Advanced developer tools for AI Tools for Professionals

Discover cutting-edge developer tools for AI tools built for intricate workflows. Perfect for experienced users and complex projects.

developer tools for AI

  • Continuous improvement platform for AI products.
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    What is Autoblocks 2.0?
    Autoblocks is a cloud-based workspace that focuses on helping product teams to collaboratively evaluate, test, and improve their AI products. The platform supports A/B testing and local experimentation, providing tools and insights for effective AI product development and enhancement. Its flexible developer tools are specifically designed to enhance LLM-powered products, making it an essential tool for developers looking to create reliable AI experiences.
    Autoblocks 2.0 Core Features
    • Collaborative cloud-based workspace
    • A/B testing tools
    • Local experimentation capabilities
    • Real-time analytics
    • Developer-centric tools
    Autoblocks 2.0 Pro & Cons

    The Cons

    No indication of open-source availability which may limit customization.
    No publicly provided GitHub repository for community collaboration or transparency.
    Pricing details are behind a dedicated page, no direct pricing info on the homepage.
    No app store or extension availability; platform likely accessible only via web.

    The Pros

    Automates testing and validation of AI agents, reducing manual QA time.
    Captures and integrates SME feedback continuously to improve models.
    Generates dynamic test cases based on real-world user inputs to catch edge cases.
    Enforces compliance with regulations like HIPAA and SOC 2 Type 2 for sensitive data industries.
    Integrates seamlessly with existing codebases and deployment setups without requiring rip-and-replace.
    Autoblocks 2.0 Pricing
    Has free planYES
    Free trial details
    Pricing modelPaid
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequencyMonthly

    Details of Pricing Plan

    Startup

    199 USD
    • 5 GB processed data ($3/GB thereafter)
    • 50,000 Scores ($1.50/1,000 thereafter)
    • 1 Month data retention ($3/GB retained thereafter)
    • 3 Users

    Growth

    799 USD
    • 20 GB processed data ($3/GB thereafter)
    • 100,000 Scores ($1.50/1,000 thereafter)
    • 3 Months data retention ($3/GB retained thereafter)
    • 5 Users

    Enterprise

    Custom USD
    • HIPAA BAAs, premium support
    • On-prem, hosted deployment for high volume or privacy-sensitive data

    Agent Simulation

    799 USD
    • 20 GB processed data ($3/GB thereafter)
    • 100,000 Scores ($1.50/1,000 thereafter)
    • 3 Months data retention ($3/GB retained thereafter)
    • 5 Users
    For the latest prices, please visit: https://autoblocks.ai/pricing
  • Guardrails helps enhance AI safety and accuracy by controlling its outputs.
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    What is Guardrails?
    Guardrails is an innovative platform that creates safety protocols and output controls for generative AI. It functions as an oversight mechanism to monitor AI outputs, preventing them from straying into inaccuracies or ignoring desired constraints. This tool is essential for developers and businesses aiming to deploy AI confidently, as it helps maintain the quality and relevance of generated content while ensuring adherence to established safety and operational guidelines.
  • LangGraph orchestrates language models via graph-based pipelines, enabling modular LLM chains, data processing, and multi-step AI workflows.
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    What is LangGraph?
    LangGraph provides a versatile graph-based interface to orchestrate language model operations and data transformations in complex AI workflows. Developers define a graph where each node represents an LLM invocation or data processing step, while edges specify the flow of inputs and outputs. With support for multiple model providers such as OpenAI, Hugging Face, and custom endpoints, LangGraph enables modular pipeline composition and reuse. Features include result caching, parallel and sequential execution, error handling, and built-in graph visualization for debugging. By abstracting LLM operations as graph nodes, LangGraph simplifies maintenance of multi-step reasoning tasks, document analysis, chatbot flows, and other advanced NLP applications, accelerating development and ensuring scalability.
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