AI tools for business are designed to automate business processes and optimize efficiency. It can help organizations reduce costs, increase productivity, and improve customer service. By making use of AI technology, businesses can achieve a level of sophistication not possible using manual methods.

1. Hubspot

Hubspot is an award-winning CRM system that offers AI marketing automation tools for lead generation, content management, social media marketing, web analytics, search engine optimization, live chat, and customer support.

In a few key ways, HubSpot incorporates AI-powered capabilities into its product suite.

Content Optimization

• Multi-armed bandit testing is used for adaptive, continuous testing of page variations.
• SEO recommendations to help with content strategy
• Suggestions for content topics based on relevance, competition, and popularity.
• Recommendations for related content

Data Management

• Scan business cards to convert them into CRM contacts automatically.
• Contact deduplication and error correction
• Improved data mapping when importing contacts.
• Call transcription and recording
• Email data collection.

Sales Support

• Create predictive lead scores to determine the likelihood of a lead closing.
• Send sales email time recommendations.
• CRM enrichment automatically recognizes certain key contact data points.
• In the live chat, name recognition is available.

2. DataRobot

DataRobot is an automated Machine Learning platform that enables businesses to build and deploy machine learning models and create advanced artificial intelligence applications with the assistance of AI and ML specialists. This platform records the most effective procedures and precautions, allowing for the acceleration and scaling of both new and existing data science capabilities.

In addition, DataRobot offers businesses specialised AI and ML training as well as services via a team of AI architects, business consultants, and systems architects. These professionals work together to deliver these offerings.

The open-source machine learning algorithms and methods that are included in DataRobot’s extensive library are made available for anyone to use. These are put through their paces to ensure that the best model is delivered on a case-by-case basis.

This is done by constructing and ranking multiple models for each AI use case, and then recommending the model that is the best fit to deploy. After it has been installed, DataRobot performs an analysis of how the data was processed, what features were engineered, and which algorithms were applied. It also continuously monitors the health of the service and its accuracy.

3. Dataiku

Dataiku Data Science Studio (DSS) is an online software designed to help data engineers, data scientists, AI users, and business analysts. Dataiku DSS also covers the entire machine learning process, from data preparation to MLOps and application support.

The solution offers two complementary components to assist organizations in reaping the full benefits of their data; self-service Analytics (SSA) enables teams to collaborate in identifying and designing high-impact projects and operationalization (o16n) is the process of maximizing reuse and automation in order to achieve concrete integration of operational systems.

The analytics and data science platform provided by Dataiku DSS includes a visual interface via notebooks (R, Python, Hive, SQL, Spark, and so on) or a drag-and-drop visual interface.

Machine Learning’s visual interface uses ML technologies (Scikit-Learn, MLlib, XGboost, Keras/Tensorflow, and so on) to build and optimize models in Python or R, and integrate any external ML library via code APIs (Dato, H2O, Skytree, etc), and provide instant statistical and visual feedback on model performance.

Dataiku provides data agnostic Integration with over 30 data connectors and therefore the ability to extend with custom plugins, hook up with existing infrastructure, detect format and schema automatically, and push computation to your current Hadoop, SQL, or Spark infrastructure.

4. DataBricks

Databricks is a Cloud-based Data Engineering Tool that is widely used by businesses to process and transform large amounts of data as well as explore the data. This is used to process and transform large amounts of data before exploring it with Machine Learning models. It enables businesses to quickly realize the full potential of their data, ETL processes, and Machine Learning.

Data processing clusters can be configured and deployed in a matter of seconds. To graph data, the platform includes a variety of built-in data visualization features.

Databricks Database Workspace is an Interactive analytics platform that allows data engineers and data scientists to collaborate on notebooks, experiments, models, and data, libraries.

Databricks Machine Learning is a managed service that includes experiment tracking, feature development and administration, model training, and model provides. Databricks ML can train Models manually or with AutoML, use MLflow tracking to track training parameters and Models, and build feature tables that can be accessed for Model training and inference.

The platform allows you to establish a Multi-Cloud Lakehouse structure and run SQL and BI workloads and also gives you a SQL-native workspace where you can run performance-optimized SQL queries.

Users may link it to some of the popular BI tools like Tableau and Power BI to get the most out of their data and collaborate more effectively.

5. C3.ai

The C3 AI Suite is a comprehensive software suite that leverages a model-driven architecture to speed delivery and simplify the development of AI-enabled applications. The C3 AI Suite allows businesses to deliver AI-enabled applications considerably more quickly.

