

Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Cohere's Embed English model took less time to embed than OpenAI's embedding ada-002 model.
Cohere helped us with all three aspects: money is saved, time is saved, and we needed fewer resources to meet our end goals.
The product offers a significant return on investment through its scalability and integration capabilities.
My customers have seen returns on investment through increased efficiency, automated calculations, improved accuracy in pricing, and reduced staffing needs due to the automation.
The support quality depends on the SLA or the contract terms.
The community access is weak, which limits the ability to engage in discussions and find documentation and examples of similar cases effectively.
I would rate the technical support of IBM Watson Studio a solid ten out of ten.
We don't observe many scaling problems because it's an enterprise application.
Watson Studio is very scalable.
I have had a chance to communicate with the technical support of IBM Watson Studio, which has been responsive and helpful.
I rate IBM Watson Studio seven out of ten for scalability because while it scales, it requires significant resources to do so, making it expensive compared to some competitors.
We haven't had any issues to escalate to Cohere's support because reranking is an optional feature in our product, and we haven't seen any significant issues so far.
Expertise in optimization is necessary to manage such issues effectively.
I find IBM Watson Studio to be quite robust, with minimal downtime and great support regarding stability and reliability.
We want such features because when chatting with clients, we can demonstrate that employing Cohere's reranking model significantly improves results compared to not using it.
Because it does not have extensive understanding of Oracle functionalities in ERP, it sometimes gives wrong results or the confidence score is lower than desired.
During the embedding process, measurable metrics are not visible.
The platform is associated with a complicated setup process and demands heavy hardware, making it expensive to scale.
One area that could be improved is the backup and restoration of the database and the overall database configuration.
I wish learning IBM Watson Studio could be easier and more gradual, as it is a complex task.
My experience with pricing, setup cost, and licensing is that it is expensive to use all Oracle services.
Cohere's pricing, setup cost, and licensing are better.
The prices are competitive compared to competitors.
IBM Watson Studio is considered rather expensive, with a rating of six or seven.
This makes it very easy to find and use the catalog to determine whether existing functionality is already implemented, preventing redundant implementations.
Cohere has positively impacted my organization by helping our customers work more efficiently when creating requests, and the embedding results are of very high quality.
I noticed a 10% improvement in my log system after using Cohere.
This capability saves a significant amount of time by automating processes that typically involve manual work, such as data cleaning, feature engineering, and predictive analytics.
I believe the AutoAI features of IBM Watson Studio have significantly helped in my data projects by automating model selection and hyperparameter tuning.
It integrates well with other platforms and offers good scalability.
| Product | Market Share (%) |
|---|---|
| Cohere | 1.3% |
| IBM Watson Studio | 1.5% |
| Other | 97.2% |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 1 |
| Large Enterprise | 5 |
Cohere provides a robust language AI platform designed for efficient implementation in various domains, offering advanced features for automation and data analysis.
Cohere delivers a scalable AI language model that facilitates automation in data-driven environments. Highly adaptable to industry-specific requirements, it supports tasks such as text generation, summarization, and anomaly detection. This flexibility, along with its integration capabilities, makes it valuable for tech-savvy users seeking seamless AI solutions.
What are the notable features of Cohere?
What benefits should users consider in reviews?
Cohere sees significant use in finance, healthcare, and marketing, enabling precise data analysis and strategic insights. In finance, it assists with detecting market trends, while in healthcare, it supports clinical documentation and research analysis. Marketing uses include content creation and consumer sentiment analysis.
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
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