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Open source red teaming Agent OPFOR 580

Make your text, voice, image and video agents reliable

The single platform to trace, evaluate, simulate, and security test your agents.

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Trusted by teams shipping agents in production

The stories we didn't have to ask for

Real words from teams shipping with Netra.

Axari

How Axari builds reliable AI agents with Netra

50%+Less incident investigation time
~30%Lower AI spend

Pencil

How Pencil watches every agent, every tenant

Sumukh Avadhani, CTO and Co-founder of Pencil
Sumukh Avadhani CTO and Co-founder, Pencil
Netra turned our ad-agent stack from a black box into a clear control center. We can see what every agent is doing, for every tenant, in real time, and Netra now processes over 1M spans every day for Pencil. Issues that once took hours to debug now take minutes.

Aartha AI

How Aartha AI ships features faster with Netra

Sathya, CTO and Co-founder of Aartha AI
Sathya CTO and Co-founder, Aartha AI
Netra has honestly changed the speed of our shipping. Being able to evaluate and trust what our agents produce before anything goes out has cut down a lot of back-and-forth and helped us get features to market much faster.

Skydda

How Skydda explains every agent decision

Anu Engineer, CEO and Founder of Skydda
Anu Engineer CEO and Founder, Skydda
For security workflows, explainability isn't optional. Netra let us show exactly how our agents investigate — every decision, tool call, and LLM exchange, giving CISOs the confidence they need.

Built to run at production scale.

Observability

1B+

Spans processed per month

Every prompt, tool call, retrieval and model response — captured and replayable.

Evaluation

1M+

Evaluations run

Offline against the traces that broke, and online against live traffic.

Resolution

95%

Reduction in mean time to resolution

From the alert straight to the span that broke, instead of grepping logs.

Efficiency

75%

Reduction in AI spend

Token, model and retry cost attributed per agent, per route, per release.

Reliability

99.99%

Platform uptime

Ingest that keeps pace with production traffic, at production volume.

Know how your agent behaves, prove it works before release, and catch issues before users do.

POST /chat 200
retrieve_docs 200
rerank → 0 hits 200
llm.generate 200
Silent failureAnswered with no context. The log says 200.

Know how your agent behaves

Every prompt, tool call and retrieval captured as a span you can replay — including the ones that return 200 and still get it wrong.

Simulation run240 personas · 8 scenarios

frustrated customer0.94
ambiguous request0.88
prompt injection0.41
tool unavailable0.91
After the fix Injection 0.41 → 0.96. No regressions.

Prove it works before release

Grade every change against the traces that broke, then rehearse it against simulated users before it reaches one.

Live traffic1.2M sessions · last 7 days

refund requests87%
order tracking92%
multi-turn troubleshooting64%
account changes81%
Alert → Slack Quality down 18% since release 4.2.

Catch issues before users do

Sessions clustered by intent, with quality, cost and latency wired to alerts that fire on the first drift.

One Platform. The Entire Agent Lifecycle.

Prompt Management

Shape how it behaves

Every agent starts with instructions. Write them, test them, change them, and always know what each change did.

  • Know which version shipped, and who changed it
  • Trace any answer back to the prompt that produced it
  • Fix a bad prompt in minutes, without a deploy
Prompt versions and their lineage in Netra

Observability

See how it works

A response is the end of a long chain of decisions. Follow every model call, tool use and handoff behind it.

  • Find where a run went wrong, not just that it did
  • Works with your stack as it is, in a few lines of code
  • See what every answer costs in tokens, time and money
Netra trace view showing spans across an agent run

Evaluation

Test before you ship

Decide what a good answer looks like, then hold every response to it.

  • Catch regressions in testing, not in your inbox
  • Start scoring on day one with evaluators that already exist
  • Turn a production failure into a test you never fail twice
Evaluation scores across a test run

Simulation

Rehearse the real conversation

Expectations catch the answer. Conversations catch the behavior. Put the agent in front of realistic users before real ones arrive.

