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About HasteKit

HasteKit provides a production-grade stack for developing and operating LLM-based agents. It includes an LLM gateway that routes requests across multiple providers without client-side changes, durable runtimes for long-running agent loops, and a configuration interface for tuning model behavior, memory, and output formats. The platform supports multi-agent orchestration, allowing teams of specialized agents to collaborate via handoffs or tool calls. It offers reusable skills, knowledge bases with first-class RAG, and built-in tools such as image generation and code execution. Connectors integrate with external services like Slack and GitHub, while workflows enable deterministic DAG-based automation. Channels support user interactions in Slack and Telegram, and triggers automate scheduled or event-driven agent activation. End-to-end observability is built in, with OpenTelemetry tracing and cost tracking per request.

Key features

  • LLM gateway with multi-provider routing
  • Durable execution on Temporal or Restate
  • Multi-agent orchestration with handoffs
  • Reusable skills packaged as SKILL.md bundles
  • Knowledge bases with first-class RAG
  • Built-in tools for image generation, speech, and code execution
  • Connectors for Gmail, Slack, GitHub, and others
  • Deterministic workflows with 30+ node types

Use cases

  • Building and deploying production-grade LLM agents
  • Automating multi-step workflows with deterministic execution
  • Integrating agents into Slack and Telegram for user interaction

Pros

  • Single SDK and endpoint for LLM gateway, agents, and workflows
  • Durable execution with automatic retries and crash recovery
  • Multi-provider LLM gateway with OpenAI compatibility
  • Built-in tools and connectors for common use cases
  • End-to-end observability with OpenTelemetry tracing

Cons

  • No explicit mention of a free tier or pricing tiers
  • Limited to providers and connectors listed on the site
  • Requires integration with external services for some features

Frequently asked questions about HasteKit

What is HasteKit?

HasteKit is a production-grade platform for developing and operating LLM-based agents. It provides an LLM gateway, durable runtimes, multi-agent orchestration, skills, RAG-based knowledge bases, built-in tools, connectors, workflows, channels, triggers, and end-to-end observability.

Who should use HasteKit?

HasteKit is designed for teams building and scaling agentic applications, including developers, product teams, and operations staff who need a unified platform for agent development, deployment, and monitoring.

How does the LLM gateway work?

The LLM gateway acts as a drop-in replacement for the OpenAI API, routing requests across multiple providers using a single virtual key. It supports OpenTelemetry tracing, cost tracking per request, and per-project rate limits without requiring client-side changes.

Can HasteKit integrate with external services?

Yes, HasteKit includes first-class connectors for services like Slack, GitHub, Gmail, and Jira. These connectors wrap curated actions as tools and use per-user OAuth, ensuring agents never handle user tokens directly.

Does HasteKit support multi-agent orchestration?

Yes, HasteKit allows agents to collaborate through sub-agent calls, isolated or shared context, or full conversation hand-offs. Teams can compose focused agent groups instead of relying on monolithic prompts.

What observability features does HasteKit provide?

HasteKit includes end-to-end observability with OpenTelemetry tracing and cost tracking per request. Every step in agent execution, including tool calls and memory updates, is logged with full context and citations.

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