What is Cyris?
It started with one core principle: If you properly harness the past, you can accurately predict the future.
Imagine if every impression from every media investment Arm Candy has ever managed could be harvested, synthesized, and analyzed across hundreds of advertisers across every industry, vertical, and variable imaginable. Now imagine filtering that intelligence through every relevant dimension, layered against advertiser business data, sales, revenue, leads, store performance, to identify the statistically probable media investments most likely to drive those outcomes.
We made “what if” a reality. Welcome to CYRIS.
150+
Advertisers
80+
Channels
30+
Unique DSPs
60+
Industries
60+
Dimensions
How CYRIS Works
Built from Arm Candy’s proprietary historical investment data across traditional, digital, and retail media, CYRIS continuously studies the correlation between media investments and business performance.
Powered by advanced AI applications, algorithms, and complex pattern recognition, CYRIS enables our teams to evaluate countless realities, model potential outcomes, and engineer media investment strategies built around what is statistically most likely to perform.
The Future of CYRIS
With every investment managed, every impression served, and every outcome analyzed, CYRIS becomes smarter, faster, and more predictive.
As CYRIS continues layering in advertiser-specific business data, historical business performance, market conditions and macro-economic variables for advanced correlation assessment and application, the intelligence becomes increasingly personalized to every advertiser, industry, client archetype, and business challenge it supports.
Not just analyzing the past. Not just measuring the present.
But helping predict how your business is most likely to perform across various investment levels and mixes.
We may never perfectly predict the future. But we’ll be pretty damn close!
The Future of CYRIS
CYRIS continues to get more and more powerful with every media investment we manage, enhancing our predictive modeling possibilities, creating the opportunity for AI applications and — ultimately — an intelligence technology built to decipher which media investments will yield the highest returns across any outcome imaginable.
As we build the ability to layer in each client’s data directly, this will allow us to personalize each analysis and best predict the future and expected return on investments from various scenarios before we activate.
When we also layer in the ability to ingest client data — such as historical sales performance, market-level information and other data sets — into our predictive algorithm, we should be able to accurately forecast outcomes to better estimate the expected return/results from various scenario plans.
We may not be able to predict the future — but we’ll be pretty damn close.