The C3’s AI Suite has created AI and IoT apps that scale powerful machine learning algorithms to give ever-smarter actionable insights for business-critical situations. Manufacturing, oil and gas, utilities, banking, healthcare, aerospace & defense, cities, and public sector, telecommunications, retail, and transportation are among the industries and areas where C3’s AI solutions are deployed.

The following is a list of all C3.ai applications:

• Predictive maintenance
• Inventory organization
• Energy management
• Anti-money laundering
• Sensor health
• Fraud detection
• Supply network
• CRM

6. Freshservice

Freshservice is the type of enterprise AI software that you use when there’s a need for smoother customer operations. Featuring a modern user interface and intuitive design, you’re going to enjoy navigating your way through this app.

The core tools provided are targeted at ticket management for support services by using ITIL and ITSM, Freshservice enables the communication between customers and a helpdesk in a straightforward manner. Rather than investing time into ineffective communication methods, Freshservice allows IT organizations to achieve customer satisfaction through a fast series of communication channels.

While your organization may have a series of prescribed steps for certain management processes, Freshservice cuts time on the bureaucracy by integrating the steps for these processes by default. This is further supported by the presence of automation that expands the workflow of your office.

If you’re looking for something to help your IT Company increase its customer success and provide a better CX, Freshservice should be on your radar. It is designed for speed of use and the affordability is an amazing selling point.

To further increase its effectiveness, Freshservice provides integrations with popularly used services like Dropbox, AWS, and Bomgar, ensuring that you can seamlessly add your organization’s profile to the Freshservice ecosystem.

7. Anaconda

Anaconda is an AI enterprise data science tool that enables organizations to use machine learning to enable growth. As an open-source tool, most of the resources are right at your fingertips, ensuring that innovation can be tailor-made to fit in with your organizational needs.

By choosing to use Anaconda, you can successfully avoid getting locked into any templates or workflows. It primarily drives data science tasks and makes the life of a data scientist much easier, giving them the chance to process and study data to process into useful information.

While using Anaconda, you can successfully maintain a high level of competence at every stage of development. There are samples and preconfigured projects that can guide your development process. Additionally, your data is protected with the help of Anaconda’s repository which is added to your infrastructure during the development of your data science resources.

The Anaconda Enterprise enables you to use Machine Learning in the best ways possible, especially because there is less resistance in terms of moving parts. Your data scientists can entirely focus on the areas where your business can be impacted. Rather than investing in DevOps or software engineering, the Anaconda tool glues things together.

8. V7

Computer vision tools are pretty nice to have if your organization wishes to speed up labelling tasks. V7 in particular could be the exact sort of tool you’re looking for thanks to the amount of control you’re getting with the workflow. It combines dataset management, video and image annotations as well as autoML model training to successfully complete labelling tasks across a range of platforms and areas. This level of convenience is something that will serve your teams pretty well. You can take advantage of the PDF and document processing to transcribe faster than ever, restore old files and generally give your workplace a strong tool to help with tasks.

V7’s UI is simple and intuitive to use. A shallow learning curve is basically a necessity when it comes to enterprise tools that may be used by non tech-savvy folk in your organization. Automation is basically the future for most industries, and V7 presents the concept in one of the most convenient forms that most people are willing to accept.

9. RapidMiner

When an organization wishes to use data science, RapidMiner is a tool worth looking into. Beyond just being a convenient interface, it enhances the data science efforts for your company in a way that supports your entire employee base and presents your process in a comprehensive manner.

One of the perks of RapidMiner is a Visual Workflow Designer that acts as a visual guide for every effort made in the area of data science by your organization. As an intuitive User interface for everyone, RapidMiner also provides automation for other jobs including domain experts. A JupyterLab environment is present for data scientists along with a visual drag-and-drop designer that keeps things neat and tidy for anyone checking out the process.

Running a successful digital enterprise with RapidMiner connects you to various existing systems that can work in tandem with your data science goals. That is why integration is a major selling point worth looking into. You can connect RapidMiner with popular industry tools including NVIDIA CUDA, Tensorflow, Python, R, and more.

Deployment with RapidMiner is quite enjoyable too thanks to various solutions across cloud platforms like Google Cloud, Docker, AWS Azure, Kubernetes, and more.

10. UpKeep

CMMS is a must for any organization that desires a solid way to organize their equipment and assets. With UpKeep, you’re guaranteed to enjoy a host of features that help keep your operations efficient and on schedule.

With this application utilized by members of your organization, you can duly ensure that everyone is kept up to date on new developments, work orders and tasks through any device of their choice. This includes smartphones, desktops and similar mediums. This is especially great as the alerts are sent straight to the app, marring any possible issues with communication.

