diff --git a/backend/app/bots/adaptive_cards.py b/backend/app/bots/adaptive_cards.py
new file mode 100644
index 0000000..60fb316
--- /dev/null
+++ b/backend/app/bots/adaptive_cards.py
@@ -0,0 +1,47 @@
+from typing import Dict, Any
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+import asyncio
+
+class AdaptiveCards:
+    def __init__(self):
+        self.llm = ChatOpenAI(temperature=0)
+        self.prompt = ChatPromptTemplate.from_template("""
+            You are a Microsoft Adaptive Card generator. Given a data schema and known values,
+            generate an Adaptive Card (v1.3) that asks the user only for missing fields.
+
+            Use this schema: https://adaptivecards.io/schemas/adaptive-card.json
+            Respond only with valid Adaptive Card JSON. Do not include explanations.
+            Always include isRequired, and errorMessage in the schema.
+            Always include a submit button at the bottom of the card as defined in the schema.
+
+            ### Schema:
+            {schema}
+
+            ### Known values:
+            {known_values}
+
+            """)
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def generate_card(self, schema: Dict[str, Any], known_values: Dict[str, Any]) -> Dict[str, Any]:
+        loop = asyncio.get_running_loop()
+        return await loop.run_in_executor(None, self.chain.run, {
+            "schema": schema,
+            "known_values": known_values
+        })
+
+    def create_welcome_card(self):
+        """Create a welcome card"""
+        return {
+            "type": "AdaptiveCard",
+            "body": [
+                {
+                    "type": "TextBlock",
+                    "text": "Welcome to the Housing Bot!",
+                    "size": "large"
+                }
+            ],
+            "version": "1.0"
+        }
diff --git a/backend/app/bots/dayta.py b/backend/app/bots/dayta.py
new file mode 100644
index 0000000..d0ec9f7
--- /dev/null
+++ b/backend/app/bots/dayta.py
@@ -0,0 +1,115 @@
+import json
+from typing import Annotated
+from fastapi import Depends
+from langchain.chat_models import ChatOpenAI
+from botbuilder.core import ActivityHandler, TurnContext
+from botbuilder.schema import Activity, Attachment, ActivityTypes
+import asyncio
+
+from pydantic import ValidationError
+
+from backend.app.bots.adaptive_cards import AdaptiveCards
+from backend.app.bots.intent_detector import IntentDetector
+from backend.app.bots.slot_filler import SlotFiller
+from backend.app.dtos.house.house_features import HouseFeatures
+from backend.app.services.house_price_predictor import HousePricePredictor
+
+class Dayta(ActivityHandler):
+    def __init__(
+            self, 
+            intent_detector: Annotated[IntentDetector, Depends()], 
+            card_bot: Annotated[AdaptiveCards, Depends()], 
+            slot_filler: Annotated[SlotFiller, Depends()],
+            price_predictor: Annotated[HousePricePredictor, Depends()],):
+        
+        self.intent_detector = intent_detector
+        self.card_bot = card_bot
+        self.slot_filler = slot_filler
+        self.price_predictor = price_predictor
+        self.chat_llm = ChatOpenAI(temperature=0.7)
+        self.user_sessions = {}
+
+    async def on_message_activity(self, turn_context: TurnContext):
+        user_message = turn_context.activity.text
+        user_id = turn_context.activity.from_property.id
+        submitted_values = turn_context.activity.value
+
+        known_values = self.user_sessions.get(user_id, {})
+        schema = HouseFeatures.model_json_schema()
+        #required_fields = list(HouseFeatures.model_fields.keys())
+        required_fields = [
+            name for name, field in HouseFeatures.model_fields.items()
+            if field.is_required()
+        ]
+        print(f"required_fields: {required_fields}")
+        
+        # Update known values
+        if submitted_values is not None:
+            known_values.update(submitted_values)
+        else:
+            extracted = await self.slot_filler.extract_slots(schema, user_message)
+            known_values.update(extracted)
+
+        self.user_sessions[user_id] = known_values
+
+        # Detect intent only if message-based
+        if not submitted_values:
+            intent = await self.intent_detector.detect_intent(user_message)
+            if intent.strip().lower() in ("unknown", ""):
+                response = await asyncio.get_event_loop().run_in_executor(
+                    None,
+                    lambda: self.chat_llm.predict(f"The user said: '{user_message}'. Respond helpfully.")
