Kong AI Gateway Managed gateway

Overview

Interpret these fields: Self-hosted vs managed LLM gateways · Who still owns your LLM gateway?

What kind of product Category ?

Managed gateway Not verified

Marketplaces resell many providers behind one key. Gateways add governance on top. Open-source projects you run yourself. Cloud platforms are hyperscaler surfaces. Inference providers host models on their own hardware.

Who runs it Deployment model ?

Managed or self-host Not verified

Managed means the vendor operates it. Self-host means you run it on your own infrastructure. Both means you can choose.

Licence Licence ?

Apache-2.0 Verified Sep 14, 2026

Proprietary products cannot be inspected or forked. Open licences such as MIT and Apache-2.0 let you audit, modify, and run the code without permission.

Company Company ?

Kong Inc. Verified Aug 29, 2026

The organisation that maintains the product.

Who you would be signing with Vendor status ?

Independent company Not verified

Whether the product is still an independent company, has been acquired, is a large cloud vendor’s product line, is run by a software foundation, or has been put into maintenance mode. Maintenance mode means bug fixes and security patches only — no new features.

Last shipped an update Latest release ?

2026-08-26 Not verified

Kong Gateway 3.14.0.14. The open-source Kong/kong repository moves more slowly: latest tag 3.9.3 on 17 June 2026.

The date of the most recent release or version tag. A product that has not shipped in a year is a different risk from one that shipped last week, regardless of what its marketing site says.

GitHub stars GitHub stars ?

44,100 Verified Aug 29, 2026

A rough proxy for community size on open-source projects. Not a quality measure.

Cost

Interpret these fields: How LLM gateway pricing works · LLM gateway spending limits: stop a runaway agent bill? · Choosing a gateway for realtime voice agents

Markup on model prices Token markup ?

Not published Not verified

How much the product adds on top of what the underlying model provider charges. Zero means you pay the same per-token price you would pay the model provider directly.

Fee to add funds Credit purchase fee ?

Not published Not verified

A percentage charged when you top up your balance, separate from token prices. It is easy to miss because it does not appear on the per-token price list.

Monthly cost per person Seat fee ?

Not published Not verified

A recurring per-user platform charge that applies regardless of how much you use the models.

Can use your own provider accounts BYOK supported ?

Yes Verified Aug 29, 2026

Bring Your Own Key: you keep direct contracts with OpenAI, Anthropic and others, and the gateway only routes traffic. This preserves negotiated rates and committed-spend discounts.

Cost of using your own accounts BYOK terms ?

You supply your own upstream LLM credentials, stored centrally in Kong's config store; Kong charges for gateways, not tokens. Not verified

What the product charges to route traffic through your own provider keys.

Free tier Free tier ?

30-day Konnect free trial with enterprise functionality; separately, Kong Gateway core is Apache-2.0 and free to self-host. Verified Aug 29, 2026

What you can do without paying, useful for evaluation.

Enterprise plan from Enterprise plan from ?

Not published Not verified

Annual entry price for the enterprise tier, where one is published or credibly reported.

Cost to run it yourself Self-host cost ?

Kong Gateway core is Apache-2.0 and self-hostable at infra cost only. The Plus plan is billed per gateway per month with the amount not published; fully self-hosted gateways plus audit logs and SSO require the custom-priced, annually billed Enterprise plan. Third-party reviews note the OSS build lacks semantic caching, analytics and compliance features found in Enterprise. Verified Aug 29, 2026

What self-hosting actually costs once you account for infrastructure and any paid tier.

How the vendor makes money Pricing model ?

Flat monthly platform fee Not verified

The shape of the vendor’s bill: does the routing layer charge a percentage on top of tokens, a flat monthly fee, both, neither (because inference is the product), or nothing at all (open source with no paid tier).

How pricing works, briefly Pricing model detail ?

Flat per-gateway platform fee (Konnect Plus, no dollar figure published) + enterprise-only annual quote. Kong does not resell inference. Plans billed on a calendar month basis in arrears. Not verified

A one-paragraph description that covers the caveats a pricing category cannot: introductory rates, per-feature meters, tier gating, and pricing that resets on a specific date.

Minimum commitment Minimum commitment ?

Enterprise 'billed annually' with duration set out in the individual Order Form; no minimum amount stated. Plus is monthly. Not verified

Whether the vendor requires a minimum contract term, a minimum spend, or a provisioned-capacity purchase to get its published rate.

