diff --git a/unknowns_classifier/src/unknowns_classifier/core.py b/unknowns_classifier/src/unknowns_classifier/core.py
new file mode 100644
index 0000000..f1b11a5
--- /dev/null
+++ b/unknowns_classifier/src/unknowns_classifier/core.py
@@ -0,0 +1,68 @@
+from __future__ import annotations
+import logging
+from collections import Counter
+from dataclasses import dataclass
+from typing import List, Dict, Any
+
+__all__ = ["UnknownClassification", "classify_unknowns"]
+
+
+@dataclass
+class UnknownClassification:
+    """Represents a classified Unknown type and its occurrence count."""
+
+    unknown_type: str
+    count: int
+
+    def __post_init__(self) -> None:
+        if not isinstance(self.unknown_type, str):
+            raise TypeError("unknown_type must be a string")
+        if not isinstance(self.count, int):
+            raise TypeError("count must be an integer")
+        if self.count < 0:
+            raise ValueError("count must be non-negative")
+
+
+def _infer_unknown_type(case: Dict[str, Any]) -> str:
+    """Infer the unknown_type from an unknown case dict using simple heuristics."""
+    msg = str(case).lower()
+
+    if "schema" in msg or "field" in msg:
+        return "schema_mismatch"
+    if "missing" in msg or "not found" in msg or "fehlt" in msg:
+        return "artefakt_fehlt"
+    if "timeout" in msg or "connection" in msg:
+        return "netzwerk_problem"
+    if "valueerror" in msg or "parsing" in msg:
+        return "datenfehler"
+    return "unclassified"
+
+
+def classify_unknowns(unknown_cases: List[Dict[str, Any]]) -> List[UnknownClassification]:
+    """Classify a list of unknown cases into categorized UnknownClassification results.
+
+    Args:
+        unknown_cases: List of Unknown-Case dictionaries.
+
+    Returns:
+        List of UnknownClassification instances summarizing counts per type.
+    """
+
+    if not isinstance(unknown_cases, list):
+        raise TypeError("unknown_cases must be a list of dicts")
+
+    logging.debug("Starting classification of %d unknown cases", len(unknown_cases))
+
+    inferred_types = []
+    for idx, case in enumerate(unknown_cases):
+        if not isinstance(case, dict):
+            raise TypeError(f"Entry at index {idx} is not a dict")
+        inferred = _infer_unknown_type(case)
+        logging.debug("Case %d inferred as: %s", idx, inferred)
+        inferred_types.append(inferred)
+
+    counts = Counter(inferred_types)
+    results = [UnknownClassification(unknown_type=t, count=c) for t, c in counts.items()]
+
+    logging.info("Classified %d unique unknown types", len(results))
+    return results