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We build and deploy enterprise machine learning via a proprietary platform and expert operators.

Industry leaders call us best in class.
And once upon a time, we only served big tech.

Now we serve you.

Click here for a no-obligation consultation
Endorsement from Industry Leader #1

“They blend best-in-class operating experience honed at Fortune 1000 e-commerce companies with a comprehensive, strategic approach that will help their customers improve their marketing programs by orders of magnitude. I’ve worked with them personally and give them my highest recommendation.

Greg Revelle

CMO for Best Buy, Kohl’s, and Autonation & current CCO for Capital Hill Brands


Economics at Princeton
MBA at Harvard University

Greg Revelle

Our journey in numbers.






Years in Business


Tables Processed


Rows Analyzed


Terabytes of Data Processed


Data Sources


Features Created


Model Iterations
Juney Ham
Endorsement from Industry Leader #2

“These leaders have built the data science and engineering programs underlying some of the most sophisticated brands in the world. And then, just as important, they’ve gone past the science and software to real world application across sales, marketing, and product. More personally, I’ve worked with and known these leaders for over a decade, and they represent some of the smartest, kindest, and value-add focused people you’ll meet.

Juney Ham

COO at, CMO at, Director at Airbnb, and VP at Expedia


Computer Science from the University of Pennsylvania


Epic endorsements from epic individuals.

Endorsement from Industry Leader #3

Distinguished Architect for the Fortune 1 company says work is the “most thoughtful and comprehensive technical work I’ve encountered”.

“Though they produce the most thoughtful and comprehensive technical work I’ve encountered, their individual and organizational humility is what elevates my endorsement to “best in class.” This combination of industry-leading empathy paired with uncanny technology-level expertise results in processes and outcomes that far exceed expectations. Others have said it, but I’ll say it again: I’ve never encountered work of this caliber. They have my strongest recommendation.

Victor Cheng

Distinguished Architect for Walmart Global Technology


Computer Science at Yale University

Victor Cheng
Case Studies

Read some epic case studies.

Major University Chooses to Build Institution-Wide Data Science Plan and Models

The Client

A top-tier U.S. based university with over ten thousand active students.
The Challenge
Despite needing data science to serve students more effectively, one of the most prestigious consulting firms in the world told this client that the school's data could not support machine learning.
The Quote
"This work is the definition of overdelivery -- in all aspects. It's rigor, but it's more than that. It's an act of concern, even love, for our organization and our people like I've rarely, if ever, seen." - VP, Admissions
The Solution

Top US County Selects to Build Data Science Plan and Prototypes

The Client

One of the largest counties in the United States by population, geography, and revenue.
The Challenge
The County possessed a massive trove of disconnected data spread across dozens of services. They wanted to build a machine learning plan, connect and clear their data, and build practical, production ready machine learning models.
The Quote
"In over 30 years of leading large-scale technology initiatives, I have found few partners as dedicated to ensuring customer success as" - Chief Information Officer
The Solution

Global Streaming Service Hires to Increase Engagement

The Client

An international media service with millions of viewers.
The Challenge
Faced with daunting goals, this client asked us to apply a full ensemble of analytical, machine learning, and growth techniques to their business.
The Quote
"You doubled our conversion rate."
The Solution

Publicly Traded Bank Selects to Upgrade Data Science Program

The Client

One of the largest financial service companies in the United States.
The Challenge
They had yet to build a performant set of machine learning models to accelerate their sales and marketing programs via machine learning.
The Quote
"Wing Yew ( CEO) is probably the smartest person I've ever met." - Executive Vice President
The Solution

Industry Leading Ad Agency Hires to Rebuild Machine Learning Program

The Client

A national advertising agency with a client roster featuring globally recognizable brand names.
The Challenge
The agency president wanted a new set of ML applications for clients and an upgrade of their existing algorithms.
The Quote
"We value real partners, especially when it comes to complex data issues. In our work with, we have found exactly that: real partners who truly understand us and the challenges we face, who have legitimate world-class expertise to help us address them in ways that exceed our high expectations, and who are fully committed to always ensuring the work is delivered impeccably." - Agency President
The Solution

