If you work in a regulated organisation, you have probably seen this play out: leadership wants AI in production, security wants an audit trail, and the team in the middle has two options. Either ship something fast with no governance — shadow tools, no DLP, no audit log — or wait twelve to eighteen months for an enterprise platform to get procured and approved. Neither is good.
Most of the tools available to bridge that gap fall into one of three camps:
Too complex. LiteLLM, Kong, Azure APIM. Good tools, but built for teams that already have DevOps capacity and a budget for AI infrastructure.
Too expensive. Enterprise AI governance platforms with six-figure contracts.
Too cloud-dependent. Require sending your data to a third party, which is a non-starter under data residency rules in finance, healthcare, and the public sector.
I have been working on a small Apache-2.0 project called Synapse AI Gateway that aims at the space between those options. docker compose up brings the whole stack — postgres, backend, admin console — and you have it running in under five minutes. Governance controls run on every inference request before they ever reach a model.
GitHub:
If your organisation is staring at the gap between "ship AI now with no controls" and "wait two years for the enterprise platform," this is meant for you.
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