Landscape · AI gateway and LLM ops platform
Portkey alternatives: the AI gateway landscape, honestly
If you are shopping for a Portkey alternative you are shopping for an AI gateway, and there are five credible ones. This page lists them, says which reader each suits, and then makes the case that a meaningful number of people searching this term have diagnosed the wrong layer.
What Portkey is genuinely good at
Portkey is a mature commercial gateway. If many applications in your company call many model providers and you want one managed place for routing, fallbacks, caching, rate limits and spend attribution, that is precisely the product category and Portkey is a serious entrant in it. Nothing below is a criticism of it.
Why people look for something else
- You want to self-host
Data residency, procurement policy or a plain preference for infrastructure you operate. This is the most common reason we hear, and it points at a specific subset of the list rather than at the whole category.
- You are consolidating vendors
A gateway is often adopted by one team and then has to survive a platform review. If you already pay for edge infrastructure or an API gateway, the question becomes whether AI traffic can ride on what you have rather than adding a vendor.
- Your requirement turned out to be narrower than a gateway
Some teams adopt a gateway for one capability — provider abstraction, or spend caps, or request logging — and later find a smaller tool covers it. Buying a full gateway to get one feature is a real and avoidable cost.
- The problem you have is not in the request path
This is the one worth pausing on. Teams reach for a gateway when the incident that triggered the search was an unreviewed MCP connector, an agent hook running shell commands, or a skill nobody approved. A gateway cannot see any of those, so switching gateways will not help. See below.
The ai gateway and llm ops platform landscape
An open-source SDK and proxy exposing a single OpenAI-compatible interface across a large set of model providers, with virtual keys, budgets and spend tracking.
pick this ifYou want provider abstraction and per-team spend limits without a commercial vendor relationship, and you are willing to run and upgrade the proxy yourself.
A gateway that proxies model requests through Cloudflare's edge, adding analytics, caching, rate limiting and logging with a base-URL change.
pick this ifYou are already on Cloudflare and want AI traffic handled like the rest of your traffic, with close to zero integration work.
A unified API and routing layer across many model providers, positioned around access and routing breadth rather than around enterprise policy.
pick this ifYour primary need is reaching many models through one credential and one interface, and you want to move today rather than run a procurement.
AI-specific capabilities layered onto an established API gateway, so model traffic is governed by the same platform as the rest of your APIs.
pick this ifYour platform team already runs Kong and would rather extend an owned control point than introduce an AI-specific vendor.
An open-source LLM observability layer with a proxy integration path, positioned around logging, monitoring and cost visibility for model calls.
pick this ifWhat you actually wanted from a gateway was visibility — which requests, which cost, which latency — rather than routing and failover.
Provider SDKs called directly, with OpenTelemetry's GenAI semantic conventions used to emit spans into the observability stack you already run.
pick this ifYou call one or two providers, you already have an observability platform, and a gateway would add a hop and a dependency to buy you a dashboard you can already build.
Why Vincosha is not on that list
the honest part
Vincosha is not on that list, and putting it there would be the dishonest move that makes these pages worthless. We do not route model traffic, do not do provider failover, and are not a caching layer. If your requirement is a gateway, buy one of the five above and we would rather tell you that than waste your evaluation cycle.
The adjacent problem, and whether it is yours
The reason we publish this page at all is the fourth switching reason above. A gateway sits in front of the *model* — every inference request passes through it, which is what makes it good at routing, caching and cost attribution. Vincosha sits in front of the *artifacts*: the skills, rule files, hooks and MCP connectors an agent loads before it ever constructs a request.
That difference decides which incidents each product can see. A malicious hook that reads `~/.aws/credentials` and posts them to an attacker's endpoint makes no inference call, so it never reaches a gateway. A poisoned MCP tool description is read by the model as instruction, but it arrives over the host's connection to the server rather than through the completion path. A skill that quietly tells an agent to skip a review step is invisible to anything watching prompts and responses.
The test is simple and you can run it without talking to anyone: write down the incident or the audit question that put you on this page. If it is phrased in terms of requests, models, latency or provider outages, you want a gateway. If it is phrased in terms of what an agent was allowed to load, who approved it, which version was running, or what it could reach — a gateway is architecturally in the wrong place, and no amount of switching between the five will change that.
Where both are true, and it increasingly is, they compose rather than compete: the gateway governs the request path, and Vincosha governs what shaped the request in the first place.
Deciding
- Do you need to reach many model providers through one interface?
- Yes — a gateway or proxy. LiteLLM if self-hosted and free matters most, OpenRouter if breadth and speed matter most, Portkey or Kong if you want a managed platform with a support relationship.
- Do you mainly need to see and cap what AI is costing?
- Visibility alone is a smaller purchase than a gateway. Helicone or your existing observability stack via OpenTelemetry's GenAI conventions will cover it. Attribution *below* the request — per session, per artifact version — is a different join and no proxy has the data for it.
- Is your AI usage mostly vendor agent tools rather than code you wrote?
- Then the gateway question is largely moot: Claude Code, Copilot and Cursor do not route their traffic through your proxy, and your exposure is the artifact layer underneath them.
- Was the trigger for this search a security incident?
- Read what the incident actually involved before buying. If a connector, a hook, a rule file or a skill appears anywhere in the timeline, a gateway would not have caught it and will not catch the next one.
Frequently asked
- What is the best open-source Portkey alternative?
- LiteLLM is the usual answer for provider abstraction and budgets, and Helicone if what you wanted was observability rather than routing. Both are self-hostable, which is the most common reason people leave a managed gateway. Which is 'best' depends entirely on whether your requirement is routing or visibility.
- Do I need an AI gateway at all?
- If you call one or two providers from a handful of services and already run an observability platform, quite possibly not — direct SDK calls instrumented with OpenTelemetry's GenAI semantic conventions cover a lot of it. A gateway earns its hop when provider fragmentation, failover or centralised spend policy become real operational problems.
- Is Vincosha a Portkey alternative?
- No. We do not proxy model traffic. We govern the artifacts AI surfaces load — skills, rules, hooks and MCP connectors — which is a layer a gateway never sees. Many teams run both, and neither constrains the other.
- Can a gateway stop prompt injection?
- It can inspect prompts and responses, which catches unsophisticated attempts and is worth having. It does not see the injection vectors that matter most for agents — poisoned tool descriptions, malicious hooks, unreviewed instruction files — because those never traverse the model request path.
Check every one of these yourself
This landscape was last checked against each vendor's own site on 2026-07-26. It asserts no feature, price, version or benchmark for any product on it, including ours — those change, and we cannot verify them from here.