run_id: String,
+    pub created_at_utc: String,
+    pub case: String,
+    pub whisper_variant: String,
+    pub whisper_hotwords_variant: Option<String>,
+    pub llm_variant: String,
+    pub whisper_url: String,
+    pub llm_url: String,
+    pub llm_model: String,
+    pub llm_temperature: f32,
+    pub vocab_dir: String,
+    pub vocab_loaded: usize,
+    pub gazetteer_dict: GazetteerDictMode,
+    pub timings_ms: RunTimings,
+    pub recordings: Vec<RecordingMeta>,
+}
+
+#[derive(Debug, Serialize)]
+pub enum GazetteerDictMode {
+    NoDict,
+    SpellbookHunspell { stem: String },
+}
+
+#[derive(Debug, Default, Serialize)]
+pub struct RunTimings {
+    pub whisper_total_ms: u64,
+    pub gazetteer_total_ms: u64,
+    pub llm_ms: u64,
+    pub wallclock_ms: u64,
+}
+
+#[derive(Debug, Serialize)]
+pub struct RecordingMeta {
+    pub recorded_at: String,
+    pub audio_path: String,
+    pub whisper_chars_raw: usize,
+    pub whisper_chars_after_gazetteer: usize,
+}