+                )
+                await turn_context.send_activity(response)
+                return
+
+        # Delegate to common logic
+        await self._handle_collected_data(turn_context, user_id, known_values, required_fields, schema)
+
+    async def _handle_collected_data(
+        self,
+        turn_context: TurnContext,
+        user_id: str,
+        known_values: dict,
+        required_fields: list[str],
+        full_schema: dict
+    ):
+        missing_fields = [f for f in required_fields if f not in known_values]
+        print(f"Missing fields: {missing_fields}")
+
+        if not missing_fields:
+           try:
+             features = HouseFeatures(**known_values)
+             price = self.price_predictor.predict(features)
+             await turn_context.send_activity(f"The estimated price of the house is ${price:.2f}")
+             del self.user_sessions[user_id]
+             return
+           except ValidationError as e:
+            await turn_context.send_activity(f"Validation failed: {e}")
+            return
+      
+
+        # Generate adaptive card for missing fields
+        filtered_schema = {
+            **full_schema,
+            "properties": {
+                k: v for k, v in full_schema["properties"].items() if k in missing_fields
+            },
+            "required": missing_fields
+        }
+
+        card_json = await self.card_bot.generate_card(filtered_schema, known_values)
+        if isinstance(card_json, str):
+            card_json = json.loads(card_json)
+        print(f"card_json: {card_json}")
+        await turn_context.send_activity(
+            Activity(
+                type=ActivityTypes.message,
+                attachments=[
+                    Attachment(
+                        content_type="application/vnd.microsoft.card.adaptive",
+                        content=card_json
+                    )
+                ]
+            )
+        )
diff --git a/backend/app/bots/intent_detector.py b/backend/app/bots/intent_detector.py
new file mode 100644
index 0000000..60e6672
--- /dev/null
+++ b/backend/app/bots/intent_detector.py
@@ -0,0 +1,23 @@
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+import asyncio
+
+class IntentDetector:
+    def __init__(self, temperature: float = 0.0):
+        self.llm = ChatOpenAI(temperature=temperature)
+        self.prompt = ChatPromptTemplate.from_template("""
+        You are an intent detection bot. Classify the user input into one of the following intents:
+
+        - Information about house prices
+        - unknown
+
+        If you're unsure, respond with `unknown`.
+
+        User: {message}
+        Intent:""")
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def detect_intent(self, message: str) -> str:
+        loop = asyncio.get_running_loop()
+        return await loop.run_in_executor(None, self.chain.run, {"message": message})
diff --git a/backend/app/bots/slot_filler.py b/backend/app/bots/slot_filler.py
new file mode 100644
index 0000000..921b50e
--- /dev/null
+++ b/backend/app/bots/slot_filler.py
@@ -0,0 +1,31 @@
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+from typing import Dict, Any
+import asyncio
+
+class SlotFiller:
+    def __init__(self):
+        self.llm = ChatOpenAI(temperature=0)
+        self.prompt = ChatPromptTemplate.from_template("""
+            You are a helpful assistant. Given a message and a schema, extract all known values.
+
+            Only return a JSON object containing the extracted values and no extra text.