Global Consulting Firm Hires to Architect Their Growth Engine

The Client

A nationally recognized, highly rated global consultancy with more than 1,000 staff and hundreds of millions in revenue.
The Challenge
They incubated a fast growing dual sided job marketplace to supply contractors for clients and wanted deep automation to accelerate out of painful, expensive manual processes.
The Quote
"Thank you will not suffice... I've been growing and changing businesses using technology for close to 30 years. I have never traveled to this point with a partner and been so certain that the set of solutions is 'right,' nor have I come to this point having enjoyed the journey so completely." - Managing Director
The Solution
Eric Lynch
Endorsement from Industry Leader #4

The head of science and technology for AWS marketing — a leader over hundreds of technical staff, calls our leadership “the rare real deal”.

“I had the opportunity to work extensively with both Kirsten (CPO) and Wing Yew (CEO) at Amazon. I can confidently say they both are some of the sharpest people I have ever worked with, and as a pair are basically a force of nature. In particular, their ability to simultaneously envision the future and then actually deliver on that vision, I believe, is unparalleled. They both have my complete trust, and I continue to seek them out for advice and council. In an industry so full of jargon, hype, and empty promises Kirsten and Wing Yew are the rare real deal.

Eric Lynch

GM/Head of Science and Technology at AWS and VP Global Franchise Ecosystems for EA


The University of Alabama, MBA, MIS

We offer end-to-end data science delivery.

If you’re a visionary who wants to introduce data science techniques into your organization, we partner to help you lead the way. If you have an ambitious roadmap and an overworked data science team, we are an extra set of hands equipped with cutting edge tools to deliver on your priorities.

Data Science Roadmaps

You’ve read enough generic articles about ML in your space. It’s time to map out what’s possible.

Our “Universe of Opportunity Map” combines your data and insight with our experience across dozens of verticals into an ultra high fidelity roadmap.

More than just a stack ranked list of applications of machine learning, we evaluate and recommend data sources for models as well as estimate likelihood of successful prediction and return on investment.

Best of all, no need to clean or standardize your data for us to complete this review and recommendation — our systems and team will handle the investigating and document construction from end-to-end.

Data Cleaning and Labeling

Years of mislabeled inventory bogging down your analyses? A dozen disconnected data sources? A mountain of documents that need to be categorized? We can help with that.

No data size is too big, no data mess too messy — that’s our motto. Take a deep breath; we’ve served over a dozen companies with data cleanliness and orderliness ranging from “we still have work to do” to exceptionally disorganized and undocumented.

As any good practitioner knows, cleaning and preparing data is (at least) 80% of the machine learning process. We’re here to not just help, but own as much of the data hygiene process as you are comfortable.

Predictive Machine Learning Models

We’ll deploy’s proprietary platform with a team of operating experts (think: Amazon veterans) to build a fleet of high performance models for your business. At prices that are less than 50% of the industry average, but speeds 2x to 4x faster than the standard, we get you performant models in the span of weeks — not months.

As a reminder, no need for pristine data — and certainly no need to clean any data before we begin our build process. We guide the project from end-to-end, including use case identification, model definition, data sharing and preparation, feature engineering, training, deployment, implementation, testing, impact measurement, monitoring, and retraining.
Endorsement from Industry Leader #5

The CIO for one of the largest counties in the United States by population, budget, and geographical size celebrates expertise and commitment.

“In over 30 years of leading large-scale technology initiatives, I have found few partners as dedicated to ensuring customer success as Their efforts to add value, above and beyond contract agreements, is a stunning commitment to ensuring our pursuits were their personal ambitions to achieve. Their grit and commitment to succeed is matched by their remarkable differentiated expertise, determination, and problem solving capacities. I count it a privilege to engage them on any data mining AI/ML adventures we take on, as well as trust them as market explorers for new technology assessments.”

Rick Napolitano

Chief Information Officer for one of the largest counties in the United States by budget, population, staff, and geography

Anne Arundel County, MD
Click here for a no cost consultation

Predictive machine learning models (a shortlist).

Predict key events and attributes that improve efficiency, agility, and scalability of your decisions. We work with you to design custom models based on your unique data and organizational goals, and partner with your team to integrate them into your existing architecture. We deploy applications within months, not years – and at a fraction of the price of hiring an in-house team.

