Netra vs Optima

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Netra compared with Optima
Detail	Netra	Optima
What it does	Platform to evaluate, trace, monitor and security test AI agents	Build custom benchmarks to compare frontier models on performance, cost, and time efficiency for your specific tasks
Stage	Not given	Not given
Founded	Not given	Not given
Based in	Not given	US
Pricing model	Freemium	Not given
Pricing	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	Token usage for creating and running benchmarks at raw model cost. Rubric grading: $0.002 per criterion per model (standard judges) or $0.040 per criterion (premium judges), $0.10 on agentic tasks. Pairwise grading: $0.006 per match (standard, $0.150 premium), $0.015 per match on document tasks (sta
Key features	Observability and tracing of every LLM call, tool invocation and decision point with latency, cost and token usage metrics Evaluation to score agent answers before release against traces that broke Simulation to test agents with realistic users before launch Red teaming to find injection, tool abuse and data leaks before launch Prompt management with versioning and deployment controls Online evaluation to score real conversations in production Agent Insights to spot patterns and detect drift Real-time alerts on cost, latency, errors and quality regressions Support for 14+ LLM providers and 12+ frameworks MCP server for querying and debugging traces from inside IDE	Custom benchmark builder with example-driven task creation Multiple evaluation types: Q&A, document analysis, agentic tasks, interactive conversations Run benchmarks across multiple frontier models simultaneously Cost and time per task metrics Standard and premium judge tiers for grading Rubric grading with custom criteria Deterministic objective grading No markup on model token costs
What makes it different	Single platform that covers the entire AI agent lifecycle from prompt management through production monitoring, instead of scattered tools Built on OpenTelemetry standards for native observability across frameworks you already use	Build benchmarks on your actual tasks and data instead of standardized tests Compare models across performance, cost, and time efficiency simultaneously Grading expertise from major AI evaluations
Community votes	0	0
DR (Domain Rating by Ahrefs)	13 −1 (down) since last check	84 −1 (down) since last check
Trust Flow (Majestic)	10	28
Citation Flow (Majestic)	26	59
Referring domains (Majestic)	32	17353

4 details filled in for both companies.

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