OpenAI API Alternatives

4.5(186 Ratings)

Considering alternatives to OpenAI API? See what this market OpenAI API users also considered in their purchasing decision. When evaluating different solutions, potential buyers compare competencies in categories such as evaluation and contracting, integration and deployment, service and support, and specific product capabilities.

Check out real reviews verified by Gartner to see how OpenAI API compares to its competitors and find the best software or service for your organization.

Reviewed in Last 12 Months

How Alternatives Are Selected

1. Grammarly

4.6

As a user on the personal as well as with a corp standpoint, I find Grammarly to be an excellent tool that provides a great foundation for improving my writing across these scenarios. The in-line suggestions in our office suite (Google) for whatever reason is hit or miss (both when it pops up and the quality). I would say it has improved the consistency and clarity in my writing and such in the larger orgs' communications. Overall very reliable, user-friendly, and transparent to integrate into workstreams.Read all insights and reviews for Grammarly

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2. Microsoft 365 Copilot

4.4

My overall experience using Microsoft Copilot has been really good. The product significantly helps in productivity, as all Microsoft products now integrate Copilot, supporting the crafting of messages and information across applications like Word, Excel, and Teams chats. My organization primarily utilizes Microsoft 365 Copilot as an end-user for our day-to-day work. Specifically, in Word, we leverage it to create and understand documents, as well as for summarizing complex documents. In Outlook, Copilot offers various features, such as crafting messages based on raw feedback and coaching on the appropriate tone for communication. For Excel, it provides quick analysis capabilities, which means we no longer need to learn or Google specific formulas, making tasks quicker and easier. Additionally, in PowerPoint, it aids in creating presentations and slides based on the information or documents we provide. From an organizational perspective, the strategy behind implementing Copilot is to bring awareness to the entire workforce about AI products. It serves as a foundational tool for common users to become accustomed to prompt engineering and the general use of AI. While we do not currently track Copilot’s impact as part of our measurable Key Performance Indicators (KPIs), we have received positive feedback regarding productivity improvements. Users have reported at least a 20% reduction in time spent on refining content created within these applications. When it comes to specific examples, quantifying time savings can be difficult due to varying use cases. However, for tasks like creating PowerPoint presentations, which might typically take a full day to gather and organize information, Copilot can save 20% to 30% of the time by generating an initial draft that then requires review and refinement. Our approach to rolling out Copilot has been phased, initially including individuals who have a direct need to interact with AI, and subsequently expanding to those who express interest. This phased implementation has resulted in a positive response. Regarding the accuracy and reliability of AI-generated responses, I would say they are pretty accurate, generally around 80% to 90%. Getting started with Copilot was quite easy for users. The basic functionality is intuitive, much like chatting with a person. Personally, I did not undergo formal prompt engineering training. Instead, I learned by refining my questions over time. I found that the first question might not always yield the most accurate result, so I would rephrase and ask more specific questions, which helped develop a "prompt engineering kind of mindset". This iterative process helped me understand how to phrase prompts more effectively over time, without needing explicit training to get started. Data security, privacy, and compliance are areas where I believe Microsoft Copilot performs really well. My organization agreed to adopt it because we understand that when questions are asked based on internal documentation within our SharePoint or other instances, the information does not leave our company's secure environment. This robust security and data compliance is a primary reason why organizations are willing to adopt it. My organization has also issued internal advisories and best practices, outlining what kind of data can be inputted and what should be refrained from using with Copilot. These guidelines are complemented by general learning materials and specific organizational trainings. I have also observed that within a chat session, Copilot can retain information from previous interactions and understand context, much like a human conversation. However, this retention does not extend once the chat session is closed. Based on my experience, I would give Microsoft Copilot an overall rating exceeds expectations. The primary reasons my organization purchased this product include the desire to create internal and operational efficiencies, drive innovation, and enhance decision-making. We also considered its potential to reduce time to market for certain initiatives. Key factors influencing this decision were Microsoft's strong services expertise, breadth of services, product roadmap and future vision, and pre-existing relationships with the vendor.Read all insights and reviews for Microsoft 365 Copilot

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3. Amazon Q Business

By Amazon Web Services (AWS)

4.4

Great tool which uses Generative AI-powered assistant designed to enhance productivity within organizations Read all insights and reviews for Amazon Q Business

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4. GitHub Copilot

4.4

Our organization, a product-based company, has had a highly positive and extensive experience using GitHub Copilot in our development environment, with nearly all our developers utilizing it. We primarily leverage it in the generative AI apps and AI code assistance markets, finding it fits well within the former. The product has significantly accelerated our development process and enhanced code quality. We've observed at least a 30% productivity boost when our teams are proficient in its use. This improvement is crucial given today's demand for rapid product and solution delivery. A key factor in our selection was Copilot's maturity and seamless integration with various development environments, including Visual Studio and VS Code, making it a valuable part of our ecosystem. It proves particularly effective for Python-based projects, machine learning libraries like scikit-learn, TensorFlow, and PyTorch, and generative models. Copilot's built-in intelligence understands the development context, offers automatic code writing, and assists with documentation, greatly aiding code maintainability and readability. It also minimizes distractions by integrating help that would otherwise require searching external forums. Onboarding was easy, leading to quick adoption within our team, partly because some developers, including myself, had prior experience with it. The return on investment (ROI) has been clear, delivering value in terms of speed, code quality, and overall project structure. While we highly value its AI assistance, we maintain strict code quality, security, and compliance through architectural reviews, penetration testing, and thorough human oversight, as AI tools require careful validation. We philosophically view Copilot as an intelligent tool that enhances productivity, not as a replacement for human input.Read all insights and reviews for GitHub Copilot

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5. Glean

4.5

A tool that integrates with other apps in the org and helps find the resource with just a quick prompt. It has made life easy by searching internal docs/emails. It not only works on searching internal organisational documents but also has the option to open the search and get results from global sources. Great thing about the search is that every result has a reference link from which you can validate and refer to the source of the given information. This gives you confidence in the information being listed on Glean.Read all insights and reviews for Glean

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6. Agentic Process Automation System

By Automation Anywhere

4.7

Our overall experience with Automation Anywhere’s GenAI solution has been highly positive. It has significantly enhanced the intelligence and efficiency of our automation workflows. The platform is user-friendly yet powerful, and the GenAI features have helped us automate tasks that were previously too unstructured or variable for traditional RPA. The support team has been responsive, and the documentation is solid. We saw tangible improvements in turnaround time, process accuracy, and employee productivity within a few weeks of implementation. This solution is helping us move closer to our vision of a truly intelligent digital workforce.Read all insights and reviews for Agentic Process Automation System

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7. Jasper

4.4

We used jasper studio. It is no code tool that allow marketers to design and build AI application without requiring technical expertise.Read all insights and reviews for Jasper

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8. Writer

4.2

My experience with Writer as a product marketer has been quite positive. I like that I can stick within the brand guidelines of the company and create consistent messaging as other marketers in my large organization.Read all insights and reviews for Writer

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