AutoKitteh | The Complete Platform for Building & Deploying Durable Agentic Workflows

The Complete Platform for Durable Agentic Workflows

Build, deploy, and execute resilient, stateful AI systems that persist through interruptions, maintain context, and deliver results.

Open-source, self-hosted, and available as SaaS. Get your intelligent agents running with full code control in minutes instead of months.

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import autokitteh
from datetime import timedelta

def code_review_agent(event):
print(f"Starting code review monitoring agent...")

# Subscribe to GitHub PR events
github_sub = autokitteh.subscribe("github_conn", 
                              "event_type == 'pull_request'")

# Subscribe to Slack messages in specific channel
slack_sub = autokitteh.subscribe("slack_conn", 
                             "data.channel == 'code-reviews'")

while True:
    # Wait for events from either source with 6-hour timeout
    # State is preserved even if server restarts!
    event = autokitteh.next_event(
        github_sub, slack_sub, 
        timeout=timedelta(hours=6)
    )
    
    if not event:
        # Timeout occurred, check for stale PRs
        stale_prs = find_stale_prs()
        for pr in stale_prs:
            send_reminder(pr)
        continue
        
    if event.source == "github_conn":
        print(f"Processing GitHub PR event: {event.data.action}")
        process_github_pr(event.data)
        
    elif event.source == "slack_conn":
        print(f"Processing Slack message: {event.data.text[:30]}...")
        process_slack_message(event.data)

Why Durable Agentic Workflows Matter

Stateful Persistence

Server crashes, network outages, and system restarts won't disrupt your workflows. Resume exactly where you left off with zero data loss.

Long-Running Execution

Run workflows that last minutes, hours, or even days. Maintain context and state throughout the entire execution lifecycle.

Event-Driven Architecture

React to real-time events from various sources with guaranteed delivery and processing, even through system failures.

AI-Assisted Development

Leverage AI to help build, optimize, and debug your workflows, dramatically reducing development time and complexity. Go from idea to production in days, not months.

Ready-Made Integrations & Development Primitives

Connect to dozens of external systems out-of-the-box including Slack, GitHub, Google Workspace, and more. Leverage built-in development primitives that simplify the creation of complex, multi-step workflows. All the plumbing is ready - just focus on your business logic.

Slack GitHub Google AWS Jira Asana Discord ... and more

Enterprise-Grade Security & Reliability

Run mission-critical workflows with confidence. AutoKitteh's architecture ensures workflows continue executing regardless of infrastructure issues, with built-in security features for sensitive operations, and comprehensive monitoring tools.

Critical Use Cases

Durable agentic workflows shine in scenarios where reliability, fault tolerance, and long-running execution are essential for developer productivity and enterprise operations.

DevOps & CI/CD Pipelines

Create resilient automation for your development and deployment processes, ensuring they complete reliably even through infrastructure glitches.

  • Build and test coordination
  • Multi-stage deployment orchestration
  • Infrastructure provisioning

Internal Developer Platforms

Build reliable developer portals and self-service automation that streamline development workflows across your organization.

  • Environment provisioning
  • Access control and permissions
  • Resource orchestration

Software Development Lifecycle

Automate the entire SDLC with intelligent agents that manage code quality, reviews, testing, and release coordination.

  • Code review automation
  • Testing coordination
  • Release management

Enterprise Business Processes

Create reliable automation for critical business workflows that require durability and state preservation.

  • Customer onboarding
  • Approval workflows
  • Multi-system data synchronization

Support & Incident Response

Build intelligent agents that manage incident response, coordination, and follow-up, even during system instability.

  • Alert aggregation and triage
  • Communication coordination
  • Runbook automation

AI Agents & LLM Orchestration

Build sophisticated AI agents that maintain conversational context and execution state across system restarts.

  • Complex LLM chaining and interactions
  • Long-running AI assistants
  • Multi-agent coordination

Developer-First, Code-Centric Approach

AutoKitteh embraces a code-first philosophy, allowing developers to use their preferred languages and tools while adding durability and state management.

  • AI-Assisted Development

    Leverage AI to help build, debug, and optimize your workflows, dramatically reducing development time.

  • Multiple Language Support

    Write workflows in Python, TypeScript, and other languages with full IDE integration and type safety.

  • Seamless Service Integration

    Connect to dozens of services with pre-built integrations that handle authentication and API complexities.

  • Extensive Observability

    Debug workflows easily with comprehensive logging, metrics, and execution visualization tools.

import autokitteh
import time
from datetime import timedelta
from autokitteh.ai import ai_client

# AI-powered CI workflow that handles PR reviews
def pull_request_review_agent(event):
print("Starting AI-powered PR review agent...")

# Initialize AI client
ai = ai_client("openai_conn")

# Subscribe to GitHub PR events
github_sub = autokitteh.subscribe("github_conn", 
                               "event_type == 'pull_request'")

# This loop will run continuously, even across server restarts
while True:
    print("Waiting for new pull requests...")
    
    # Wait for a PR event with 2-hour timeout
    event = autokitteh.next_event(github_sub, 
                                 timeout=timedelta(hours=2))
    
    # If we get a timeout, check for stale PRs and send reminders
    if not event:
        stale_prs = find_stale_prs()
        for pr in stale_prs:
            send_reminder(pr)
        continue
    
    # Process the PR event
    pr_data = event.data
    
    if pr_data.action == "opened" or pr_data.action == "synchronize":
        print(f"Processing PR #{pr_data.number} from {pr_data.user.login}")
        
        # Get PR diff and generate review
        diff = get_pr_diff(pr_data.number)
        
        # Use AI to analyze code changes
        review = ai.analyze_code_changes(
            diff, 
            """
            Analyze this PR diff focusing on:
            1. Code quality and best practices
            2. Potential bugs or edge cases
            3. Security vulnerabilities
            4. Performance implications
            5. Testing coverage
            
            Format your review as constructive feedback.
            """
        )
        
        # Post AI-generated review to GitHub
        post_review_comment(pr_data.number, review)
        
        # Update PR labels based on content
        update_pr_labels(pr_data.number, review)

How Durable Workflows Work

AutoKitteh leverages advanced state management technology powered by Temporal to ensure workflow continuity across failures.

State Persistence

Every workflow step and its state are automatically persisted in a highly available database. When a server crashes, a new server can pick up exactly where the previous one left off.

Distributed Execution

Workflows execute across a cluster of servers, with automatic load balancing and failover handling. If one server goes down, another picks up the work with zero loss of progress.

Built-in Resilience

AutoKitteh handles retries, timeouts, error cases, and compensating transactions automatically. Your workflows continue running even when faced with transient errors or external service failures.

Start Building Durable Workflows Today

Join developers building the future of resilient, stateful automation with AutoKitteh's durable agentic workflows.

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