If you’re in the market for an AutoML platform, you’ve likely encountered the plethora of options. One google search will show you the innumerable AI and analytics tools out there, with offerings from startups to giants like Amazon, Microsoft, Google, and more.
Many businesses find themselves comparing H2O.ai and Zams when looking for the right AutoML solution. In this article, we’ll compare and contrast the two in both application and use case so you can make an informed decision to help empower everyone in your organization.
Overview
Here’s a high-level overview of Zams and H2O.ai:
- H2O.ai is designed for larger enterprises and offers a set of features at a higher price point, and is geared to a more technical audience. H2O.ai is a top contender in the traditional AutoML space, and a leading rival to the likes of Google AutoML and Azure AI. As H2O writes, they’re focused on offering “sophisticated AI technology that enables businesses, government entities, nonprofits and academic institutions to make, operate and innovate with AI."
- In contrast, Zams is built for speed and accessibility. It’s a no-code AI platform that anyone can use: affordable, fast to deploy, and designed for non-technical teams. Instead of months of setup or specialist data teams, Zams lets you build predictive models on tabular data in minutes. The result: AI that’s simple, practical, and within reach of businesses that need leverage now, not later.
Let's start comparing.
Price
Most other solutions require a high investment just to get started. Some start low and quickly become costly as more training is added.
H2O.ai isn’t very open about their pricing, requiring you to request a quote. That said, we dug through IBM documentation to find an H2O AI pricing list, which features subscriptions ranging from $300,000 (a 3-year subscription) to $850,000 (a 5-year subscription with GPU).
This implies that an H2O.ai subscription will be even pricier than hiring a data scientist at US-level market rates. That said, if a company is spending six-figures on AI software, they’ll probably hire data scientists to use it anyway, so affordability is out the window with H2O.ai.
Additionally, one review listed that while the H2o.ai version is great for a trial, it’s quite expensive and seems to be focused only on enterprises, and that a version for SMEs or smaller businesses would be ideal.
Zams makes machine learning accessible to every business. Our pricing is simple - knock a couple zeros off H2O’s plans and you’re in Zams territory.
Getting started takes minutes, and we scale with you as your needs grow. We back it up with an opt-out period, so you only stay if we deliver real value. If you’re not getting leverage, we haven’t done our job.
Clean and Clear UI
H2O.ai is convenient and easy to use, with many reviewers praising its familiar interface.
Zams carries a similar easy-to-use interface. It was designed to provide a user experience that can easily be understood and used by any entry-level Business Analyst. Teams can easily share results or provide customer-facing predictions with the models they create.
Support from a Data Scientist
Oftentimes, when users sign up, they’re left alone to their own devices. We aren’t sure if that’s the case for H2O.ai - they may offer the support from a data scientist, but it isn’t entirely clear or upfront in any of their product listings.
Our customers enjoy guidance from our in-house Data Science team. Upon sign-up, our customers are scheduled for onboarding with their Product Specialist and Data Scientist.
Our team is then able to sync with the data sources, enrich the data so it is fit for machine learning, and push the data back to wherever the customer wants to see it. We then schedule another time to show the customer the work that was completed and how to get their results moving forward.
Ongoing check-ins are also scheduled at that point. Any time a new use case comes up, our customers can schedule a new time to speak with their assigned team.
Data Cleaning is also included, and that includes: Data Cleaning, Merging, Enrichment, Statistical work and Applying Business Logic. This ensures that organizations get the kind of success they need.
Extras
Integrations
Both H2O and Zams have invested heavily in integrations, especially in comparison to tools like Power BI, which has relatively few integration options.
H2O’s integrations are highly technical, covering areas like Instance Life-Cycle Management, API clients, scoring, and storage. What’s apparently absent are easy-to-use, simple integrations like Zapier, HubSpot, or Salesforce.
Zams connects to the tools you already use, whether it’s through a simple REST API, Zapier for no-code users, or direct integrations with platforms like Airtable, HubSpot, Shopify, Snowflake, and more. From analytics to CRMs, storage to spreadsheets, Zams unifies your stack into one command center. And the list keeps growing.
Dashboards
If your key goal is creating Business Intelligence dashboards, then you might want to check out our guide on Power BI. Neither H2O nor Zams are primarily focused on dashboards, though they both offer visualization features.
Features
Both H2O and Zams offer sharing features, but H2O report sharing functionality seems to be quite limited, and it doesn’t seem possible to access any public AI reports.
With Zams, a shareable report can be made in a single click, accessible to anyone, anywhere, even without an Zams account.
Conclusion
When comparing H2O and Zams, there’s no clear winner, per se. If financial resources are unlimited, and features like image processing are needed, then H2O is likely the way to go.
We believe everyone should be able to harness the power of ML to support their businesses. If you’re looking for advanced analytics and AI functionality, but aren’t willing or able to shell out up to a million dollars, then Zams is the way to go.