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LLM Gateway Alternatives: A Governance-First Comparison Framework

· 5 min read

"Which LLM gateway should we use?" doesn't have a universal answer, because teams optimize for different things — fastest to adopt, cheapest to run, most observable, or most governable. What is universal is the set of questions worth asking, and the order to ask them in.

This is a framework, not a leaderboard. And it's deliberately governance-first, because that's the axis where products differ most and demo videos reveal least. Routing and provider coverage are easy to compare and roughly commoditized; whether a platform can enforce a policy, prove what it did, and keep sensitive data in your perimeter is where the real divergence — and the real buying decision — lives. DVARA is one option in the field; the point of this post is to help you score the field, including us, on criteria that matter.

The categories on the market

Broadly, the options fall into a few shapes, each with a different center of gravity:

  • Open-source proxies / libraries (e.g. LiteLLM, Bifrost). Fast to start, free to run, huge provider coverage. You operate and secure them yourself, and governance depth — Policy-as-Code, immutable audit, PII enforcement — is usually thin or DIY. Great when routing and provider abstraction are the whole ask.
  • Cloud-vendor gateways (e.g. Cloudflare AI Gateway, Kong's AI Gateway add-on). If you're all-in on one ecosystem, the native integration is tight. The trade-off is gravity toward that vendor and weaker neutrality — and governance that's often coarse.
  • Developer/observability-first platforms (e.g. Portkey, Helicone). Strong on tracing, evals, and prompt management, with a gateway attached. A good fit if your primary pain is visibility; typically lighter on hard enforcement (blocking budget caps, policy denial, PII blocking) and on self-hosting for regulated data.
  • Governance-native platforms. Built around Policy-as-Code, PII/guardrails, immutable audit, agentic (MCP) governance, and self-hosting from the start, with routing and cost as table stakes. The fit when compliance and control are the point. DVARA sits here — and the honest framing is that most of the field started as a gateway and added governance, while a governance-native platform starts from the control requirements and ships the gateway as the mechanism.

No category is "best." They're answers to different questions.

The criteria that matter — governance first

Score any candidate on these, weighted by what your team is actually optimizing for. Governance rows lead deliberately:

CriterionWhat to ask
Policy enforcementPolicy-as-Code that can deny a request (model, tools, region, budget), or only observe?
AuditImmutable, tamper-evident trail of every decision — or just request logs?
PII / guardrailsPrompt & response scanning that can block or redact, in-perimeter?
Agentic (MCP) governanceCan it govern tool calls — approval gates, loop detection, tool-poisoning defense — not just model calls?
Data residency / self-hostingRuns inside your perimeter, or SaaS-only?
Cost controlReal-time attribution and hard budget caps, or dashboards only?
CachingSemantic caching, and does a hit cost $0 and stay PII-safe?
Routing & failoverModel-prefix, weighted, and capability-aware failover — or blind retries?
Provider coverageThe models you use and the ones you might switch to?
ObservabilityPrometheus + OpenTelemetry (incl. GenAI conventions), or a closed dashboard?

A few deserve emphasis because they're where products quietly differ:

  • Enforcement vs. observation. "We show you your spend / your prompts / your traces" is not "we can stop a disallowed call." Hard caps that block and policies that deny are a different capability class than dashboards that inform. → Cost Management
  • Where it runs. SaaS is fastest; self-hosting keeps prompts, policy enforcement, and audit in your perimeter. For regulated data this is often the first filter, not the last. → Self-Hosted LLM Gateway
  • Model-aware governance. A repurposed API gateway can't see models, tokens, or PII. If governance matters, that gap is disqualifying. → Why an AI Gateway, Not an API Gateway
  • Capability-aware failover. Blind failover can retry on a model that can't serve the request. Ask specifically. → Fallback & Failover

A note on MCP and agents

By 2026, governing agent traffic — not just model calls but the tool calls agents make via the Model Context Protocol — is a real axis of comparison, and most serious gateways now offer some MCP support. The differentiator isn't presence, it's depth: whether MCP is governed (approval gates, loop detection, tool-poisoning defense, per-call audit) or just proxied. If you're building agents, weight this heavily; if you're not yet, treat it as forward-looking rather than deciding.

How to actually choose

  1. Write down your top three constraints. Regulated data? Multi-cloud? Tiny ops team? These pick your category before you compare products.
  2. Disqualify on the hard requirements. SaaS-only is a non-starter for some; that filter shrinks the list fast.
  3. Trial two candidates on real traffic. Routing and coverage demo easily; enforcement, PII blocking, audit integrity, and self-hosting only reveal themselves under load.
  4. Weight enforcement over dashboards if control is why you're here.

Where DVARA fits

DVARA is a governance-native, self-hostable AI governance platform: Policy-as-Code that denies, immutable HMAC-signed audit, PII redaction and guardrails, governed MCP for agent traffic, and data residency by self-hosting — with capability-aware routing and failover, real-time cost attribution and hard budget caps, and $0 PII-safe semantic caching as table stakes. It's the right fit when compliance, control, and sovereignty lead your criteria; if your top constraint is "free and OSS with the widest provider list," an open-source proxy may serve you better. Score it against your own weighted criteria using the pillar guide, What Is an LLM Gateway?, as the reference.