Charges that fire after you go over an allowance Overage terms ?

No metered overage billing published. Plus enforces soft limits via email + in-app notifications prompting you to reduce usage or upgrade. Not verified

The line items that scale with usage after an included allowance is exhausted — log storage, extra requests, per-feature meters, data export — which is where cost estimates usually go wrong.

Prompt cache offered Cache mechanism ?

Semantic cache Not verified

Whether the gateway offers its own response cache, what kind of match it does (exact request, prefix, semantic), or simply passes provider caching through unchanged.

Discount on cached input Cache-read discount ?

Not published Not verified

How much cheaper cached tokens are than fresh input, when the vendor publishes a single figure. Bundled-inference clouds usually price this per model instead of as one number.

Premium on cache writes Cache-write premium ?

Not published Not verified

How much more the first write of a cached prefix costs versus a plain input token. A high write premium and a low hit rate can leave you paying more than you save, so this matters as much as the read discount.

Who captures the cache saving Cache economics ?

Semantic caching included in Plus under 'Cost Control'. Exact-match and provider passthrough not stated. Kong prices no tokens, so semantic cache hits save on the customer's provider bill; cached requests may still count toward Plus request/analytics limits. Not verified

Whether the customer keeps the full saving from caching or the vendor captures part of it — and any conditions attached (write premium, storage fees, best-effort hits).

What you can split spend by Cost attribution ?

Plus includes 'AI Observability: token-level tracking and real-time cost analytics'. Per key/user/team/tag/customer splits not stated. Not verified

The dimensions the vendor documents for splitting spend — per key, per user, per team, per tag, per customer. Matters if you need to chargeback internally or bill an end customer.

How you get cost data out Cost export ?

None stated on the pricing page. Not verified

The mechanisms the vendor publishes for exporting cost and usage data: CSV, an API, webhooks, S3, a data warehouse, or nothing at all. Any per-unit price is included.

Who pays the model bill BYOK mode ?

Your keys only Not verified

Whether you bring your own provider accounts (BYOK), buy inference from this vendor, or can do either. This is the single biggest commercial difference between these products: it decides who holds the contract with the model provider and who carries the spend.

Catalog

Interpret these fields: LLM gateway model counts: what “500+” means · Model aliases and deprecations: build an endpoint inventory · Choosing a provider for Qwen, DeepSeek, GLM or Kimi

Models available Models available ?

Not published Not verified

How many models you can call, shown as a range because several vendors publish different totals on different pages. Vendor-reported either way, so counts are not directly comparable — some count every provider variant of the same model separately.

Model providers reachable Upstream providers ?

17 Not verified

How many distinct model providers or labs you can reach, shown as a range where the vendor’s own pages disagree. More providers usually means better redundancy when one has an outage.

Works with standard OpenAI code OpenAI-compatible API ?

Yes Verified Aug 29, 2026

If yes, you can usually switch to it by changing one base URL, and switch away just as easily. This is the main defence against lock-in.

OpenAI chat endpoint POST /v1/chat/completions ?

Yes Not verified

The endpoint almost every application ports first. "Not documented" means the vendor never states it, which is different from a documented no.

Anthropic messages endpoint POST /v1/messages ?

Yes Not verified

Whether Anthropic-shaped calls work without rewriting them. Several products support this only as SDK compatibility or provider passthrough rather than a native endpoint — the detail page says which.

OpenAI Responses endpoint POST /v1/responses ?

Yes Not verified

The newer stateful OpenAI surface. Support is much thinner across this market than chat completions.

Embeddings endpoint POST /v1/embeddings ?

Yes Not verified

Whether you can generate vectors through the same gateway, or need a second integration for retrieval workloads.

Image generation endpoint POST /v1/images/generations ?

Yes Not verified

Whether image models are reachable through the same surface as text.

Audio endpoints POST /v1/audio/* ?

Yes Not verified

Speech-to-text and text-to-speech. Frequently the first gap in an otherwise complete gateway.

Batch jobs endpoint POST /v1/batches ?

Yes Not verified

Asynchronous bulk processing, usually at a discount. Commonly undocumented, and commonly the reason a migration stalls late.

Needs the vendor’s own code library Requires a vendor-specific SDK ?

