Gemini Enterprise Agent Platform vs. Twilio

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

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I have tried other competitors. But I always end up going back to Twilio because I feel like it is dependable, easy to use, and, has competitive pricing. The only time I wouldn't recommend Twilio to someone as if they are completely inexperienced about using webhooks or APIs. Because you can't really just sign up and start using Twilio without connecting it to another platform first.

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• 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

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• Easy to see my team in one place, when they log in and out and what call status they are in.
• Twilio is a simple, user friendly way to log in and out of work activities.
• Excellent services and support.
• The omnichannel feature which allows agents to get request from all channels.

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• Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
• Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
• Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users

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• Control panel. Often, navigating through lists is challenging. I want endless scrolling, not pagination.
• Conversational intelligence service require a Language. I would like it to detect it.
• We would like to have some credit on clients that chose to use their own Twilio account.

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Unless we can get this handled quickly -- less than 1 week -- we will likely switch to another provider who, in my opinion, we'll have to spend close to $3,000 in development time to build a new integration for texting. Our clients need texting and I feel Twilio has failed us miserably.

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Twilio has well documented APIs and examples. There are several tutorials, videos and Q&As regarding their services. So, usability is very good. I must say that advanced knowledge of telephony, API/Programming and error-handling is essential to make good use of Twilio. It's not just plug-and-play unless you are integrated with a system that has all of the programming built for it.

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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.

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Twilio executes what it is designed to do: send SMS messages at scale while providing very good deliverability. I believe that Twilio is very good at what we use for adding SMS messages to our comms strategy. We can see those messages get opened and replied to, which is exactly what we are looking to achieve.

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I have not had to communicate with Twilio support in the last 3 years but my past experience with them has been very positive. They replied to my previous requests promptly and kept me well informed to resolve my inquiries. With their documentation that's available, I hardly imagine why anyone would need to contact support since it's all there in a concise and easy to understand format. It would probably take you longer to type out a support ticket than to just open their doc websites.

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The developer APIs and SDKs are super easy to follow.

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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.

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We evaluated many fundraising-based text-to-give programs and found the subscriptions prohibitively expensive for our small scale and uncertain first few years of development. While we may be willing to invest that kind of money after discovering how things work, we're happy with Twilio now and have no desire to start over.

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Being in South Africa, direct local currency support would be nice

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• It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
• It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
• It'll help you in terms of Security wherein we can use row level security access to authorized persons.

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• We found that associates who had the opportunity to respond to a survey about their assigned job were 37% more likely to return to a job site
• We were able to reduce the number of resources required to manually respond to associates using Twilio Studio, so those resources could have more time to complete other tasks
• We were able to scale the number of associates who received survey messages at least by a factor of 8 without increasing our resource demand

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