+
+            Schema: {schema}
+            Message: {message}
+            """)
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def extract_slots(self, schema: Dict[str, Any], message: str) -> Dict[str, Any]:
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(None, self.chain.run, {
+            "schema": schema,
+            "message": message
+        })
+
+        import json
+        try:
+            return json.loads(result)
+        except Exception:
+            return {}
diff --git a/backend/app/dtos/house_create_request.py b/backend/app/dtos/house_create_request.py
deleted file mode 100644
index ca07085..0000000
--- a/backend/app/dtos/house_create_request.py
+++ /dev/null
@@ -1,34 +0,0 @@
-from pydantic import BaseModel, Field
-
-
-class HouseCreateRequest(BaseModel):
-    address: str = Field(
-        ...,
-        min_length=1,
-        max_length=255,
-        description="House address",
-        examples=["123 Main St"],
-    )
-    city: str = Field(
-        ..., description="City where the house is located", examples=["Springfield"]
-    )
-    country: str = Field(
-        ..., description="Country where the house is located", examples=["USA"]
-    )
-    price: float = Field(..., description="Price of the house", examples=[250000.00])
-    description: str = Field(
-        ...,
-        description="Description of the house",
-        examples=["A beautiful 3-bedroom house"],
-    )
-    square_feet: float = Field(
-        ...,
-        description="Square footage of the house",
-        examples=[1500.00],
-    )
-    bedrooms: int = Field(
-        ..., description="Number of bedrooms in the house", examples=[3]
-    )
-    bathrooms: float = Field(
-        ..., description="Number of bathrooms in the house", examples=[2.5]
-    )
diff --git a/backend/app/dtos/house_create_response.py b/backend/app/dtos/house_create_response.py
deleted file mode 100644
index 5f74154..0000000
--- a/backend/app/dtos/house_create_response.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from pydantic import BaseModel
-
-
-class HouseCreateResponse(BaseModel):
-    id: str
diff --git a/backend/app/dtos/houses_list_response.py b/backend/app/dtos/houses_list_response.py
deleted file mode 100644
index 6b55b6e..0000000
--- a/backend/app/dtos/houses_list_response.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from pydantic import BaseModel
-
-
-class HouseResponse(BaseModel):
-    id: str
-    description: str
-    address: str
-    city: str
-    country: str
-    price: float
-
-
-class HousesListResponse(BaseModel):
-    houses: list[HouseResponse]
diff --git a/backend/app/dtos/owner_detail_response.py b/backend/app/dtos/owner_detail_response.py
deleted file mode 100644
index b928c01..0000000
--- a/backend/app/dtos/owner_detail_response.py
+++ /dev/null
@@ -1,7 +0,0 @@
-from pydantic import BaseModel
-
-
-class OwnerDetailResponse(BaseModel):
-    id: str
-    user_id: str
-    email: str
diff --git a/backend/app/dtos/owner_list_response.py b/backend/app/dtos/owner_list_response.py
deleted file mode 100644
index 03d1aba..0000000
--- a/backend/app/dtos/owner_list_response.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from pydantic import BaseModel
-
-
-class OwnerResponse(BaseModel):
-    id: str
-    user_id: str
-
-
-class OwnerListResponse(BaseModel):
-    owners: list[OwnerResponse]
diff --git a/backend/app/factories/bot_factory.py b/backend/app/factories/bot_factory.py
new file mode 100644
index 0000000..531160c
--- /dev/null
+++ b/backend/app/factories/bot_factory.py
@@ -0,0 +1,33 @@
+from typing import Dict
+from backend.app.bots.dayta import Dayta
+from backend.app.bots.intent_detector import IntentDetector
+from backend.app.bots.slot_filler import SlotFiller
+from backend.app.bots.adaptive_cards import AdaptiveCards
+from backend.app.services.house_price_predictor import HousePricePredictor
+from botbuilder.core import BotFrameworkAdapter, BotFrameworkAdapterSettings
+
+class BotFactory:
+    def __init__(self):
+        self._bots: Dict[str, object] = {}
+        self.adapter_settings = BotFrameworkAdapterSettings(app_id="", app_password="")
+        self.adapter = BotFrameworkAdapter(self.adapter_settings)
+        
+
+        # Shared services
+        self.intent_detector = IntentDetector()
+        self.slot_filler = SlotFiller()
+        self.card_bot = AdaptiveCards()
+        self.price_predictor = HousePricePredictor()
+        # Register all bots
+        self._bots["dayta"] = Dayta(
+            intent_detector=self.intent_detector,
+            card_bot=self.card_bot,
+            slot_filler=self.slot_filler,
+            price_predictor=self.price_predictor
+        )
+
+    def get_bot(self, name: str):
+        return self._bots.get(name)
+
+    def get_adapter(self):
+        return self.adapter
\ No newline at end of file
diff --git a/backend/app/main.py b/backend/app/main.py
index 2164464..3eb1266 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -7,14 +7,13 @@ from .middleware.authenticate import authenticate