No Verified Aug 29, 2026

A proprietary client library spreads through your codebase and has to be torn out again if you leave. “No” is the better answer here, and it means the standard OpenAI client works.

You can export your request history Logs / usage data export ?

Yes Verified Aug 29, 2026

Whether you can get your own request logs, traces, or usage records back out — through an API, a bulk export, or a download. Decides whether you leave with your history or abandon it.

Settings can live in version control Declarative config-as-code ?

Yes Verified Aug 29, 2026

Whether routing, fallback, and budget rules can be declared in a file you keep in Git, rather than existing only as settings clicked into a hosted dashboard.

Embeddings Embeddings ?

Yes Verified Aug 29, 2026

Text-to-vector models, needed for search and retrieval features.

Image generation Image generation ?

Not published Not verified

Whether image models are reachable through the same interface.

Speech and audio Speech and audio ?

Not published Not verified

Text-to-speech or transcription models through the same interface.

Video generation Video generation ?

Not published Not verified

Whether video models are reachable through the same interface.

Batch processing Batch processing ?

Not published Not verified

Submitting large jobs for cheaper, slower processing. Often 50% off for work that is not time-sensitive.

Routing & reliability

Interpret these fields: How LLM gateway failover actually works · Does your LLM gateway promise any uptime? · Is routing destroying your prompt cache? · Changing models without breaking production · Choosing a gateway for realtime voice agents

Uptime it promises in writing Contractual SLA uptime ?

99.9% Not verified

The uptime percentage in a published, contractual service level agreement. A public status page is not an SLA — it reports what happened, it does not promise anything or pay you back when it breaks.

Automatic failover Automatic failover ?

Yes Verified Aug 29, 2026

When a model provider goes down or rate-limits you, traffic moves to a backup automatically instead of returning errors to your users.

Load balancing Load balancing ?

Yes Verified Aug 29, 2026

Spreads requests across several providers or keys to raise your effective rate limit.

Rule-based routing Conditional routing ?

Yes Verified Aug 29, 2026

Send different requests to different models based on rules — for example a cheap model for free users and a strong model for paying ones.

Response caching Response caching ?

Not published Not verified

Reuses the answer when the exact same request comes in again, which cuts both cost and latency.

Similar-question caching Semantic cache ?

Yes Verified Aug 29, 2026

Reuses an answer when a new question means roughly the same thing as an earlier one. Saves far more than exact-match caching but can return subtly wrong answers if tuned loosely.

Where you set the timeout Request timeout surface ?

In config Not verified

Upstream/service timeouts `connect_timeout`, `read_timeout`, `write_timeout` are configurable, and timeout is a first-class failover condition ([Kong AI Proxy Advanced](https://developer.konghq.com/plugins/ai-proxy-advanced/)).

Where a request timeout can be set: per request, in a config file, in the vendor dashboard, or nowhere. Nine of the twenty products documented here do not describe a request timeout at all, so the worst case of a hung upstream call is unknowable from the docs.

Where you set retries Retry policy surface ?

In config Not verified

Key `retries`, which retries on both error and timeout. Default retry count and backoff strategy are not stated on the fetched pages: `n.a.` ([Kong AI Proxy Advanced](https://developer.konghq.com/plugins/ai-proxy-advanced/)).

Where retry count and backoff are configured. Worth knowing alongside billing: a retried streaming call can be charged more than once.

Where you set fallbacks Fallback surface ?

In config Not verified

ORDERED and WEIGHTED are both available — the AI Proxy Advanced plugin's target list supports `weight` (documented example 70/25/5), and failover is controlled by `failover_criteria`, which defaults to error and timeout and can add `http_429`, `http_500` and `non_idempotent` ([Kong AI Gateway load balancing](https://developer.konghq.com/ai-gateway/load-balancing/), [Kong AI Proxy Advanced](https://developer.konghq.com/plugins/ai-proxy-advanced/)).

Where the fallback chain is defined. Almost every product claims fallback; the useful question is whether you can change it from code or only by hand in a dashboard.

Shape of the fallback chain Fallback shape ?

Weighted split Not verified

An ordered list tries targets in sequence; a weighted split sends a percentage of traffic to each, which is what you need to trial a new model on 5% of requests. Weighted splits are much rarer than the marketing implies.

Upstream health tracking Health checks / circuit breaking ?