Upkeep gives users a level of convenience that is hardly found in large workplaces nowadays. The presence of due dates, criticality and worker assignments is something that adds a strong level of connection from your workers to your organization’s ecosystem. Rather than spending time printing schedules and working out conflicts, UpKeep is a one stop shop for everyone.

Navigation with this application is something that adds a decent level of edge to the UpKeep experience. It is fairly simple to use, so the learning curve should not be a limiting factor for workers of all ages. It is an amazing tool for any logistics or manufacturing organization to adopt.

Do note that some users have noticed slow-downs and hiccups with the UpKeep mobile application.

11. Qlik

Qlik is the sort of application you need if you want something that validates your decisions with data driven statistics/analysis. The main selling point of Qlik lies in the augmented analytics coupled with amazing data visualization for users to observe. Natural language analytics brings Qlik closer to the average user than most data analytics platforms available. It is relatively unmatched with how well it indexes associations within user data, revealing insights that would have been almost impossible to find with query-based tools.

Trends and insights with Qlik can be brought to your fingertips with just a few steps, but the visualization methods may vary from perfect to a splotch of confusing colors for some users. The application could benefit from more education directed towards users, detailing how exactly each element works.

Regardless of the few hiccups, you may encounter, there’s no doubt that Qlik is a super flexible application that will do wonders for your organization with the presence of solid analytics.

One benefit of Qlik that you may find yourself enjoying is the fact that it is able to connect to a variety of data sources, giving users pages, reports, and dashboards that are tailored to a user’s requests.

12. Domino

Domino is a powerful platform that provides model-driven data science solutions to users. It is a critically important piece of software that not only helps with collaboration but also solutions. If you’re looking for something that can support an enterprise-scale organization, this is probably one of the best applications to utilize.

As an MLOps platform, Domino’s Enterprise accelerates the progression of your organization through the state-of-the-art data science tools, languages, and computing available with the platform. You’ll never really find yourself struggling with infrastructure or other issues when engaging with Domino. Stability is a solid selling point if reliability matters to you the most.

Domino enterprise is one of the best tools for artificial intelligence today. The machine learning and data science workloads are quite easy to train using the platform, and it allows for integration with Rstudio, visual studio code and other useful tools for development and debugging.

13. Hypersonix

The Hypersonix AI eCommerce platform has a strong likelihood of becoming your trump card for making decisions for your organization. If you want success in the consumer commerce industry, there needs to be an upper hand that elevates you above the competition. This platform does just that, but convincingly well. Hypersonix uses predictive and prescriptive analytics around your industry to provide empowering decisions.

Your e-commerce data will be done justice by plugging it into the Hypersonix platform for auto-analysis. There are timely notifications provided for you while substantial changes are looming for your business. The way this platform is able to achieve its blazing speed and processing is truly admirable with massive amounts of data being processed on the fly.

Contextual intelligence and decisions with Hypersonix is amazing to have, and you won’t be left in the dark on how Hypersonix achieved these conclusions.

14. Genuity

The Genuity IT Admin Suite is a cloud-based platform that assists businesses in the generation of actionable insights and the streamlining of process workflows for IT departments. Ticket management, network monitoring, asset performance tracking, and spending analysis are some of the most important features.

The application includes a module for contract management, which enables members of the team to manage documents, automate renewals, and visualise usage through graphs.

Administrators are able to identify errors in operational procedures or performance problems and receive alerts in real-time, which helps to prevent unscheduled downtime and network failures. Stakeholders are able to better analyse vendor purchases and inspect the breakdown of monthly transactions with the assistance of the system’s expense management feature.

15. Adobe Captivate Prime

Adobe Captivate Prime is an AI LMS (Learning Management System) with a learner-focused environment. It provides a variety of learning styles and course formats, unified playback of the majority of eLearning content types, gamification, mobile, and offline access, as well as other features.

Learners are able to monitor their progress through the courses in which they are enrolled, view a map of the skills they have obtained, and see which courses are recommended for them to take. Adobe Captivate Prime also includes fully customizable gamification features.

Learners’ points earned from course completions and awarded badges can be viewed on their dashboards, along with information on activities that can be carried out in order to earn more points. The dashboard also has the capability of launching leaderboards, which compare the score of a single learner to the scores of their classmates.

Enterprise AI Software Final Words

In conclusion, it is evident that AI software has become a staple in the enterprise. Its ability to automate repetitive tasks and processes has saved businesses time and money. As AI continues to evolve, businesses should consider implementing it into their operations to stay competitive.

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