Traces: Complete AI Observability for Every Conversation
When a bot does something unexpected, "it gave a weird answer" isn't enough to fix it. You need to see exactly what happened inside that conversation. Rylvo Traces captures every turn as a complete, replayable observation tree — across every channel your bots serve.
The problem this solves
Modern bots are complex: a single reply can involve an LLM call, several tool invocations, guardrail checks, and a knowledge-base lookup — across API, web widget, WhatsApp, Telegram, and the dashboard. When something goes wrong, plain logs give you a wall of text and aggregate analytics give you numbers, but neither lets you reconstruct one specific conversation step by step. So debugging becomes guesswork.
How it works
- Full observation tree. Every LLM call, tool call, guardrail check, and knowledge-base retrieval is captured in order, with timing — so you can see precisely what the bot did and why.
- Cost and latency, per turn. Each conversation shows its token usage and cost, so you can find your slowest and most expensive interactions and optimize them.
- Customer identity. Conversations are grouped by the customer behind them, even across channels, so you can answer "what happened for this person?"
- Replay and fix loop. Replay any trace to see the full flow, save a trace as a test case to lock in a fix, and track recurring issues over time.
What this means for you
You move from "the bot seems off" to "here's the exact step that failed, here's what it cost, and here's the test that proves it's fixed." Traces turns conversation data into operational intelligence — for debugging, for cost control, and for understanding your customers' real experience.
Getting started
- Open Traces.
- Click any conversation to expand its full observation tree.
- Replay a tricky one, then save it as a test case to make sure it never regresses.
See everything. Know everything. Fix anything.