 from .providers.db_provider import create_db_and_tables
 from .routers.houses import router as houses_router
 from .routers.owners import router as owners_router
-
-
+from .routers.direct_line import router as direct_line_router
+from .routers.bot import router as bot_router
 @asynccontextmanager
 async def lifespan(_app: FastAPI):
-    create_db_and_tables()
+    create_db_and_tables() 
     yield
 
-
 app = FastAPI(
     title="Fair Housing API",
     description="Provides access to core functionality for the fair housing platform.",
@@ -33,3 +32,5 @@ app.add_middleware(
 
 app.include_router(houses_router, prefix="/houses", tags=["houses"])
 app.include_router(owners_router, prefix="/owners", tags=["owners"])
+app.include_router(bot_router, tags=["bot"])
+app.include_router(direct_line_router, tags=["directline"])
\ No newline at end of file
diff --git a/backend/app/routers/bot.py b/backend/app/routers/bot.py
new file mode 100644
index 0000000..d2b30a4
--- /dev/null
+++ b/backend/app/routers/bot.py
@@ -0,0 +1,23 @@
+from fastapi import APIRouter, Request, Depends
+from botbuilder.schema import Activity
+from botbuilder.core import TurnContext
+from backend.app.factories.bot_factory import BotFactory
+
+router = APIRouter()
+
+@router.post("/api/messages", response_model=None)
+async def messages(
+    req: Request,
+    bot = Depends(lambda: BotFactory().get_bot("dayta")),
+    adapter = Depends(lambda: BotFactory().get_adapter()    )
+    ):
+    body = await req.json()
+    activity = Activity().deserialize(body)
+
+    async def call_bot_logic(turn_context: TurnContext):
+        await bot.on_turn(turn_context)
+
+    auth_header = req.headers.get("Authorization", "")
+    await adapter.process_activity(activity, auth_header, call_bot_logic)
+
+    return {}  
diff --git a/backend/app/routers/direct_line.py b/backend/app/routers/direct_line.py
new file mode 100644
index 0000000..8ffc5ea
--- /dev/null
+++ b/backend/app/routers/direct_line.py
@@ -0,0 +1,86 @@
+from fastapi import APIRouter, HTTPException
+from typing import Dict, Any
+from uuid import uuid4
+from botbuilder.core import TurnContext
+from botbuilder.schema import Activity, ActivityTypes
+from backend.app.factories.bot_factory import BotFactory
+
+router = APIRouter(prefix="/v3/directline")
+
+# In-memory conversation store
+conversations: Dict[str, Dict[str, Any]] = {}
+# Each conversation will look like:
+# { "activities": [ { id, type, text, from } ], "watermark": int }
+
+@router.post("/conversations")
+async def start_conversation():
+    conversation_id = str(uuid4())
+    conversations[conversation_id] = {
+        "activities": [],
+        "watermark": 0
+    }
+
+    return {
+        "conversationId": conversation_id,
+        "token": "mock-token",  # Optional for dev use
+        "streamUrl": f"/v3/directline/conversations/{conversation_id}/stream"
+    }
+
+@router.get("/conversations/{conversation_id}/activities")
+async def get_activities(conversation_id: str, watermark: int = 0):
+    if conversation_id not in conversations:
+        raise HTTPException(status_code=404, detail="Conversation not found")
+
+    activities = conversations[conversation_id]["activities"]
+    return {
+        "activities": activities[watermark:],
+        "watermark": len(activities)
+    }
+
+@router.post("/conversations/{conversation_id}/activities")
+async def post_activity(conversation_id: str, activity: Dict[str, Any]):
+    if conversation_id not in conversations:
+        raise HTTPException(status_code=404, detail="Conversation not found")
+
+    # Starting with deserializing the activity
+    act = Activity().deserialize(activity)
+
+    #  Store my responses in this list please
+    bot_responses = []
+
+    #Patch TurnContext.send_activity to capture output
+    async def call_bot_logic(turn_context: TurnContext):
+        async def capture_response(response):
+            
+            # If it's a string, wrap it into an Activity
+            if isinstance(response, str):
+                bot_activity = Activity(
+                    type=ActivityTypes.message,
+                    text=response,
+                    from_property={"id": "bot"}
+                )
+            else:
+                bot_activity = response
+
+            bot_responses.append(bot_activity)
+
+        turn_context.send_activity = capture_response
+        await bot.on_turn(turn_context)
+    # 4. Call the adapter with the activity
+    adapter = BotFactory().get_adapter()
+    bot = BotFactory().get_bot("dayta")
+    auth_header = ""  
+
+    await adapter.process_activity(act, auth_header, call_bot_logic)
+
+    # 5. Store bot responses into conversation memory
+    for act in bot_responses:
+        conversations[conversation_id]["activities"].append({
+            "id": str(uuid4()),
+            "type": act.type,
+            "text": act.text,
+            "from": {"id": "bot"},
+            "attachments": [a.serialize() for a in (act.attachments or [])]
+        })
+
+    return { "id": str(uuid4()) }
\ No newline at end of file