Predictive models can be used in a wide variety of contexts including:


Lifetime Value Models
A lifetime value machine learning model forecasts the future value of a customer to a business. It can take into account factors like the customer’s likelihood to make future purchases, the amount they are likely to spend, and the length of time they are likely to remain a customer. It seeks to answer the question: “How much is a user worth over their lifetime?”.

Lead Scoring Models
Lead scoring models use lead behavior and demographics to predict their likelihood to complete a conversion event (e.g., a purchase). We do this by assigning a quantitative score to each lead, with higher scores indicating a higher likelihood of conversion.

Customer Retention Models
A customer retention model forecasts a customer’s likelihood to continue doing business with a company over a given time period. It seeks to answer the question: ‘How long will the customer stay with the company?”

These models can use data on customer behavior, demographics, and other specific engagement factors, including customer’s past purchases, their engagement with the company’s marketing efforts, and their satisfaction with the products or services.


Outreach Timing Models
Outreach timing models predict the optimal time to contact potential customers in order to maximize the likelihood of success. They seek to answer the question: “When should I reach out to a customer for maximum impact and efficiency?” These models use data like past response rates to marketing and sales efforts, time zones, and preferred communication channels.Offer or Incentive

Affinity Models
These models predict the degree to which offers (or incentives) are likely to be effective for a given customer. An offer affinity model might predict a customer is more or less likely to respond to a discount on a product they have purchased in the past, rather than a free trial of a new product. At their foundation, they seek to answer the question: “How effective is each promotion or offer for this customer?”

Purchase Propensity Models
A propensity model can predict the the next products a customer will purchase. Advanced applications might prioritize moving customers to a preferred action based on its relatively high ROI and low cost as compared to other available actions. This model, and models tangential to it, seeks to answer the question: “Of available products, which one is the customer most likely to purchase?”

Content Engagement

Media Recommendation Models
A media recommendation model recommends videos, articles, or songs based on a user’s stated or implied goal. These models often use data like the customer’s past interactions with media content, their demographics, and their engagement with the company’s marketing to predict which content is relevant; they often look at the behavior of other, “look alike” customers as well.

Intervention Recommendation Models
An intervention recommendation model recommends “interventions” (or actions) that may positive impact user or customer experience. These models can radically improve the ROI of high cost touch allocations (e.g., a 1:1 sales call) as well as the full system of interventions across the full customer population.

Product Recommendation Models
A product recommendation model predicts which product should be suggested to a customer given a set goal. Classic applications of this model include search results in customer shopping experiences as the now ubiquituous checkout widget that highlights products other customers were interested in.

Meet the leadership.

