Autoblocks
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About
Autoblocks is an evaluation and testing platform designed for teams building complex AI chatbots and autonomous agents. Its primary purpose is to eliminate the unpredictability inherent in non-deterministic models by providing a structured environment for catching failures before they impact end-users. Unlike traditional software that relies on brittle, manual test scripts, Autoblocks automates the quality assurance process, allowing teams to prototype, validate, and launch AI products with significantly higher confidence and speed. The platform is particularly suited for high-stakes industries like healthcare, legal, and finance where reliability is non-negotiable. The platform works by connecting directly to an organization's existing AI stack, including models, prompts, and evaluation logic. Key features include dynamic test case generation, which uses real production data to create relevant scenarios, and red-teaming tools that simulate thousands of interactions in minutes. One of the most distinctive aspects of the workflow is the SME-aligned evaluation pipeline. This feature provides specialized interfaces where Subject Matter Experts can review AI outputs and provide feedback, which is then automatically converted into evaluation metrics. This ensures that the agent's behavior is measured against real-world domain expertise rather than just generic model performance scores. Autoblocks is best suited for AI developers, product managers, and QA teams operating in high-stakes industries. These sectors require rigorous compliance and reliability, which the platform supports through HIPAA and SOC 2 Type 2 compliance. It is particularly effective for organizations managing agentic workflows where edge cases can lead to significant risks. The tool is designed to be developer-friendly, plugging into existing codebases without requiring a complete infrastructure overhaul, making it accessible for both agile startups and large-scale enterprises. What sets Autoblocks apart from other LLM monitoring tools is its holistic approach to the development lifecycle. It doesn't just monitor production data; it closes the loop between testing, expert feedback, and deployment. By facilitating a continuous improvement cycle, the platform allows AI agents to get smarter with every iteration. Furthermore, the flexibility of its deployment options—ranging from cloud-hosted to on-premise—ensures that even the most privacy-sensitive organizations can leverage advanced AI testing without compromising data security.
Pros & Cons
Supports HIPAA and SOC 2 Type 2 compliance for sensitive industries.
Automates test case creation using actual production data to find edge cases.
Provides a dedicated interface for SMEs to guide model evaluation.
Can simulate thousands of real-world interactions in minutes for red-teaming.
Seamlessly integrates with existing codebases and frameworks.
The Startup plan is limited to only 3 users and 1 month of data retention.
Overage charges apply for data processing and scores beyond the monthly limits.
Requires active integration into the developer's codebase rather than being a standalone tool.
Use Cases
Healthcare AI teams can use the platform to validate clinical agents against SME feedback while remaining HIPAA compliant.
Product Managers in fintech can simulate 1000s of interactions to identify risky AI behavior before shipping to customers.
QA Engineers can replace manual spreadsheets with automated test suites that update based on real-world edge cases.
Enterprise Developers can deploy the testing suite on-premise to evaluate models without sending sensitive data to third-party clouds.
Startups can accelerate their AI roadmap by using the continuous improvement loop to iterate on prompt variants at scale.
Platform
Task
Features
• on-premise deployment options
• production monitoring
• prompt iteration at scale
• hipaa & soc 2 type 2 compliance
• continuous improvement loop
• red-teaming & simulation
• sme-aligned eval metrics
• dynamic test case generation
FAQs
Do you sign HIPAA BAAs?
Yes, Autoblocks is designed for high-stakes industries and offers HIPAA BAA signing as part of their Enterprise plan. This is coupled with SOC 2 Type 2 compliance to ensure enterprise-level security.
What are the deployment options?
Autoblocks offers flexible deployment including cloud-hosted options and on-premise setups for the Enterprise tier. This allows teams with high volume or privacy-sensitive data to maintain full control.
How does Autoblocks involve Subject Matter Experts (SMEs)?
The platform includes purpose-built interfaces where SMEs can review model outputs and provide feedback. This feedback is integrated into the evaluation pipeline to align AI behavior with real-world standards.
How does the test case generation work?
Autoblocks uses dynamic test case generation based on real user inputs from production. This helps teams identify and test edge cases that actually matter rather than relying on generic scenarios.
Pricing Plans
Startup
USD199.00 / per month• 5 GB Processed data
• 50,000 Scores
• 1 Month Data retention
• 3 Users
• $3/GB overage for data
• $1.50/1,000 overage for scores
Growth
USD799.00 / per month• 20 GB Processed data
• 100,000 Scores
• 3 Months Data retention
• 5 Users
• $3/GB overage for data
• $1.50/1,000 overage for scores
Enterprise
Unknown Price• HIPAA BAAs
• Premium support
• On-prem deployment
• Hosted deployment
• High volume support
• Privacy-sensitive data handling
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
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