In config Not verified

`config_file`, and it is a real circuit breaker: from v3.13+ `config.balancer.max_fails` with `config.balancer.fail_timeout` ejects a failing upstream for a period ([Kong AI Gateway load balancing](https://developer.konghq.com/ai-gateway/load-balancing/)). Kong Gateway itself lists "health checking" as configurable through the admin API or declarative config ([Kong/kong](https://github.com/Kong/kong)).

Whether the product notices a failing upstream and stops sending traffic to it, and whether you can tune the thresholds. This is what turns a provider outage into a blip rather than a sustained error rate, and only four of the twenty expose it.

Cross-region failover you control Multi-region failover surface ?

Not documented Not verified

`not_documented` as a named feature. You self-host the data plane wherever you like (Linux, Docker, Kubernetes, or Konnect's managed control plane), but no cross-region failover config is documented ([Kong Gateway install](https://developer.konghq.com/gateway/install/)).

Whether you can define what happens when a region degrades. A vendor running many regions is not the same as a vendor letting you configure failover between them; only three document a user-controlled mechanism.

Where you set load balancing Load balancing surface ?

In config Not verified

Weights supported (`weight` on upstream targets). Strategies include lowest-latency with `latency_strategy` (`tpot` default, or `e2e`) and peak-EWMA, plus consistent hashing via `hash_on_header` (default header `X-Kong-LLM-Request-ID`) ([Kong AI Gateway load balancing](https://developer.konghq.com/ai-gateway/load-balancing/)).

Where traffic distribution across upstreams or keys is configured.

Operations

Interpret these fields: LLM gateway observability: traces, logs and export · Changing models without breaking production · Running coding agents through an LLM gateway · Model aliases and deprecations: build an endpoint inventory

Usage dashboards and logs Observability ?

Yes Verified Aug 29, 2026

Built-in visibility into what was sent, what came back, what it cost, and how long it took.

Spending limits Budget controls ?

Not published Not verified

Hard caps that stop spend before it becomes a surprise invoice. The single most valuable control for a small team.

Rate limits Rate limits ?

Yes Verified Aug 29, 2026

Caps on request volume per key or per user, useful for protecting against abuse and runaway loops.

Separate keys per team or app Virtual keys ?

Not published Not verified

Issue scoped keys with their own budgets and permissions so you can attribute cost and revoke access without rotating everything.

Prompt versioning Prompt management ?

Yes Verified Aug 29, 2026

Store and version prompts outside your code so they can be changed without a deploy.

Quality testing Evals ?

Not published Not verified

Built-in tooling to score model output against test cases, so you can tell whether a model swap made things better or worse.

MCP support MCP support ?

Yes Verified Aug 29, 2026

Native support for the Model Context Protocol, the emerging standard for connecting models to external tools.

What gets logged Logged content ?

Your choice Not verified

AI plugin logging of statistics and payloads is controlled per plugin; Kong's AI audit log records guardrail verdicts and, for the sanitizer, the original and redacted entity values ([AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/))

Whether full prompts and responses are stored, only metadata, or nothing. Full-body logging is the most useful debugging feature here and the one most likely to need a conversation with your compliance team.

You can turn logging off Body-logging opt-out ?

Yes Not verified

Payload logging is a plugin config toggle, so metrics can be kept without bodies ([AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/))

Whether prompt and response bodies can be suppressed while still keeping usage metrics. Nineteen of the twenty document a way to do this; the mechanisms range from a per-request header to an organisation-wide setting.

Traces you can take elsewhere Distributed tracing ?

OpenTelemetry Not verified

OpenTelemetry is native to Kong: the `opentelemetry` plugin exports OTLP-over-HTTP spans (with AI span attributes and metrics in the AI Gateway) and supports full request-lifecycle tracing ([Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether the product emits OpenTelemetry, a proprietary format, or nothing. OpenTelemetry means the traces land in the tooling you already run instead of only in the vendor’s dashboard.

Where telemetry can go Export destinations ?

OpenTelemetry, Prometheus, Datadog, StatsD, HTTP log, Kafka, Loki Not verified

OpenTelemetry collectors/OTLP-HTTP endpoints for traces and metrics; Kong's AI audit log is emitted through Kong's logging plugins ([Kong AI Gateway](https://developer.konghq.com/ai-gateway/), [AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/)). A full enumerated destination list was `n.a.` on the fetched pages.

