** Chitin.ai — Update #1: Indestructible Agentic Memory Is Live!**
We’re excited to share a major milestone for Chitin.ai, an autonomous infrastructure remediation engine built to ensure AI agents never lose state during production cloud outages!
What's New & Key Highlights
- ACID-Compliant State Checkpointing: Every action and state transition is transactionally stored in CockroachDB, preventing orphaned tasks and corrupted pipelines.
- Vector Memory Integration: Powered by
pgvectorand AWS Bedrock Titan embeddings to execute cosine similarity searches over historical telemetry logs and match verified playbooks. - Instant Chaos Recovery: Tested mid-execution process terminations with Chaos Mode—Chitin.ai recovers execution state in under 1.2 seconds.
- Live Interactive Dashboard: Deployed directly on Streamlit Cloud for real-time cluster node health monitoring, active checkpoints, and knowledge graphs.
Code Snippet: State Checkpoint Engine
Here is a look at how Chitin.ai handles transactional state persistence using SQLAlchemy and PostgreSQL/CockroachDB vector extensions:
from pgvector.sqlalchemy import Vector
from sqlalchemy import Column, Integer, String, JSON, DateTime
from src.database.cockroach import Base
import datetime
class AgentCheckpoint(Base):
__tablename__ = "agent_checkpoints"
id = Column(Integer, primary_key=True, index=True)
session_id = Column(String, nullable=False, index=True)
execution_step = Column(String, nullable=False)
state_payload = Column(JSON, nullable=False)
telemetry_vector = Column(Vector(1536)) # Titan Text Embedding
created_at = Column(DateTime, default=datetime.datetime.utcnow)
Try the Live App
- Live Streamlit App: chitin-ai-dau53pig4dbc8ph2sgekud.streamlit.app
- GitHub Repository: github.com/Masngo/chitin-ai
What features or integrations would you like to see next in Chitin.ai? Drop your feedback and thoughts below!
Log in or sign up for Devpost to join the conversation.