The Gemini Enterprise Agent Platform is a fully-managed, unified environment designed for the development, orchestration, and governance of Autonomous AI Agents. The platform consolidates AI Studio, Agent Builder, and a diverse Model Garden to support the creation of complex, multi-agent systems grounded in enterprise data and business logic.
$0
Starting at
Heap
Score8.1 out of 10
Small Businesses (1-50 employees)
Heap is a web analytics platform captures every user interaction on web iOS with no extra code. The tool allows you to track events and set up funnels to understand user flow and dropoff. It also provides visualization tools to track trends over time.
$0
per month
Pricing
Gemini Enterprise Agent Platform
Heap
Editions & Modules
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Free
$0
Up to 10k sessions/month
Growth
Starting at $3,600 annually
Up to 300k sessions/year
Pro
Contact Heap Sales
Custom sessions per month and unlimited projects
Premier
Contact Heap Sales
Custom sessions per month
Offerings
Pricing Offerings
Gemini Enterprise Agent Platform
Heap
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
Optional
Optional
Additional Details
Pricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
Heap pricing is based on session volume. A session is a period of activity from a single user on your app or website. It can include many pageviews or events.
we used Vertex AI on our automation process the model very useful and working as expected we have implemented in our monitoring phase this very helpful our analysis part. real time response is very effective and actively provide detailed overview about our products.this phase is well suited in our org. this model could not applicable for small level projects why because this model not needed for small level projects and without related resource of ML this model not useful. strictly on non cloud org not suitable means on pram not suitable
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Scenarios when Heap was well suited: It is when a user claims that he encountered a bug without giving us the details of the error message. Scenarios where it is less appropriate: Its when we try to capture user interaction in our mobile app
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Vertex AI comes with support for LOTs of LLMs out of the box
MLOps tools are available that help to standardize operational aspects
Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
It's a great platform. I'm glad that one of our product managers introduced it because it has allowed us to create all kinds of new functionality. We're not only able to create a better product experience from our communications because of Heap, but we're also able to generate all kinds of helpful analysis.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
On a scale from 1-10, I find Heap to be incredibly user-friendly and easy to use. I enjoyed the training videos available and was quickly able to pick up how to create events and reports to track user interactions on our product. I would recommend Heap for its usability first and foremost.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
I've never run into any issues with Heap's availability, Heap is always there when I need it. I haven't run into any issues like application errors or unplanned outages during my 2+ years of using Heap. Each and every time I log in to Heap I have a completely functional experience
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Heap doesn't affect page load times considerably nor has a large impact [on] our overall score, as far as page loading times inside of the tool its pretty reliable to retrieve data as much as "instant" that it can be the delay seems to be on data getting tracked into the servers to be read but it's not significant.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Heap support has allowed us to troubleshoot and test a lot of different items. Their support team is always helpful and friendly, even when we come to them with the most complicated questions. I think this greatly improves the value proposition of the product because their support team is knowledgable and friendly.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
The implementation was smooth and easy. The Heap team helped us with implementation and it went great! Within a few weeks, we were fully up and running and utilizing the platform to its full capability. This is an additional thing that has made this platform so great and we couldn't recommend it enough.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's feature-set. This makes it suitable for bigger customers that have the capital and time to spend on a bigger project that is well researched and not quick to market like some of the other options that feel like a light-version of this.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
Heap offers a ton of functionality on a single platform.It also has an smart data science layer to offers suggestions for next steps in the analysis, allowing us to explore alternative paths we may not think to take. The low-code option for updating data is appealing, and there is a lot of automation with minimal engineering effort.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The most challenging part of using Heap in a growing organization is the naming and structure in which reports and dashboards are organized. I work within the marketing department and our Heap leader internally works within the IT/Product department, which makes it challenging because we often don't speak the same language, so the learning curve has been steep without any specific use-case examples to leverage online.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info