Documented sinks for logs and metrics. This is a good proxy for how replaceable the vendor’s own dashboard is: around twenty destinations means you never have to depend on it, while a CSV download means you do.

Can record user feedback Feedback capture API ?

No Not verified

`n.a.` — No feedback/score API documented ([Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether there is an API to attach a rating or score to a logged request, which is what lets production traffic feed quality work later.

Scores live traffic Online eval hooks ?

No Not verified

`n.a.` — No eval/online-scoring feature documented ([Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether automated scorers can run against real production requests, rather than only against a test set you assemble yourself.

Performance

Delay it adds Proxy overhead ?

12 ms Verified Aug 29, 2026

Extra time the product itself adds to each request, on top of however long the model takes. Usually irrelevant next to multi-second model latency, but it matters for high-volume or streaming-sensitive workloads.

Requests per second ceiling Throughput ?

8,200 rps Verified Aug 29, 2026

Published sustained request rate before the product becomes the bottleneck. Only relevant at genuinely high volume.

What the request path runs on Architecture class ?

Interpreted proxy Not verified

Repo language breakdown: Lua 89.2%, Perl 5.2%, Raku 3.1% ([Kong/kong](https://github.com/Kong/kong)).

The comparable way to talk about latency here. An edge worker, a compiled Go or Rust binary, and a Python proxy have different overhead floors no matter which figures each vendor publishes. Products that never disclose their runtime are recorded as undisclosed rather than assumed.

You can run the request path yourself Self-hostable data plane ?

Yes Not verified

Prebuilt `deb` and `rpm` packages, official Docker Hub images including a distroless image (AMD64 and ARM64), and Helm charts for Kong Gateway and Kong Ingress Controller ([Kong Gateway install](https://developer.konghq.com/gateway/install/)).

Whether the component that actually carries your prompts can run on your own infrastructure. Distinct from a vendor offering a self-hosted control plane while still proxying traffic through their network.

Streaming responses Streaming support ?

Yes Not verified

Supported, including WebSocket realtime traffic. Documented caveat: the lowest-latency balancing algorithm is "less suitable for long-lived connections like WebSockets" ([Kong AI Gateway load balancing](https://developer.konghq.com/ai-gateway/load-balancing/)).

Whether token-by-token streaming is documented. The caveats matter more than the yes: some products cannot cancel a stream without still being billed, and several timeout and fallback mechanisms stop applying once the first token has been sent.

Security & compliance

Interpret these fields: LLM gateway compliance: SOC 2, HIPAA and evidence · How LLM gateway guardrails fail · Which LLM gateways store your prompts? · Do you need an MCP gateway as well?

Does your prompt reach their servers Prompt transits vendor ?

Depends how you deploy it Not verified

The data plane is yours to run, or Kong-hosted as serverless or dedicated cloud gateways. Konnect's control plane is Kong-hosted in a geography you pick.

Whether the text you send passes through this company’s own infrastructure. If it does, every other promise on this page is a policy commitment rather than a physical impossibility. Self-hosted products can answer no outright.

What they keep if you change nothing Logging default ?

Nothing stored by default Not verified

The AI Proxy plugin ships with statistics and payload logging both set to false, so nothing about your prompts is recorded until you turn it on and point it at a sink you own.

Defaults matter more than options. A product that stores full prompts and replies unless you find the right header will have stored them by the time you read the docs.

How long they keep it Default content retention (days) ?

30 days Not verified

Thirty days for Konnect analytics and seven for audit logs. Prompt bodies are not retained at all unless you enable payload logging.

Default retention for request content, in days. Zero means nothing is kept. Read the note: several products keep nothing as a rule but make timed exceptions for abuse review or specific models.

Could they train on your prompts Training on customer data ?

Not published — silence, not a no Not verified

Nothing on the trust center or subprocessor page addresses training.

Whether the vendor may use your prompts and outputs to train models. “Not published” means we could not find any position, which is not the same as a no — ask for it in writing.

Where it runs, and what you can pin Region and residency control ?

Konnect control-plane geographies in Australia, the EU, the Middle East, the US, India and Singapore, with dedicated data planes across roughly 17 AWS, 13 Azure and 11 Google regions. Self-hosted and on-premises data planes are supported. Not verified

Which regions are offered and whether you can force processing to stay in one. A global endpoint that silently picks a region is a different compliance story from an endpoint you pin yourself.

