AI-Assisted Detection

Ask your infrastructure a question.

Klyroo's chat assistant calls real tools against your live data — server status, alert history, log search — instead of guessing from a prompt. Ask in plain language, get an answer grounded in what's actually happening right now.

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Grounded, Not Guessed

Real function calls, not a stale training cutoff.

A language model on its own doesn't know your infrastructure's current state — it can only guess, or worse, sound confident while guessing. Klyroo's chat assistant instead calls actual tools against your live dashboard data: search servers by status, pull alert history, search logs. The answer comes from a live query, and the model's job is to phrase it clearly, not to invent it.

Which servers are unhealthy right now?

🔧 search_servers(status: "down")

2 servers are currently down: db-replica-2 (no check-in for 6 min) and worker-03 (disk full, 09:41 UTC).

Example Prompts

What people actually ask it.

Prompt	Tool call	What comes back
"Which servers are down right now?"	`search_servers(status)`	Live status, not a stale snapshot
"Why did server-13 alert this morning?"	`get_alert_history(server)`	The same causal reasoning shown in the incident view
"What's the root cause of the current incident on db-replica-2?"	`get_incident(server)`	Named root cause plus the effect chain
"Show me any recent errors mentioning connection timeouts"	`search_logs(query)`	Matching log lines with context

Unrecognized, Not Ignored

Log lines that don't match a known signature still get a voice.

223 root-cause signatures can't cover every possible log line from every possible stack. When a line looks worth attention but doesn't match a known pattern, it gets routed for an LLM-generated explanation instead of being silently dropped — so an unusual failure on an uncommon stack still gets some signal, even without a pre-written fix attached.

Where We Stand

Scope, honestly.

What's covered

Tool-calling chat grounded in live server, alert, and log data
Plain-language answers to status, history, and root-cause questions
LLM-generated explanations for log lines outside the curated signature library

What it isn't

Read and investigate only — the chat cannot take an action on your infrastructure by itself. Blocking an IP or updating an agent still requires the explicit, human-approved flow described in Automated Response
Answers are grounded in the data Klyroo already has — it won't reach outside your monitored infrastructure for context it doesn't have

Pairs Well With

Related capabilities

Ask it about your own infrastructure.

Point one agent at a handful of servers and start asking questions.

Book a 20-minute demo