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Pick 2–5 published tools. Values come from our evidence-checked profiles — an em-dash means unknown, never “no”. Ranking rows reflect the current published methodology for the comparison context.
Requesty vs Kong AI Gateway
Context: LLM Gateways & Model Routing Platforms · 17 rows
| Attribute | RequestyRequesty | Kong AI GatewayKong |
|---|---|---|
| Identity · Taxonomy | ||
| Documentation | https://docs.requesty.ai | https://developer.konghq.com/ai-gateway/ |
| Tags | llm-gateway, model-routing, cost-optimization, observability | llm-gateway, api-gateway, kubernetes, mcp, microservices |
| Platform · Deployment | ||
| Delivery model | SaaS | SaaS, self-hosted |
| Pricing · Licensing | ||
| Free plan | true | — |
| License model | — | open-source |
| Pricing model | usage, custom | custom |
| Source repository | — | https://github.com/Kong/kong |
| SPDX license IDs | — | Apache-2.0 |
| Features · Product · Fit | ||
| Core capabilities | OpenAI-compatible router API for 600+ models, Routing by cost, latency, and availability, Automatic failover and weighted load balancing, Observability dashboards for cost and latency, RBAC and approved-model whitelists, PII masking with EU data residency | Multi-LLM routing with provider failover, Semantic caching and load balancing, PII sanitization and semantic prompt guards, Token quotas, chargeback, and spend tracking, MCP server governance and authentication, L7 observability with logging and tracing |
| Api · Integrations · Ecosystem | ||
| API available | true | true |
| Security · Privacy · Compliance | ||
| Regulatory compliance | GDPR | — |
| Audience · Use · Case | ||
| Best for | Developers and companies that want a hosted router across many model providers with cost controls, caching, and governance features. | Organizations with existing API gateway or Kubernetes infrastructure that want LLM, MCP, and agent traffic governed through one gateway platform. |
| Company-size fit | individual, SMB, mid-market, enterprise | SMB, mid-market, enterprise |
| Primary use cases | Multi-provider LLM routing, Cost optimization and budget caps, AI governance and PII protection | Governing LLM traffic in API infrastructure, MCP and agent-to-agent traffic governance, Provider switching and failover |
| Skill level | intermediate | advanced |
| Lifecycle · Versioning | ||
| Maintenance status | active | active |
| Vendor · Maintainer | ||
| Vendor type | commercial | commercial |
“—” means unknown (we never treat missing evidence as a negative). Cells reflect each value's current evidence state; superseded or stale values are excluded. Ranking rows are editorial assessments under the cited methodology version — see the LLM Gateways & Model Routing Platforms category for definitions.