Where safety filters run Guardrail execution location ?

In your own infrastructure Not verified

The PII sanitizer calls an anonymizer service you run yourself, typically in a Docker container, so redaction happens inside your boundary.

A filter that strips personal data only helps if it runs before the data leaves your boundary. If guardrails execute in the vendor’s cloud, the vendor has already received whatever you wanted redacted.

Who else touches the data Subprocessor list ?

https://konghq.com/legal/subprocessors Not verified

The published list of third parties the vendor passes your data to. No list means you cannot know the full chain, which most data-protection agreements require you to.

SOC 2 audited SOC 2 audited ?

Yes Verified Aug 29, 2026

An independent audit of security controls. Enterprise buyers and their procurement teams routinely require it.

Will sign a HIPAA agreement HIPAA BAA ?

Not published Not verified

Required before you may send protected health information through the service. Without a signed BAA, healthcare data is off limits.

GDPR commitments GDPR commitments ?

Yes Verified Aug 29, 2026

Published data processing terms for handling personal data of people in the EU and UK.

Can keep data in the EU EU data residency ?

Not published Not verified

Requests can be processed inside the EU rather than routed to US infrastructure. Often the deciding constraint for European customers.

Does not retain your data Zero data retention ?

Not published Not verified

Prompts and responses are not stored after the request completes. Sometimes a paid add-on rather than the default.

Strips personal data PII redaction ?

Yes Verified Aug 29, 2026

Detects and removes identifiers such as names, emails, and card numbers before the request reaches the model provider.

Content guardrails Content guardrails ?

Yes Verified Aug 29, 2026

Policy checks on inputs and outputs — blocking unsafe content, enforcing formats, or catching prompt-injection attempts.

Runs fully disconnected Air-gapped deployment ?

Not published Not verified

Can be deployed in a network with no internet access, which some regulated and defence environments require.

Blocks personal data in prompts PII / DLP enforcement ?

Can block the request Not verified

The AI PII Sanitizer plugin sends payloads to a customer-run `ai-pii-service` anonymiser covering ~20 categories, replaces matches with placeholders or synthetic values, and can restore originals on the response path; audit logs record `ai.sanitizer.pii_identified`, `pii_sanitized`, and per-entity original/redacted pairs ([AI Sanitizer plugin](https://developer.konghq.com/plugins/ai-sanitizer/), [AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/))

Whether personal data detection sits on the request path and can stop the call, merely inspects and forwards it, or is not documented. A control that only reports is a logging feature, not a policy control.

Blocks prompt injection Injection / jailbreak enforcement ?

Can block the request Not verified

Kong itself ships regex prompt guarding; injection/jailbreak classification comes from plugged-in services such as Lakera Guard, whose `input_block_reason` / `output_block_reason` audit fields record blocked requests ([AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/), [Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether injection and jailbreak detection can stop a request. Most products offering this call a partner classifier rather than shipping their own.

Blocks harmful content Toxicity / moderation enforcement ?

Can block the request Not verified

The AI Azure Content Safety plugin "analyzes the request against configured moderation categories and allows or blocks the request", and does the same for responses; GCP Model Armor input/output block reasons are also logged ([AI Azure Content Safety](https://developer.konghq.com/plugins/ai-azure-content-safety/), [AI audit log reference](https://developer.konghq.com/ai-gateway/ai-audit-log-reference/))

Whether hate, violence, sexual and self-harm categories are checked inline and can stop a request, in either direction.

Your own policy rules Custom policy hooks ?

Can block the request Not verified

`ai-prompt-guard` takes PCRE allow and deny pattern lists and returns HTTP 400 on a deny match; Azure Content Safety blocklist IDs and per-category thresholds are also configurable ([AI Prompt Guard](https://developer.konghq.com/plugins/ai-prompt-guard/), [AI Azure Content Safety](https://developer.konghq.com/plugins/ai-azure-content-safety/))

Whether you can add your own rule — a regex, a webhook, or your own classifier — rather than choosing from the vendor library.

Where guardrails run Guardrail execution location ?

Either, your choice Not verified

Whether guardrail evaluation happens inside your infrastructure or on the vendor’s servers. This decides whether the prompt you are trying to protect leaves your network in order to be checked.

