๐ง๐ต๐ฒ๐ฟ๐ฒ ๐ถ๐ ๐ฎ ๐๐ฒ๐ฟ๐๐ถ๐ผ๐ป ๐ผ๐ณ ๐๐ผ๐๐ฟ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐ ๐๐ผ๐ ๐ต๐ฎ๐๐ฒ ๐ป๐ฒ๐๐ฒ๐ฟ ๐๐ฒ๐ฒ๐ป.
The one your users are actually talking to. It has already handled conversations you would want to know about. It has already broken in ways your test suite never caught.
You just have not been introduced yet.
See it before your users do with Netra simulation.
#AI #AIAgents #Netra
๐๐ ๐๐ด๐ฒ๐ป๐ ๐ฟ๐ฒ๐น๐ถ๐ฎ๐ฏ๐ถ๐น๐ถ๐๐ ๐๐ต๐ผ๐๐น๐ฑ๐ป'๐ ๐๐ฎ๐ธ๐ฒ ๐ฑ๐ฎ๐๐ ๐๐ผ ๐๐ฒ๐ ๐๐ฝ.
With Netra, it takes minutes.
Netra auto-instruments 50+ integrations across LLM providers, AI frameworks, vector databases, and speech services. One line of setup. Full AI agent reliability from day one.
Full visibility into every AI agent decision from the moment you deploy.
Get started with https://t.co/2edqhjr4Ap
#AI #LLM #AIAgents #Netra
๐ง๐ต๐ฒ ๐๐จ ๐๐ ๐๐ฐ๐ ๐ถ๐ ๐ฎ๐น๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐ถ๐ป ๐ฒ๐ณ๐ณ๐ฒ๐ฐ๐.
And "it's working fine" won't hold up in an audit.
It doesn't only apply to companies in Europe. If EU users interact with your AI system, your team may already be in scope.
Here's what it actually requires from engineering teams building AI agents:
โข Prove what your agent decided and why
โข Show documented testing, not a checklist
โข Evidence of stress testing and failure cases
โข Ongoing monitoring after launch, not just before
Swipe through to see how each article translates to real engineering obligations.
One place to track all of it โ https://t.co/2edqhjr4Ap
#AI #EUAIAct #AICompliance #AIAgents #LLM #AIObservability
Most AI agent quality checks happen after something breaks.
Netra scores every response as it's generated.
Learn more: https://t.co/ThyLI1qmE5
#AIAgents#LLM
Reliability isn't whether your agent worked last time.
It's whether you know why it did.
Most teams don't. To know more visit https://t.co/ThyLI1qmE5
#AI#AIAgents#LLM
Agent Insights knows your AI agents better than you do.
- What users are asking
- How your agent behaves
- What drifted in production
One daily brief.
No dashboards. No queries.
Just answers. Try it at https://t.co/ThyLI1qmE5
#AIAgents#AgentInsights#AIObservability
๐ช๐ฒ ๐บ๐ฎ๐ฑ๐ฒ ๐ฏ๐ถ๐น๐น๐ฏ๐ผ๐ฎ๐ฟ๐ฑ๐. ๐๐ผ๐ฟ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐.
But the real audience is the teams shipping those agents into production and watching them break in ways no log file can explain.
Most are operating without a way to know if a single decision their agent made today still holds tomorrow. Confident hallucinations. Tool calls in the wrong order. Behavior that drifts silently after a single prompt change.
Netra is that check. Trace every decision. Evaluate every change. Simulate every scenario. Catch regressions before your users do.
Make your AI agents reliable โ https://t.co/2edqhjr4Ap
#AIAgents #AgenticAI #Netra #AIObservability #Reliability
No crash. No spike. No warning.
Just your AI agent slowly becoming a worse version of itself.
That's the drift nobody talks about.
Netra Alerts catch it early.
Watch to see what acting on it early looks like.
#AIAgents#LLMOps#AIObservability#AgentOps#Netra #DeveloperTools #AIEngineering
As Pencil scaled their AI ad-agent stack, they needed real-time visibility to keep up.
With Netra:
- Debugging time dropped to under 30 min
- Failure Identification down to 10โ15 min
- AI costs tracked across every model and tenant
- 1M+ spans processed daily
Scaling fast, staying in control.
Read the full blog here : https://t.co/L1FmS83YqZ
#AIAgents #LLMOps #AIObservability #AgentOps #GenerativeAI #Netra
We traced a CrewAI agent and found things we didn't expect.
3 lines of code showed us everything our logs never did.
See what your agent is hiding โ https://t.co/ThyLI1qmE5
#AIAgents#LLMOps#Netra
The AI conversation is changing.
From โwhat can agents do?โ to โcan we actually see them, trust them, and ship faster with them?โ
These are perspectives from teams already navigating that shift firsthand.
Book a demo: https://t.co/exdpLrHSAu
#AIObservability#AIAgents#LLMOps #MLOps #DevTools #Netra
Your AI agent didn't fail on the first response. It failed 12 exchanges in.
Thatโs the problem with most evals.
Single turn scoring can make an agent look production-ready while a real multi-turn conversation exposes context drift, weak memory, persona breaks, and missed goals.
We saw it firsthand while running multi turn simulation at scale.
If youโre still evaluating conversational agents one response at a time, you may be shipping optimism, not reliability.
Read the blog to see what full-conversation AI simulation revealed that turn-level evals completely missed.
Read the blog here : https://t.co/bshSNiVBZV
#MultiTurnConversation #MultiTurnSimulation #AISimulation #AgentSimulation #AIAgentMonitoring #AgentBasedMonitoring #ConversationalAI #LLMEvaluation #AgentOps #GenAI #AIProductEngineering #Netra
Full AI agent visibility in under 5 minutes.
โ pip install netra-sdk
โ 2 lines of code
Done. Every trace, live.
Check out Netra @ https://t.co/pxo1CGqkvJ
#AIAgents#LLMOps#Netra
Two months ago a prospect said:
"Love Netra. But our data never leaves our walls."
Today it doesn't have to.
Air-gapped. No cloud. Fully theirs.
This photo, us sharing what we learned, reliving the moments that made it click.
Looking for more moments like this one.
#netra
We have been testing AI agents wrong.
Unit tests. Integration tests. CI green.
Still broke in production. Same inputs. Every time.
Our founder wrote about it โ
https://t.co/8DwvhlrbLn
What does your current test setup not cover?
#Netra#AIAgents#AIObservability