Kaya directs AI execution across your existing systems, data, and models, without replacing what already works: every vendor, every model, and your homegrown systems.
How Kaya fits into your enterprise ecosystem.
Kaya is the platform between your AI and your systems of record. It works with your hyperscalers, your enterprise applications, and your partners, and it is model and vendor agnostic.
HyperscalersÂ
Kaya builds iFlows across cloud and model providers while remaining LLM-agnostic.
Result: Execution remains consistent, even as underlying technology changes.
Enterprise Applications
Kaya connects AI into the systems where work actually happens. 

Result: Decisions and actions happen in the flow of work, not outside it.Â
Partners + Integrators
Kaya enables partners to deliver governed, production-ready AI workflows at scale.Â
From data to verified action, governed at every step.
Kaya Intelligence Flows (iFlows) are the execution mechanism that makes the ecosystem operable. Every integration, every model call, every action follows the same governed path – so AI behaves predictably and responsibly at scale.
Partnerships
Kaya on AWS
Kaya deploys inside your own AWS environment, turning AWS’s infrastructure and AI services into production-grade business processes that run the same way every time.
Kaya gives partners and integrators a repeatable way to deploy governed AI across complex enterprises – faster deployments, lower risk, no custom rebuilds.
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CASE STUDY · FINANCIAL SERVICES
Trade-fail resolution, governed and in production.
A global financial-services firm runs trade fail resolutions powered by the Kaya platform, early results showing a 70% reduction in costs.
The Business Problem
Unresolved settlement fails carry direct costs: fines and fees on the failed trades, financing and funding charges, and the operational overhead of resolving them, alongside counterparty exposure.
Visibility typically arrives at or after end of day, once the cost is already locked in.
Without a live, exposure-ranked view, operational attention spreads evenly rather than concentrating on the positions that carry the most risk.
The Solution
The platform continuously evaluates settlement obligations through the trading day and surfaces those failing, or at risk of failing, ranked by dollar exposure, while there is still time to act.
Evaluation is deterministic, driven only by explicit upstream signals: the same inputs produce the same classification on every run.
The platform identifies and prioritizes; the operations team retains the decision, and every state change is timestamped and attributed.
It runs on the firm’s own AWS infrastructure, consuming the firm’s existing data feeds over event stream, APIs, and secure file transfer.
Results
70%
reduction in costs in early results.Client-stated, measured on live data.