YABANIN / Model access & economics
A common path to AI.
Under your control.
Connect your applications and supported agents to local or approved cloud models. Operate the gateway in your infrastructure, set the rules, and see where AI spend goes.
Your Agnostic Bridge Across Numerous Inference Networks.
A governed request pathSelf-hosted
Teams and agents.
One operating policy.
01Your applications & agentsConnect supported clients using scoped credentials.
02YABANIN in your environmentApply configured routes, access controls, and budgets. Record usage and request evidence.
03Your approved model endpointsLocal inference, external providers, or a workload-specific combination.
Explore the architecture →01Apache-2.0 core02Customer-operated infrastructure03Enterprise deployment
Make policy part of everyday use
Give teams access. Give the business visibility.
Approved routes and models
Configure providers, model routes, and fallback rules around each workload. Keep restricted work on approved destinations.
Provider integration →Scoped access and budgets
Use team and agent identities, configured grants, and spending limits to make responsibility explicit.
Agent governance →Cost by task and team
Inspect recorded requests, tokens, cost estimates, latency, and errors. Group analytics by team, task, agent, or supported labels, and export results.
Analytics and price coverage →Evidence for operating decisions
Compare model behavior, inspect policy decisions, and use optional signed request records to trace recorded claims.
Request lineage →Choose how to adopt
An open foundation. A deployment that fits your business.
Apache-2.0 coreExplore the technology
Review the documentation, architecture, and operating model with your engineering team. Core source access is currently by request.
The core license permits commercial use. Enterprise arrangements cover the agreed commercial offering, implementation, and support.
Request core source access →Enterprise · Talk to usDeploy with YABANIN
Work with the product team on enterprise licensing, installation, identity and policy configuration, integrations, training, and ongoing operation.
Scope, commercial terms, and support commitments are agreed around your environment and requirements.
Explore enterprise deployment → Start with a workload you understand
Measure the change before you scale it.
Understand existing AI spend
The offline audit analyzes local request logs and estimates spend using recorded usage and prices. Cache and routing scenarios help identify what to test next.
Explore the offline audit →Include quality in the decision
Compare candidate models with a baseline on representative tasks. Bring accepted outcomes and human review effort into your evaluation alongside usage costs.
Build the business case →The gateway governs traffic routed through it. Your network, client configuration, and tool permissions complete the control boundary. External inference follows the destination and terms you configure.
Put the platform to work
See YABANIN in your operating context.
We’ll walk through model access, task costs, and deployment choices with your business and engineering teams.