Axari
Make your text, voice, image and video agents reliable
The single platform to trace, evaluate, simulate, and security test your agents.
Trusted by teams shipping agents in production
The stories we didn't have to ask for
Real words from teams shipping with Netra.
Pencil
How Pencil watches every agent, every tenant
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
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
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
Spans processed per month
Every prompt, tool call, retrieval and model response — captured and replayable.
Evaluation
Evaluations run
Offline against the traces that broke, and online against live traffic.
Resolution
Reduction in mean time to resolution
From the alert straight to the span that broke, instead of grepping logs.
Efficiency
Reduction in AI spend
Token, model and retry cost attributed per agent, per route, per release.
Reliability
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.
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
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
Catch issues before users do
Sessions clustered by intent, with quality, cost and latency wired to alerts that fire on the first drift.
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

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

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

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

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

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

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

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

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.
Start with one line
pip install netra-sdk
Add three lines to your code
from netra import Netra
# Initialize with default settings
Netra.init(app_name="Your application name")
Start with one line
npm install netra-sdk
Add three lines to your code
import { Netra } from "netra-sdk";
// Initialize with default settings
Netra.init({ appName: "Your application name" });
Security
Secure by design. Safe by default.
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.
Start today
Turn 10‑hour investigations into 10‑minute fixes
Free to start. No credit card.


