Comparison · Last reviewed June 2026
routeur.ai vs Portkey
Portkey is an LLMOps platform built for AI engineering teams: gateway, observability, prompt management. routeur.ai is built for the company around that team — every application and every employee through one governed doorway, fully hosted on Google Cloud. Below: the full capability matrix, the three questions that decide it, and what switching takes.
The short version
routeur.ai or Portkey: which fits your team?
Both sit between you and the model providers — but they answer different questions. If yours sounds like the left column, you're done looking.
routeur.ai is the answer when…
- You're buying governance for the organisation — employees and applications under one policy set — not tooling for one team.
- Data residency on every plan, from the first seat — not at the end of an enterprise sales cycle.
- The audit trail must stand up as compliance evidence: append-only and tamper-evident, not just request telemetry.
Portkey fits when…
- Your buyer is an AI engineering team that wants prompt versioning, evals hooks and request-level traces inside the gateway.
- A US-hosted SaaS fits your data posture, or you're prepared to negotiate a dedicated deployment for residency.
Side by side
routeur.ai vs Portkey: the full matrix
Capability by capability, summarised from Portkey's own documentation — so you can check every cell yourself.
Portkey's column is summarised from
their public documentation,
last reviewed June 2026.
Spotted something out of date?
Tell us and we'll fix it.
The difference
What Portkey doesn't give you
Portkey goes deep for the team building with LLMs. routeur.ai goes wide across the company using them — and compliance is graded on coverage, not depth.
One doorway for people and apps
The same DLP, shields, budgets and audit trail govern your applications' API traffic and your employees' chat usage. An LLMOps platform covers the first; the second is where most of a company's data risk actually lives.
Residency without negotiation
Every plan runs fully hosted on Google Cloud — prompts, metadata and audit trail, with data residency included from the first seat. No enterprise tier to reach, no dedicated-deployment conversation, no sales cycle between you and compliance.
Evidence, not just observability
Traces tell engineers what happened; auditors need proof nothing was altered. routeur.ai's append-only, tamper-evident trail of every routing and policy decision maps onto the EU AI Act's logging obligations.
Decision framework
Three questions that decide it
Put these to any gateway you're evaluating — Portkey included. They're the ones your security, finance and compliance teams will ask anyway.
Are you governing a team or the company?
LLMOps tooling makes one engineering team faster. Governance has to cover every team — including the ones who will never open an API console.
Apps route through the gateway; everyone else uses the governed chat workspace. One policy set, one budget view, one audit trail across all of it.
Which plan gets you data residency?
If residency only arrives with an enterprise negotiation, your compliance timeline belongs to a sales cycle.
Every plan, from the first seat — fully hosted on Google Cloud, with prompts, metadata and audit trail included. Nothing to negotiate.
Is your audit trail telemetry or evidence?
Request logs answer engineering questions. Regulators ask a different one: can you prove the record is complete and unaltered?
Append-only, tamper-evident records of every routing and policy decision — built to be handed over, not just queried.
Switching
Switching from Portkey takes an afternoon
Both gateways are OpenAI-compatible, so evaluation is cheap: point one route at routeur.ai, keep the rest where it is, and compare the dashboards by Friday.
Bring your provider keys
Add your OpenAI, Gemini, DeepSeek and Anthropic keys in the dashboard. They're encrypted at rest and never appear in your application code again.
Change two lines
Point your existing OpenAI client at api.routeur.ai/v1. No new SDK, no rewrite — your business logic stays byte-for-byte identical.
from openai import OpenAI
client = OpenAI(
api_key="sk-your-openai-key"
)from openai import OpenAI
client = OpenAI(
api_key="rtr-your-routeur-key",
base_url="https://api.routeur.ai/v1"
)Route a slice, read the receipts
Send 5% of traffic through, switch on DLP and prompt shields per route, and watch the dashboard report savings versus going direct — in real time, per request.