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DVARA vs Kong AI

API gateway heritage vs AI-native governance.

Kong is a mature API gateway with AI plugins added on top. DVARA is purpose-built for AI traffic patterns — tokens, models, streaming, MCP tool calls, agent loops, and context windows. The difference is architectural, not incremental.

AI-Native Capabilities

Kong treats AI as another API. DVARA understands AI traffic natively.

FeatureDVARAKong AI
OpenAI-compatible unified API
Structured outputs across all providers
Per-model capability flags on /v1/models
Capability-aware route filtering
Context window governance + pruning
Semantic caching (vector similarity)

Governance & Policy

FeatureDVARAKong AI
Policy-as-Code engine (YAML DSL)
Policy dry-run before activation
Immutable HMAC-signed audit trail
PII detection and redaction
Prompt firewall + jailbreak detection
Budget caps with model downgrade
RBAC access control

MCP & Agentic Governance

Kong has no MCP awareness whatsoever.

FeatureDVARAKong AI
MCP tool calls proxied and governed
MCP PII scan on arguments + responses
MCP server registry + credentials
Human approval gate
Agent loop detection + kill switch
Unified LLM + MCP trace

Operations

FeatureDVARAKong AI
Purpose-built for AI traffic
Sub-60-second quickstart
Air-gapped deployment
Multi-region active-active
SOC2 / HIPAA compliance reports
EU AI Act compliance engine

The Bottom Line

Kong is a general-purpose API gateway that added AI plugins. DVARA is an AI-native governance platform. Kong understands HTTP requests; DVARA understands tokens, models, tool calls, agent loops, and context windows. If your AI traffic needs more than routing, Kong hits its architectural ceiling.

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