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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.
Helicone vs Kong AI Gateway
Context: LLM Gateways & Model Routing Platforms · 22 rows
| Attribute | HeliconeHelicone | Kong AI GatewayKong |
|---|---|---|
| Identity · Taxonomy | ||
| Documentation | — | https://developer.konghq.com/ai-gateway/ |
| Tags | llm-observability, llm-gateway, open-source, monitoring | llm-gateway, api-gateway, kubernetes, mcp, microservices |
| Platform · Deployment | ||
| Delivery model | SaaS, self-hosted | SaaS, self-hosted |
| Pricing · Licensing | ||
| Free plan | true | — |
| Free trial | true | — |
| License model | open-source | open-source |
| Pricing model | free, subscription, usage | custom |
| Source repository | https://github.com/Helicone/helicone | https://github.com/Kong/kong |
| SPDX license IDs | Apache-2.0 | Apache-2.0 |
| Starting price | 79 | — |
| Trial length | 7 | — |
| Features · Product · Fit | ||
| Core capabilities | LLM request logging and tracing, AI gateway with caching, rate limits, and fallbacks, Prompt management and datasets, HQL querying and user analytics, Alerts and reports, Evaluation and experiments | 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 |
| Enterprise SSO | SAML | — |
| Security · Privacy · Compliance | ||
| Security certifications | SOC 2, HIPAA | — |
| Support · Docs · Services | ||
| Support channels | community, email | — |
| Audience · Use · Case | ||
| Best for | AI engineering teams that want open-source LLM observability with an optional hosted gateway for logging, caching, and rate limiting. | 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 | LLM observability and debugging, Cost and latency monitoring, Gateway routing for AI applications | 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.