Multi-Vendor Network Configuration Analysis with CogniNet
Parse and analyze configurations from Cisco IOS, NX-OS, ASA, Palo Alto, and F5 through 7 specialized analyzers and a 108+ rule engine — in a single pass.
CogniNetBatfish
Cisco IOSCisco NX-OSPalo AltoF5The problem today
Multi-vendor networks mean multi-tool analysis. Cisco configs go through one validation tool, Palo Alto through another, F5 through a third — if they get analyzed at all. Cross-vendor issues (a Cisco ACL blocking traffic that a Palo Alto policy expects to pass, an F5 pool member pointing at a subnet that a Cisco router doesn't advertise) fall through the cracks because no single tool sees the whole picture. Each vendor's best practices are checked in isolation, missing the interactions that cause real outages.
How AI agents solve it
CogniNet has vendor-specific parsers for Cisco IOS/IOS-XE, NX-OS, ASA, Palo Alto Networks, and F5 BIG-IP. All configs are parsed into a unified data model and fed into a single heterogeneous graph. The 7 specialized analyzers then run cross-vendor: the routing analyzer checks OSPF/BGP consistency across Cisco and Palo Alto, the security analyzer validates ACL and zone policies end-to-end, the capacity analyzer spots subnet exhaustion regardless of which vendor owns the prefix. The 108+ rule engine scores each device against management, control plane, and data plane best practices tuned per vendor.
Who this is for: Network engineers and architects managing multi-vendor environments (enterprise campus, data center, hybrid cloud)
Manual workflow vs. CogniNet Agent
Manual workflow
- Each vendor analyzed by a different tool or team
- Cross-vendor issues fall through the cracks
- No unified view of network health across vendors
- Best practices checked in vendor silos
- Integration issues found in production, not in analysis
With the CogniNet Agent
- All vendors parsed into a single unified data model
- Cross-vendor issues caught by graph-wide analysis
- Single health score and issue list across the entire network
- 108+ rules tuned per vendor but applied holistically
- Integration issues surfaced before deployment
How the CogniNet Agent runs this
- 01
CogniNet Agent collects configs from all supported vendors via API, Git, or file upload
- 02
Vendor-specific parsers extract devices, interfaces, routing protocols, security policies, and features
- 03
Unified data model normalizes vendor-specific constructs into common abstractions
- 04
Graph builder constructs a single heterogeneous graph spanning all vendors
- 05
7 analyzers run cross-vendor checks: routing consistency, L2 stability, FHRP readiness, multicast, security, capacity, convergence
- 06
Rule engine scores 108+ checks per device with vendor-specific tuning
- 07
Results surface per-device scores, cross-vendor issues, and prioritized remediation
Measurable impact
Eliminates vendor-siloed analysis that misses cross-platform issues
Single unified view of network health regardless of vendor mix
Cross-vendor routing, security, and capacity issues caught proactively
Remediation plans account for multi-vendor dependencies
Agents involved
Part of our Network Visibility solution
This use case is one piece of a larger pipeline
Multi-vendor analysis is part of the Network Visibility solution — see the full pipeline from config collection to cognitive analysis.
Explore the Network Visibility solutionGoverned by the AI Gateway
Every agent action in this use case is audited, policy-checked, and cost-tracked
Structura's AI Gateway sits between every agent and the underlying LLM providers. Every decision made during this use case. Every plan review, every policy check, every fix PR, is routed through guardrails, logged to an immutable audit trail, and evaluated against NIST AI RMF and AIUC-1 controls.
Learn about the AI GatewayRelated use cases
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See this use case in a live demo
We'll walk you through exactly how the CogniNet Agent handles this in a real environment with your stack, your policies, and your constraints.