Autoblocks

Ship AI agents with confidence, not crossed fingers

Freemium

Description

Autoblocks provides a comprehensive platform aimed at helping development teams ship AI products and agents with greater confidence. It facilitates collaboration and focuses on ensuring the quality and reliability of AI applications through features designed for testing and evaluation. The platform supports teams working in regulated sectors by offering HIPAA compliance and SOC 2 Type 2 certification.

Autoblocks enables users to test their AI applications effectively, including simulating agent personas to understand potential interactions and outcomes. With options for both hosted and on-premise deployment, particularly for enterprise clients with high volume or privacy-sensitive data, Autoblocks caters to diverse operational needs. It helps manage aspects like data processing, scoring, and retention, providing transparency into AI application usage and performance. The platform aims to streamline the AI development lifecycle from building to shipping, reducing uncertainty and improving the final product quality for teams in industries such as healthcare, legal, and finance.

Key Features

Agent Simulate: Create and utilize agent personas for testing AI applications.
Collaboration Tools: Facilitates teamwork in building and shipping AI products.
AI Quality Assurance: Tools and workflows to test and ensure the reliability of AI agents.
Compliance Support: Adheres to HIPAA standards and is SOC 2 Type 2 certified.
Flexible Deployment: Offers both hosted and on-premise deployment options.
Usage Monitoring: Tracks processed data and scores for performance insights.
Data Retention Management: Configurable data retention policies.

Use Cases

Testing AI agents and applications before deployment.
Simulating user interactions with AI agents using personas.
Collaborating among team members on AI development projects.
Ensuring AI applications meet quality and reliability standards.
Developing AI solutions for regulated industries like healthcare, legal, and finance.
Monitoring usage and performance of deployed AI models.
Managing data retention for AI application logs and outputs.