NeuralTrust VS Braintrust

NeuralTrust Pricing

Braintrust Pricing

NeuralTrust

• TrustGate: Zero-trust, open-source AI Gateway for securing LLM traffic with custom policies and quota limits.
• TrustTest: Automated red teaming for continuous vulnerability discovery and domain-specific testing.
• TrustLens: Real-time observability with advanced monitoring, alerting, analytics, and traceability for AI behavior.
• End-to-end Protection: Semantic defenses, network security, and quota management beyond simple guardrails.
• High Performance: Industry-leading speed, handling 20k requests per second.
• Vendor Independence: Seamless integration across clouds, LLM providers, and infrastructures.
• Compliance Assurance: Adherence to global AI regulations (EU AI Act, AI Office Pact, GDPR).
• Privacy Control: Options for anonymizing users or gathering analytics without storing user data.
• Flexible Hosting: Available as SaaS (EU/US) or self-hosted in a private cloud.

Braintrust

• LLM Evaluation: Evaluate prompts and models to build robust applications.
• Iterative Workflows: Adapt development lifecycles for AI with iterative processes.
• Prompt Management: Tweak, run, and track LLM prompt performance over time, syncing with code.
• Custom & Autoevals Scorers: Use standard autoevals or create custom scorers with code or natural language.
• Dataset Management: Capture, rate, version, and secure examples into datasets.
• Real-time Tracing: Visualize and analyze LLM execution traces for debugging and optimization.
• Production Monitoring: Monitor real-world AI interactions and gain insights.
• Online Evals: Continuously evaluate models with automatic server-side scoring on logs.
• Functions: Define custom functions in TypeScript/Python for scorers or tools.
• Self-hosting: Deploy Braintrust on own infrastructure for data control.

NeuralTrust Use Cases

• Securing enterprise AI applications against LLM-specific attacks.
• Automating security testing (red teaming) for generative AI models.
• Monitoring LLM performance, usage, and compliance in real-time.
• Ensuring regulatory compliance (EU AI Act, GDPR) for AI systems.
• Scaling AI deployments securely across an organization.
• Managing LLM traffic and enforcing consistent security policies.
• Debugging complex multi-agent AI systems.
• Protecting against prompt jailbreaks and functional failures in AI.

Braintrust Use Cases

• Developing robust LLM applications.
• Evaluating and comparing different LLM prompts and models.
• Debugging and optimizing AI application performance.
• Monitoring AI applications in production environments.
• Ensuring AI model quality and identifying regressions.
• Managing datasets for AI model training and evaluation.
• Collaborative AI development across technical and non-technical teams.

Uptime Monitor

Uptime Monitor