The landscape for AI gateway tooling has expanded fast in the last year. What started as "put an nginx proxy in front of your LLM calls" has grown into a category with real product differences. The challenge is that most comparison pages from vendors in this space are misleading — features are listed as checkboxes without describing what they actually do or don't do.
This post is our attempt at a genuinely honest comparison. We'll acknowledge where other products do things we don't, and where we think our approach is materially better. We'll be specific about limitations instead of hiding behind vague "enterprise features on request" language.
We're focusing on four products we hear about most often: API Stronghold, Portkey, Kong AI Gateway, and AWS Bedrock Guardrails.
The question that separates the products
Most AI gateway products answer the question: "How do I route requests across multiple LLM providers with cost tracking?"
KnoxCall also answers: "How do I make sure an AI agent can't be manipulated into leaking secrets, calling unauthorized APIs, or sending PII to a provider that isn't cleared to see it?"
That's a security-first framing, not just an observability framing. It changes what you build.
Phantom tokens vs. API key forwarding
The most fundamental difference in this category is how provider credentials are handled.
API Stronghold, Portkey, Kong AI Gateway: You configure your provider API keys in the gateway's dashboard. The gateway injects them on the way to the upstream. Your application sends a gateway API key; the gateway swaps it for the provider key. This is better than putting the raw provider key in your app — but the gateway API key is still a bearer credential that grants full provider access if it's leaked.
KnoxCall: Phantom tokens are DPoP-bound capability credentials. They can be scoped to specific models and capped at specific budgets. They rotate via refresh chains that revoke old tokens on use. And because they're DPoP-bound, a leaked token is useless without the agent's private key. We think this is the right credential model for AI agents specifically — they operate in environments where prompt injection is a realistic attack vector, and bearer tokens are too broad.
This isn't a marketing claim about "zero-trust architecture." It's a specific mechanism: the gateway verifies a proof-of-possession JWT on every request, tied to a keypair the agent controls. If you can't present the keypair, the token doesn't work.
Prompt injection: detection vs. prevention
AWS Bedrock Guardrails: Has a prompt injection detection feature that uses a classifier to flag injection attempts. Good at detecting the known patterns; less useful for novel attacks. Tied to Bedrock — not available for Anthropic direct, OpenAI, or other providers.
API Stronghold, Portkey: Offer content moderation filtering using third-party classifiers (typically Lakera or similar). These work by scoring the prompt; high-score prompts get blocked. The challenge is threshold tuning — aggressive thresholds produce false positives on legitimate complex prompts.
KnoxCall: We run a layered approach. First, a fast regex/keyword heuristic stack covering the 8 most common prompt-injection patterns (case-insensitive, runs on every request regardless of policy). Then optional tenant-supplied rules. Then the canary mechanism: we inject a kc_canary_ token into every system prompt; if the model echoes it back verbatim in the response, we know the system prompt was successfully extracted. The canary signal is deterministic — no classifier threshold to tune.
The canary isn't a replacement for heuristic detection (it only catches successful exfiltration, not the attempt), but it's a reliable second signal for audit and alerting.
PII redaction in streaming responses
Streaming is the default for modern LLM applications. Most users are expecting token-by-token output. PII redaction in a streaming context is hard: you can't wait for the full response before deciding whether to redact, but you also can't make redaction decisions on half a word.
API Stronghold, Portkey, Kong AI Gateway: PII redaction on streaming responses is not supported or is listed as a future roadmap item. Most products buffer the full response, redact it, and re-stream — which adds latency and removes the UX benefit of streaming.
AWS Bedrock Guardrails: Has sensitive information detection that can be applied to streaming, but it's PII classification only (no tokenization), it's Bedrock-specific, and it operates at a chunk level that can still split sensitive values across chunk boundaries.
KnoxCall: We built a streaming PII rewriter with a configurable hold-back buffer (default 96 chars). The buffer is tuned so that entity boundaries never span the hold-back window; the rewriter flushes characters that are confirmed clean while holding back the minimum number of chars needed to avoid mid-entity decisions. Entities are replaced with format-preserving vault tokens, not generic [REDACTED] strings, so the model can refer back to tokenized values in later turns. The response-side detector stack also detokenizes on the way back to the caller, so the end user sees the original value if your policy permits it.
Compliance packs
API Stronghold, Portkey, Kong AI Gateway: Don't have compliance packs as a concept. Compliance configuration is manual.
AWS Bedrock Guardrails: Has HIPAA eligibility documentation for Bedrock infrastructure, but compliance configuration for content policies is manual.
KnoxCall: Compliance packs are file-based manifests that install recognizers and audit-alert rules in one operation. The HIPAA Safe Harbor pack installs 18 PHI entity recognizers and wires up alerts that fire when canary leaks, DPoP failures, or PHI-in-response events appear in the audit log. The GDPR pack installs email, phone, and national ID recognizers plus data-residency checks. PCI-DSS installs PAN tokenization with Luhn-valid format preservation. SOC 2 installs change-log and unauthorized-access alerts. You can review exactly what each pack installs before running it — no black box.
What we don't do (and why)
Honesty requires covering our gaps.
Semantic cache: We have it. It works. Our similarity threshold UI is solid. But Portkey's semantic cache has been in production longer and has better embedding model options. If semantic caching is your primary use case, Portkey's offering is currently more mature.
Fine-tuning and evals: We ship an eval runner for testing output schema compliance and model quality. API Stronghold has a more mature eval UI with test-case management and regression tracking. If you're doing heavy prompt engineering and need a first-class eval UI, that's a gap we're actively closing but haven't closed yet.
Hosted model inference: AWS Bedrock serves hosted models directly. KnoxCall is a proxy — you bring your own provider relationships. If you want a single vendor for both inference and security, Bedrock is the only product on this list that offers that.
Multi-region data residency: We support routing to data-residency-specific routes (EU-only, US-only) at the agent configuration level, but we don't have native multi-region infrastructure. If your compliance requirement is that tokens and usage data never leave a specific geography, we can accommodate that with self-hosted deployment but not (yet) with our SaaS offering.
The decision heuristic
Based on what we hear from teams evaluating us:
- Choose KnoxCall if: you need phantom token credentials for AI agents (not just API key forwarding), you're deploying in a regulated industry where HIPAA/GDPR/PCI compliance packs reduce your manual configuration burden, or streaming PII redaction is a real requirement for your use case.
- Choose Portkey if: semantic caching hit-rate is your primary metric and you're willing to handle security separately.
- Choose API Stronghold if: you need a mature eval UI and you're not in a regulated industry with PII redaction requirements.
- Choose Kong AI Gateway if: you're already running Kong for non-AI API management and want to extend the same platform to LLM calls without a separate vendor relationship.
- Choose AWS Bedrock Guardrails if: you're Bedrock-only, you want a single vendor for infrastructure + security, and you don't need the routing flexibility of a multi-provider setup.
We'd rather you choose the right tool than force fit KnoxCall where it's not the right answer. If you're evaluating and want to talk through your specific setup, reach out directly — we'll give you a straight answer about whether KnoxCall is the right fit.