diff --git a/core/src/agentforge_core/llm/azure.py b/core/src/agentforge_core/llm/azure.py
new file mode 100644
index 0000000..0b1264c
--- /dev/null
+++ b/core/src/agentforge_core/llm/azure.py
@@ -0,0 +1,78 @@
+"""Proveedor Azure OpenAI con retry exponencial y fallback configurable."""
+
+from __future__ import annotations
+
+import asyncio
+import time
+from typing import Any
+
+from openai import AsyncAzureOpenAI
+
+from agentforge_core.llm.base import CompletionResult, Message
+
+
+class AzureOpenAIProvider:
+    """Cliente Azure OpenAI con retry 3x backoff exponencial."""
+
+    name = "azure"
+
+    def __init__(
+        self,
+        endpoint: str,
+        api_key: str,
+        deployment: str,
+        api_version: str,
+    ) -> None:
+        if not (endpoint and api_key and deployment):
+            raise ValueError("Azure OpenAI requiere endpoint, api_key y deployment.")
+        self._client = AsyncAzureOpenAI(
+            azure_endpoint=endpoint,
+            api_key=api_key,
+            api_version=api_version,
+        )
+        self._deployment = deployment
+
+    async def complete(
+        self,
+        messages: list[Message],
+        schema: dict[str, Any] | None = None,
+        temperature: float = 0.2,
+        max_tokens: int = 2000,
+    ) -> CompletionResult:
+        delays = [1.0, 2.0, 4.0]
+        last_exc: Exception | None = None
+        for attempt, delay in enumerate([0.0, *delays]):
+            if delay:
+                await asyncio.sleep(delay)
+            try:
+                return await self._call_once(messages, temperature, max_tokens)
+            except Exception as exc:
+                last_exc = exc
+                if attempt >= len(delays):
+                    break
+        assert last_exc is not None
+        raise last_exc
+
+    async def _call_once(
+        self,
+        messages: list[Message],
+        temperature: float,
+        max_tokens: int,
+    ) -> CompletionResult:
+        start = time.perf_counter()
+        resp = await self._client.chat.completions.create(  # type: ignore[call-overload]
+            model=self._deployment,
+            messages=[m.model_dump() for m in messages],
+            temperature=temperature,
+            max_tokens=max_tokens,
+            response_format={"type": "json_object"},
+        )
+        elapsed = int((time.perf_counter() - start) * 1000)
+        choice = resp.choices[0]
+        return CompletionResult(
+            content=choice.message.content or "",
+            model=resp.model,
+            tokens_in=resp.usage.prompt_tokens if resp.usage else 0,
+            tokens_out=resp.usage.completion_tokens if resp.usage else 0,
+            latency_ms=elapsed,
+        )
diff --git a/core/src/agentforge_core/llm/openai.py b/core/src/agentforge_core/llm/openai.py
new file mode 100644
index 0000000..457fbd4
--- /dev/null
+++ b/core/src/agentforge_core/llm/openai.py
@@ -0,0 +1,60 @@
+"""Proveedor OpenAI directo (fallback)."""
+
+from __future__ import annotations
+
+import asyncio
+import time
+from typing import Any
+
+from openai import AsyncOpenAI
+
+from agentforge_core.llm.base import CompletionResult, Message
+
+
+class OpenAIProvider:
+    """Cliente OpenAI con misma política de retry que Azure."""
+
+    name = "openai"
+
+    def __init__(self, api_key: str, model: str = "gpt-4o") -> None:
+        if not api_key:
+            raise ValueError("OpenAIProvider requiere api_key.")
+        self._client = AsyncOpenAI(api_key=api_key)
+        self._model = model
+
+    async def complete(
+        self,
+        messages: list[Message],
+        schema: dict[str, Any] | None = None,
+        temperature: float = 0.2,
+        max_tokens: int = 2000,
+    ) -> CompletionResult:
+        delays = [1.0, 2.0, 4.0]
+        last_exc: Exception | None = None
+        for attempt, delay in enumerate([0.0, *delays]):
+            if delay:
+                await asyncio.sleep(delay)
+            try:
+                start = time.perf_counter()
+                resp = await self._client.chat.completions.create(  # type: ignore[call-overload]
+                    model=self._model,
+                    messages=[m.model_dump() for m in messages],
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    response_format={"type": "json_object"},
+                )
+                elapsed = int((time.perf_counter() - start) * 1000)
+                choice = resp.choices[0]
+                return CompletionResult(
+                    content=choice.message.content or "",
+                    model=resp.model,
+                    tokens_in=resp.usage.prompt_tokens if resp.usage else 0,
+                    tokens_out=resp.usage.completion_tokens if resp.usage else 0,
+                    latency_ms=elapsed,
+                )
+            except Exception as exc:
+                last_exc = exc
+                if attempt >= len(delays):
+                    break
+        assert last_exc is not None
+        raise last_exc