If the guardrail itself fails Guardrail failure mode ?

Not documented Not verified

`not_documented` — no fail-open/fail-closed statement on the fetched guardrail plugin pages ([AI Azure Content Safety](https://developer.konghq.com/plugins/ai-azure-content-safety/), [AI AWS Guardrails reference](https://developer.konghq.com/plugins/ai-aws-guardrails/reference/))

What happens when the guardrail service times out or errors: does the request proceed unchecked, or is it blocked? This is the worst-documented field in the entire catalogue — only two vendors state it plainly, which means most teams are running a control whose failure behaviour they cannot know.

Third-party guardrail vendors Guardrail integrations ?

AWS Bedrock Guardrails, Azure Content Safety, Google Model Armor, Lakera Not verified

Named external guardrail services the product can call. A long list means the product is a router for policy engines rather than a policy engine itself — which also means another vendor bill and another hop.

Fit & integration

Interpret these fields: How much does an LLM gateway lock you in? · Changing models without breaking production · Running coding agents through an LLM gateway · Do you need an MCP gateway as well? · Choosing a gateway for realtime voice agents · Choosing a provider for Qwen, DeepSeek, GLM or Kimi

Work to try it Evaluation work shape ?

Run something locally first Not verified

The shape of the work on the vendor’s own quickstart, from swapping one base URL through to deploying infrastructure. An ordinal class rather than a duration, because elapsed time depends on accounts and quota we cannot see.

Work to run it Production work shape ?

Deploy it on your infrastructure Not verified

The same scale applied to the vendor’s recommended production path. For several products this is much heavier than the quickstart, which is exactly why both are recorded.

Steps on the quickstart Numbered quickstart steps ?

3 Not verified

A literal count of numbered steps on the vendor’s quickstart, recorded as evidence beside the work shape. Zero means the page publishes no numbered procedure at all. Large counts usually mean interleaved language tracks rather than more work.

Can you self-host it today Self-host install documentation ?

Install command published Not verified

`curl -Ls https://get.konghq.com/quickstart | bash -s -- -e KONG_LICENSE_DATA` (self-managed Enterprise); destroy with `curl -Ls https://get.konghq.com/quickstart | bash -s -- -d`; the AI-specific demo is `curl -Ls https://get.konghq.com/ai/v1 | bash` ([How to: Get started with Kong Gateway](https://developer.konghq.com/gateway/get-started/), [Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether an install command is actually published. Several products advertise self-hosting while publishing no command to start from, which a plain yes/no would hide.

Works with the OpenAI SDK OpenAI SDK drop-in ?

Partly Not verified

Kong documents connecting the LangChain OpenAI adapter without code changes. The documented setting is `base_url=f'{kong_url}/{kong_route}'`, with `kong_url="http://127.0.0.1:8000"`, `kong_route="gpt4o"`, and `api_key="NONE"` or a Kong consumer key. ([Kong LangChain integration guide](https://docs.jp.konghq.com/gateway/latest/ai-gateway/llm-library-integration-guides/langchain/))

Whether an existing OpenAI-compatible client can be pointed at it by changing the base URL and key.

Vercel AI SDK support AI SDK provider package ?

Not documented Not verified

n.a. (not documented)

Whether a first-party AI SDK provider package exists, or only a community package, a documented workaround, or the generic OpenAI provider pointed at a custom base URL.

Python framework integrations Documented Python frameworks ?

LangChain Not verified

Kong documents LangChain integration using the `langchain-openai` package and the `ChatOpenAI` class. Custom tools use `langchain_core.tools` and its `tool` decorator; LlamaIndex is not documented. ([Kong LangChain integration guide](https://docs.jp.konghq.com/gateway/latest/ai-gateway/llm-library-integration-guides/langchain/))

LangChain, LangGraph, LlamaIndex and similar orchestration frameworks with a documented integration.

Callable from Cloudflare Workers Cloudflare Workers support ?

Not documented Not verified

n.a. (not documented)

Whether the docs show calling this product from your own Worker. Deliberately separated from the several products whose own gateway runs on Workers, which is a fact about their infrastructure and not about your edge compatibility.

Kubernetes install Helm chart availability ?

