The Evaluations Toolkit for Network AI Agents
Keep your NOC Copilots, RCA Agents, and Troubleshooting Bots consistently accurate.
Why Network AI Agents Demand a New Kind of Evaluation
Network AI agents aren’t like chatbots.
They make operational decisions:
A mistake isn't just "wrong."
It can cause cascading outages, SLA breaches, compliance risks, and major operational costs.
That's why we built the Evaluations Toolkit — a purpose-specific layer for stress-testing prompts, tuning agent policies, and proving reliability before those workflows ever touch live network operations.
Meet the Evaluations Toolkit for Network AI Agents
A single abstraction to evaluate every agent workflow.
Offline & Online Agent Evaluation
Deep Observability & Trace Collection
Support for DSPy, MLFLow, Langfuse and other frameworks
Automated scoring & Prompt Optimization
Ready-to-start NetworkScenarios
Unit & Workflow level evaluations
Our toolkit provides the evaluation glue your agentic network stack has been missing.
Define a test case once.
Run it anywhere — regardless of the agent framework.
Integrates With the Network AI Ecosystem
No need to rebuild your agent logic. Our toolkit plugs directly into what you already use.
Langfuse
Trace-level metrics, scores, hallucination tracking, cost/latency analysis.
DSPy
Evaluate ReAct/CoT-based network agents, track DSPy Signature accuracy, regression test after GEPA.
Custom APIs & OSS/BSS Systems
Validate tool-calls, CMDB lookups, topology queries, ticket updates, telemetry fetches.
MLflow
Compare versions of agents, prompts, and underlying LLMs.
Build For the Teams That Run Networks
NOC Copilots
Alarm Correlation Agents
RCA Agents
Troubleshooting Assistants
Ticketing/Service Desk Agents
Network Automation Bots
Telecom · ISP · OSS/BSS · Enterprises
Ready to Get Started?
Empower your network operations with AI-driven intelligence and automation.