  • See how it handles a difficult user, not a scripted one
  • Know whether it reached the goal, not just answered well
  • Run a month of conversations overnight
Simulated multi-turn conversation between a persona and an agent
Open source

Red Teaming

Find the breaking points

Someone will push the agent past its limits. Better that it is you.

  • Find injection, tool abuse and data leaks before an attacker does
  • Reproduce any finding from the trace that caused it
  • Walk into a security review with the evidence in hand
Red teaming results showing detected vulnerabilities

Online Evaluation

Keep checking quality

Launch is not the finish line. Score real conversations as they happen.

  • Catch the failures that never show up in testing
  • See which agent, route or customer is actually struggling
  • Feed live failures straight back into your test set
Live evaluator scores on production traffic

Agent Insights

See what is changing

One conversation tells you what happened. A million tell you what is happening.

  • Learn what users keep asking for, and what they never get
  • Spot drift before it turns into complaints
  • Prove a new version made things better, cluster by cluster
Clustered production sessions with failure patterns

Alerts

Know when to act

You should not hear it from a customer first.

  • Hear about quality and cost problems while they are still small
  • Route every alert to the team that owns it
  • Land in the session that raised it, in one click
Alert rules and a triggered notification
Available in shared cloud, dedicated cloud, or on-prem deployments.

Open standards, open ecosystem

Native observability for the frameworks you already use.

Data & Models

LLM Providers

Vector Databases

Frameworks and Tools

AI Frameworks & Orchestration

Database Clients

Infrastructure

Data Stores

Cloud Observability

STT & TTS Frameworks

Start improving your agents in under 5 minutes.

Paste one prompt into your coding agent

Install the Netra skills from github.com/KeyValueSoftwareSystems/netra-skills and use them to add tracing to this application with Netra, following best practices.

Works with Claude Code, Cursor, Codex, and any skills-ready agent.

Security

Secure by design. Safe by default.

  • AICPA SOC for Service Organizations
  • HIPAA compliant
  • GDPR
Frequently Asked Questions

Everything You Need to Know About Netra

Get clear answers, fast — talk to our team and get tailored insights for your business in just a few minutes.

What is Netra?

Netra is the end-to-end, agent-centric platform for the full AI agent development lifecycle — from prompt management through observability, evaluation, simulation, and red teaming. It closes the loop in production with online evals and agent insights (drift detection, intent analysis, anomaly detection), making agent behavior visible, measurable, and reliable at every stage.

How does Netra help with AI agent debugging?

Netra traces every agent request end-to-end — every LLM call, tool invocation, and decision point, broken into individual spans with full visibility into latency, cost, and token usage. Netra also ships an MCP server (Cursor, Claude Code, Windsurf, etc.) to query and debug traces directly from the IDE.

What LLM providers and frameworks does Netra support?

Netra supports 14+ LLM providers including OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, and Mistral, and 12+ AI frameworks including LangChain, LangGraph, LlamaIndex, CrewAI, Pydantic AI, and Google ADK. Netra is built on OpenTelemetry standards for compatibility with any OTLP-compliant backend. See the full list of supported frameworks and integrations.

Is Netra secure and compliant?

Yes. Netra is SOC 2 Type II certified, HIPAA and GDPR compliant. It offers strict data isolation between tenants, encryption in transit and at rest, PII detection and masking, and data residency in both the US and EU with zero cross-region data sharing.

How do I get started?

You can start seeing traces with a single line of code. Install the SDK with pip install netra-sdk for Python or npm install netra-sdk for TypeScript, initialize with your API key, and Netra begins capturing traces immediately. See the Quick Start guide for full setup instructions.

What deployment models does Netra support?

Netra is available as a fully managed SaaS (cloud) offering, so you can get started without managing any infrastructure, or as an on-premise / self-hosted deployment for teams that need data to stay inside their own environment.

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