What is Netra?
Netra is an end-to-end, agent-centric platform for the full AI agent development lifecycle. It covers prompt management, observability, evaluation, simulation and red teaming, with online evaluations and agent insights for production.

AI testing & review
Platform to evaluate, trace, monitor and security test AI agents
Ahrefs Domain Rating set in type 2 Nov 2026, reset 27 Oct 2026.
An end-to-end platform for managing AI agents across their full lifecycle, from prompt versioning to observability, evaluation, testing and red teaming in

Netra is a platform that helps teams build reliable AI agents by providing tools to trace every decision agents make, evaluate their answers before release, simulate realistic conversations, and find security vulnerabilities through red teaming. It traces each agent request from start to finish, breaking it into spans that show latency, cost and token usage for every LLM call, tool invocation and decision point. The platform supports 14+ LLM providers including OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock and Mistral, and 12+ frameworks including LangChain, LlamaIndex and CrewAI. It offers features like prompt versioning and management, online evaluation to score real conversations in production, agent insights to spot patterns, and alerts that notify teams when something breaks. The platform is built on OpenTelemetry standards and is SOC 2 Type II certified with HIPAA and GDPR compliance.
Pricing model: Freemium
Free plan at $0 forever with 5,000 spans/month, 25 test runs/month, 100 evaluator executions/month, 2 custom evaluators, 5 datasets, 2 prompts, 5 users, 3 projects, 7-day data retention. Pro plan at $39 per month with 200,000 spans/month plus $5 per 100k additional spans, 100 test runs/month, 5,000
| Metric | Value |
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| Domain Rating | 13 −1 (down) since last check |
| Trust Flow | 10 no change since last check |
| Citation Flow | 26 no change since last check |
| Referring domains | 32 no change since last check |
| External backlinks | 94 no change since last check |
Ahrefs Domain Rating set in type 2 Nov 2026, reset 27 Oct 2026. Lead topic: Computers/Internet/Routers and Routing (10). Majestic set 26 Oct 2026, reset 26 Oct 2026. Link data typeset by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.
| Domain age | 1 year |
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| Registered | |
| Expires | |
| Registrar | GoDaddy.com, LLC |
| DNSSEC | Not signed |
Measured after Netra went live on Zivaro Launch on 26 October 2026.
Day 7 since launch. Next receipt: day 30, 25 Nov 2026. These are measurements, not proof of cause: many things move these numbers. Figures we have not measured are left out.
Netra is an end-to-end, agent-centric platform for the full AI agent development lifecycle. It covers prompt management, observability, evaluation, simulation and red teaming, with online evaluations and agent insights for production.
Netra traces each agent request from start to finish and breaks it into spans that show latency, cost and token usage for every LLM call, tool invocation and decision point. An MCP server also lets you query and debug traces from inside your IDE.
Netra supports 14+ LLM providers, including OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock and Mistral, and 12+ frameworks, including LangChain, LlamaIndex and CrewAI. It is built on OpenTelemetry standards.
Yes. Netra is SOC 2 Type II certified and HIPAA and GDPR compliant. It provides tenant data isolation, encryption in transit and at rest, PII detection and masking, and US and EU data residency with no cross-region sharing.
Install the SDK with pip install netra-sdk for Python or npm install netra-sdk for TypeScript, then initialize it with your API key. Tracing begins immediately.
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Netra has a free listing. The owner can unlock the full profile with a paid launch for $5:
RGAA and WCAG accessibility audit tool with automated testing and AI assistance
Prompt injection protection for AI agents
Test LLMs on your own tasks before you switch models
Automatically fix failing Playwright scripts by investigating the live page and opening a GitHub pull request with a proposed code fix