Observer & LLM monitor

See every tool call and every LLM request your agents make

The Observer captures real-time agent activity. The LLM Monitor captures every prompt sent to every model API. Minutes to deploy, no code changes required.

Policy rules

Define rules. Stack them. Monitor in real time.

Build a layered policy engine that matches the complexity of your agent estate. Each rule targets a specific risk. Stack them to create comprehensive coverage across every agent, team, and compliance framework.

Observer policy rules interface showing rule definitions, stacking, and real-time monitoring
How it works

Four capabilities. One integration.

Full prompt capture

Every request captured with full prompt text, model, token count, cost, and latency. Lightweight integration with negligible overhead, never breaks a developer's workflow.

LLM request log
Time Agent Model Tokens Cost Lat
14:31:02 billing-copilot claude-3.5-sonnet 1,247 / 892 $0.042 1.2s
14:30:58 support-triage gpt-4o 834 / 512 $0.018 0.9s
14:30:41 code-review-bot claude-3.5-sonnet 3,102 / 1,640 $0.107 2.1s
14:30:27 data-pipeline gpt-4o 2,891 / 944 $0.063 1.7s

PII detection and policy enforcement

Scan every prompt for PII patterns. Enforce policies before requests reach the model. Alert on violations in real time.

Request detail
Agent data-pipeline
Model gpt-4o
Policy Violated: no-pii-in-prompts
Prompt excerpt
Process this customer record for billing. Name: John Smith, Email: j.smith@acme.com, Phone: +1-415-555-0182. Generate a summary for the support team.
PII detected: email address, phone number

Cost attribution

See exactly which agents call which models, how many tokens they consume, and what they cost. Attribute LLM spend to teams, projects, and use cases.

Cost by agent, last 30 days
billing-copilot $142.30
support-triage $89.17
code-review-bot $34.52
By model
Claude $163.80 GPT-4o $89.14 Llama 3 $13.05

Threat detection

Detect anomalous behavior, data exfiltration patterns, and prompt injection attempts. Configurable threat rules with automatic alerts.

Active alerts
High
Anomalous volume support-triage · 10x baseline in 5 min
2m ago
High
Data exfiltration pattern code-review-bot · large outbound payloads
14m ago
Med
Prompt injection attempt billing-copilot · user input bypass detected
1h ago
The problem

Running blind is not a monitoring strategy

When agents call LLMs on your behalf, the requests are invisible by default. Costs, PII, policy violations, all happening outside your field of view.

Without runtime monitoring
  • No visibility into what prompts agents send to LLMs
  • PII in requests discovered after a breach, not before
  • LLM costs discovered in monthly cloud bills with no attribution
  • Policy violations are invisible until an incident
  • Agent behavior changes silently when models update
With Roval
  • Full visibility into every LLM request across every agent
  • PII detection flags sensitive data before it reaches any model
  • Real-time cost attribution by agent, team, and model
  • Policy violations detected and alerted in real time
  • Behavioral drift detected continuously with threshold alerts
Installation

Minutes to deploy. No code changes.

Integrate with your existing agent stack in minutes. Works with all major LLM providers and agent frameworks.

Compatible with OpenAI, Anthropic, LangChain, LlamaIndex, and more
Zero impact on agent performance or reliability
No changes to your existing codebase required

Know what your agents are sending.

Request early access to the Observer and LLM Monitor. Setup takes under 5 minutes.

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