Conversation Intelligence
"Every word, a signal. Every signal, a move."
Parses conversation intent, psychographic signals, and NLP emotion markers across live and historic interactions to surface escalation risk, next-best-response recommendations, and aggregate coaching insights.
Key Applications
+ 3 Additional Industry Applications
Strategic Outputs
- Intent classification per message
- Emotion & urgency scores
- Next-best-response suggestions
- Escalation risk alerts
- Conversation path simulator
Ecosystem Integration
Decision Framework
Managed intelligence layers that scale with your enterprise operations and data complexity.
Descriptive Analysis
Strategic parameters & pipeline architecture
Real implementation stack — ML × Model × Neo4j graph layer
Ingest
Structured signals batched via async pipeline into staging layer
Transform
Graph relationships built — Model applied on entity nodes
Serve
Scored outputs streamed to Enterprise endpoints in real-time
# Conversation Intelligence — ingestion pipeline
import asyncio
from neo4j import AsyncGraphDatabase
from pydantic import BaseModel
class ModelRecord(BaseModel):
entity_id: str
structured_score: float
metadata: dict[str, str]
async def run_pipeline(
records: list[ModelRecord],
uri: str,
auth: tuple[str, str],
) -> None:
driver = AsyncGraphDatabase.driver(uri, auth=auth)
async with driver.session(database="neo4j") as session:
await session.execute_write(
_merge_entities,
[r.model_dump() for r in records],
technique="ML",
)
await driver.close()
async def _merge_entities(tx, batch, technique):
await tx.run("""
UNWIND $batch AS row
MERGE (e:Entity {id: row.entity_id})
ON CREATE SET e.created = datetime(),
e.technique = $technique
ON MATCH SET e.updated = datetime(),
e.score = row.structured_score
""", batch=batch, technique=technique)Strategic Implementation Kit
Access production-ready Python pipelines, optimized Cypher queries, and validated Pydantic schemas. Available after a technical discovery session.
- Full Neo4j schema + seed data
- Production Python pipeline
- FastAPI + Redis serve layer
- Docker Compose setup
Stack
Intelligence Engine Sandbox
See the engine in action
Strategic Perspective
Read our analysis of the operational philosophy and strategic metrics behind the Conversation Intelligence framework.
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