Splyntra traces every AI-agent run with a risk score, analyzes cost, evaluates quality, and governs what agents can do — on one OpenTelemetry-based pipeline. Source-available core, self-host or managed cloud.
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Maker
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Hey! 👋 I'm Anand, the creator of Splyntra.
As AI agents move from simple prototypes to production environments handling critical tasks, observability and security become major bottlenecks. Traditional APM tools weren't built for non-deterministic LLM workflows, multi-agent loops, or sudden cost spikes.
We built Splyntra to give developers and teams full visibility and guardrails over their agentic workflows — all on a single OpenTelemetry-native pipeline.
What you can do with Splyntra:
🔍 Trace Agent Execution — complete, distributed traces of multi-step agent actions, tool calls, and LLM decisions
🛡️ Real-Time Risk Scoring — automatically evaluate and score risk across prompt injections, tool abuse, and unintended agent behavior
💰 Cost & Quality Insights — track token spend, latency, and output quality across every model provider
🔐 Agent Governance — set policy guardrails to control what tools agents can access and enforce execution boundaries
⚙️ Open & Flexible — source-available core on GitHub, self-host it in your own VPC, or use our managed cloud
Two-line install if you want to try it now:
pip install splyntra
# or
npm install @splyntra/sdk
Hey! 👋 I'm Anand, the creator of Splyntra.
As AI agents move from simple prototypes to production environments handling critical tasks, observability and security become major bottlenecks. Traditional APM tools weren't built for non-deterministic LLM workflows, multi-agent loops, or sudden cost spikes.
We built Splyntra to give developers and teams full visibility and guardrails over their agentic workflows — all on a single OpenTelemetry-native pipeline.
What you can do with Splyntra:
🔍 Trace Agent Execution — complete, distributed traces of multi-step agent actions, tool calls, and LLM decisions
🛡️ Real-Time Risk Scoring — automatically evaluate and score risk across prompt injections, tool abuse, and unintended agent behavior
💰 Cost & Quality Insights — track token spend, latency, and output quality across every model provider
🔐 Agent Governance — set policy guardrails to control what tools agents can access and enforce execution boundaries
⚙️ Open & Flexible — source-available core on GitHub, self-host it in your own VPC, or use our managed cloud
Two-line install if you want to try it now:
Docs are here if you want the full picture: splyntra.com/docs
Would love for you to try it out, poke at the repo, and tell us what breaks. I'll be in the comments all day to answer questions and take feedback! 🚀