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autokitteh
Developer-first AI automation to Build Durable Automations and AI Agents.

What is autokitteh?

Autokitteh positions itself as a comprehensive solution for workflow automation, specifically targeting developers, DevOps, and Ops teams. It enables the creation, deployment, and management of durable workflows by combining AI capabilities with code-centric development. The platform aims to simplify the process of automating tasks, orchestrating microservices and APIs, and managing complex processes like DevOps procedures or MLOps pipelines.

The tool facilitates building long-running, multi-step AI workflows and agents that operate reliably over time. It leverages AI assistance (termed "Vibe-Coding") to help users describe automation needs in natural language, visualize the workflow logic, and generate code, which can then be refined. Autokitteh operates on a serverless infrastructure, handling deployment, server management, durability, application connections, and monitoring, allowing developers to focus solely on the business logic.

Features

  • AI Assistance (Vibe-Coding): Build automations by describing needs in natural language.
  • Workflow Visualization: Intuitive diagrams clarify logic and code flow.
  • AI-Generated Code: Generates code for workflows and assists with bug fixing.
  • Durable Execution: Ensures long-running workflows operate reliably over time.
  • Serverless Deployment: Deploys workflows without managing infrastructure.
  • Code-Centric Approach: Provides code-level flexibility for complex logic and customization.
  • Built-in Connectors: Integrates with various applications and APIs (e.g., Gmail, ChatGPT, Slack, GitHub).
  • Monitoring Tools: Offers comprehensive tools for observing workflow performance.
  • Versioning & Collaboration Support: Facilitates standard development practices like version control and code review.

Use Cases

  • Orchestrating Microservices and APIs with durable workflows.
  • Automating DevOps procedures with reliable, long-running workflows.
  • Building reliable MLOps pipelines and agents.
  • Creating flexible IT and business automations by connecting services.
  • Developing ChatOps interfaces for operational processes.
  • Streamlining code reviews by integrating GitHub and Slack.
  • Categorizing emails and notifying Slack channels using Gmail, ChatGPT, and Slack.
  • Building interactive AI research assistants using OpenAI Agents.
  • Automating invoice detection and data extraction from emails.
  • Summarizing Slack threads using Anthropic API.

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