“They blend best-in-class operating experience honed at Fortune 1000 e-commerce companies with a comprehensive, strategic approach that will help their customers improve their marketing programs by orders of magnitude. I’ve worked with them personally and give them my highest recommendation.” – Greg Revelle, CMO of 3 Fortune 500 Companies (Best Buy, Kohl’s, Autonation) and CCO for Capital Hill Brands
Wing Yew Lum
Leads the organization. Experience includes fifteen years leading growth, product and technology functions at Amazon (including Alexa and Marketplace), Expedia (global marketing technology), and zero-to-one startups. Led teams driving data science and engineering, technical product management, and growth marketing. Delivered over a billion dollars in statistically validated lift over career. Attended the University of Washington, where he led the honors college and graduated with dual degrees. He lectures there now on strategy. Say hi at wingyew[at]!
Kirsten Lum
Oversees all aspects of data science, product, and engineering. A 9 year analytics veteran of Amazon and Expedia, she led dozens of leaders across core applied science, economics, as well as experience instrumentation and data architecture at global scale. Directly managed and led one of Jeff Wilke's core science and economics teams at Amazon, where she was selected for Amazon's top tier leadership program (500 out of ~1,500,000 employees worldwide selected each year). Graduated from the University of Washington with Distinction and now teaches at their Master's of Business Analytics degree program.
Phil Gallo
Leads sales, operations, and account management. Led applied R&D globally for a 1,000+ person solutions consultancy spanning nearly a dozen verticals. Prior to that, led product delivery for one of the first open source software projects at the Pentagon. Had the privilege of serving as product leader for dozens of engineers at Microsoft, overseeing the optimization of the purchase funnel for the Xbox. A New Yorker at heart, he lives in Seattle with his four beautiful kids and wife.
Chris Gutierrez
Chief Scientist
Responsible for reviewing's approach to science as well as recommending next generation machine learning and engineering approaches and tools. Experience spans LinkedIn, Airbnb, Mesosphere, Google, and Expedia where he led delivery of multiple company-wide models spanning recommendation engines, image recognition, auction optimization, financial prediction, fraud detection, and customer segmentation. Led science and analytics for multiple institutions as the Principal Scientist to Chief Scientist.
Garrett Fiddler
Senior Scientist
A graduate of Yale University, Garrett has been passionate about the intersection of coding and language for nearly 15 years, with multiple years solving data science problems across diverse verticals, including insurance, higher education, marketing, and anomaly detection. Garret leads bespoke machine learning projects, especially those including natural language processing, sparse datasets, or unusual operating conditions.
Shujie Xiu
Senior Scientist
A research data scientist with nearly a decade of work experience spanning everything from Meta (Facebook) to Progressive Insurance, Shujie has deployed dozens of advanced analytics solutions into production at massive enterprise scale and impact. Problems solved span everything from determining employee attrition to distribution of service cases to demand forecasting all the way over to product recommendations and pricing predictions. Shujie holds a Master's Degree in Computational Data Analytics from Georgia Tech.
Sheffield Leithart
Engineering Manager
A senior engineer and design technologist, Sheffield is a veteran of Amazon Marketplace and Amazon Web Services (AWS), as well as a host of other technology startups. A national merit scholar, Sheffield left the University of Idaho to join the Zac Brown band as their tour photographer. He's passionate about engineering, stories, and community. He lives in Idaho with his wife and four children.
Julia Hannula
Research Lead & PM
Julia will quickly become a familiar face as she drives the timely delivery of machine learning projects, including deep research into the use cases, system architecture, and organizational goals that inform impactful applications. She brings with her over 12 years of experience in healthcare administration, and graduated cum laude from Trinity Western.
Luke Perley
Senior SDE
Responsible for MLOps and back-end architecture for our proprietary machine learning technology, Luke specializes in building scalable, flexible solutions that integrate seamlessly with the unique infrastructure each of our clients use. Luke graduated from the University of Idaho with a degree in Computer Science.
Jason Pamer
VP, Strategic Partnerships
Responsible for building the next generation of’s relationships. Has created partnerships across a bevy of verticals, including with industry leaders (e.g., Jada Pinkett Smith, Steph Curry, and Lionsgate). Founded the award-winning Sypher Studios in Los Angeles and was an early investor in, a technology suite of tools (incl. focused on revolutionizing cloud-based film tools.
Myron Chiu
Engineering Partner
A self-proclaimed human embodiment of Stack Overflow and Google Search, Myron is a full-stack engineer with a decade of experience. He was the first employee for a 9-figure app analytics platform ($45M raised and hundreds of employees), and has served as a full stack engineer for multiple startups. At, he continues to use his pattern recognition abilities with Stack Overflow and Google Search as we build the next generation of data and ML-focused applications alongside his wife and cat.
Erin Torgerson
Data Scientist
A data science leader trained at the University of Washington, Erin has built and deployed high performance models in multiple industries, including higher education, non-profit donor management, marketing, and content engagement. A Washington native, Erin is also a certified Occupational Therapy Assistant and yoga instructor.
Victor Cheng
Technical Partner
Advises on solution architecture, system design, and technology selection. Served in roles as substantial as Distinguished Architect for Walmart Global Technology to CTO of a fast growing identity resolution software company which was bought (also by Walmart Global Technology). Graduated from Yale University with a degree in Computer Science.
Doug Treff
Provides strategic guidance on a wide variety of topics, including vision and operations. Current CFO of World Vision and board member of publicly traded firm Crox. Former CFO for multiple publicly traded firms. Doug graduated with an MBA from Wharton.