Official Helm chart Not verified

Kong provides official Kubernetes Helm charts from `https://charts.konghq.com`, including `kong/ingress` and `kong/kong`. Kong’s Kubernetes integration uses the Kong Ingress Controller; `kong/ingress` is recommended for new installations, while `kong/kong` supports hybrid and unmanaged Kong instances. ([Kong Helm charts](https://charts.konghq.com/))

Whether a named, published Helm chart exists, versus Helm being referenced with no chart named, versus generic cluster documentation that has nothing to do with this product.

Terraform support Terraform provider or modules ?

Official Terraform provider Not verified

Kong documents the official Terraform providers `konnect`, `konnect-beta`, `kong-gateway`, and `kong-mesh`. The Terraform Registry provider source for the Kong Gateway provider is `Kong/kong-gateway`; the registry documentation states that Terraform 0.13+ is required. ([Kong Terraform documentation](https://developer.konghq.com/terraform/))

Whether you can declare this in code: an official provider, official modules, resources inside a hyperscaler’s provider, a community provider, or only Terraform code shipped in a repo.

Reuses your cloud identity Cloud IAM reuse ?

Reuses your cloud identity Not verified

Kong documents Azure authentication through an Azure Compute resource’s Managed Identity or User-Assigned Identity, configured with `config.auth.azure_use_managed_identity` and optionally `config.auth.azure_client_id`. Amazon Bedrock authentication can use AWS IAM credentials or assumed roles. ([Kong AI provider documentation](https://developer.konghq.com/ai-gateway/ai-providers/))

Whether you can authenticate with IAM roles, workload identity or managed identities instead of another long-lived API key. Distinguished from products that only accept static upstream provider credentials.

Fits behind your API gateway API gateway integration ?

It is the API gateway Not verified

Kong AI Gateway is implemented through Kong Gateway plugins, including **AI Proxy** and **AI Proxy Advanced**, with a minimum Kong Gateway version of `3.6`. The **AI MCP Proxy** is an additional Kong Gateway plugin for connecting Kong-managed services to MCP, available from Kong Gateway `3.12` and supporting hybrid, DB-less, and traditional topologies. ([Kong AI Gateway overview](https://developer.konghq.com/ai-gateway/))

Whether AI traffic can go through a gateway you already run, and who documented that — the product’s vendor or the gateway’s.

MCP support MCP surface shape ?

MCP gateway or registry Not verified

Kong’s AI MCP Proxy bridges MCP and HTTP, supports MCP tool discovery and invocation, proxies MCP requests, aggregates tools, and can convert REST API paths into MCP tools. Kong also provides `mcp-konnect`, an MCP server with tools for querying analytics and managing Konnect resources, usable with MCP clients such as Claude Desktop and Cursor. ([Kong AI MCP Proxy plugin](https://developer.konghq.com/plugins/ai-mcp-proxy/))

Which kind of MCP support this is: a gateway that governs many MCP servers, a hosted MCP server you connect to, MCP tools accepted inside the completion API, or client tooling. These are different products behind one acronym.

Needs your own provider key Upstream provider key required ?

Required Not verified

Yes for the documented walkthrough: prerequisites include "OpenAI account and API key" ([How to: Get started with AI Gateway](https://developer.konghq.com/ai-gateway/get-started/)); keys can be centralised via "Konnect Config Store to store and reference your LLM provider API keys" ([Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether an upstream provider account and key must exist before your first call works. A prerequisite rather than a step, and it can differ between the hosted and self-hosted forms of the same product.

Gate before models work Model access gate ?

Not documented Not verified

n.a. (not documented). No model approval, enablement, quota, or waitlist step appears ([How to: Get started with AI Gateway](https://developer.konghq.com/ai-gateway/get-started/), [Kong AI Gateway](https://developer.konghq.com/ai-gateway/))

Whether an enablement click, a quota grant, a paid tier or an approval form stands between a valid key and a working model call.

Official client languages First-party client SDK languages ?

Not published Not verified

The documentation explicitly names the **OpenAI SDK** and **Gemini SDK**. The LangChain guide documents Python usage of `langchain-openai` and `ChatOpenAI`; official Kong client-library names and a broader supported-language list are not documented. ([Kong AI provider documentation](https://developer.konghq.com/ai-gateway/ai-providers/))

Languages with a first-party client library. An empty list can still mean the product is usable from any language via an OpenAI-compatible SDK.