deepsense.ai Customer Reviews 2025 | Machine Learning Platforms

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deepsense.ai

Composite Score

8.1 /10

CX Score

8.6 /10

13 Reviews Write a Review

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What is deepsense.ai?

deepsense.ai is a data science company, which helps organizations gain competitive advantage by providing them with AI-based end-to-end solutions, with the main focus on computer vision, predictive analytics and natural language processing. The company also delivers machine learning and deep learning training programs to support enterprises in building AI capabilities in-house.

Company Details

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deepsense.ai Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on deepsense.ai.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

87 Likeliness to Recommend

94 Plan to Renew

1
Since last award

94 Satisfaction of Cost Relative to Value

1
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+99 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love deepsense.ai?

0% Negative

0% Neutral

100% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 85

Data Pre-Processing

Explainability

Model Tuning

Pre-Packaged AI/ML Services

Performance and Scalability

Model Monitoring and Management

Data Exploration and Visualization

Algorithm Recommendation

Feature Engineering

Data Labeling

Openness and Flexibility

Vendor Capability Ratings

Average 82

Usability and Intuitiveness

Ease of IT Administration

Ease of Implementation

Business Value Created

Vendor Support

Ease of Data Integration

Availability and Quality of Training

Breadth of Features

Quality of Features

Product Strategy and Rate of Improvement

Ease of Customization

deepsense.ai Reviews

Prisca Nwanneka E.

Role: Consultant
Industry: Media
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted May 2025

Powerful AI solutions

Likeliness to Recommend

9 /10

What differentiates deepsense.ai from other similar products?

Deepsense.ai stands out for its strong focus on custom AI and machine learning solutions tailored to business needs, not just off-the-shelf tools. Their deep expertise in computer vision and predictive analytics also sets them apart.

What is your favorite aspect of this product?

Their hands-on, consultative approach. They don't just build models—they help solve real business problems with clear strategy and support.

What do you dislike most about this product?

The onboarding and project timelines can sometimes feel lengthy, especially for smaller companies with tight deadlines.

What recommendations would you give to someone considering this product?

Have a clear goal in mind and be ready to collaborate closely—deepsense.ai delivers best when clients are engaged and provide domain insights.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Mohammad O.

Role: C-Level
Industry: Technology
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Feb 2025

Powerful AI tools, but it is not beginner-friendly

Likeliness to Recommend

9 /10

What differentiates deepsense.ai from other similar products?

It gives very smart AI solutions that are not just theory but actually work in our real business situations. Many AI platforms provide tools, but deepsense.ai focuses on solving our real problems.

What is your favorite aspect of this product?

Their custom AI solutions is very good. We have used in our e-learning platform to enhance the experience and learning outcomes of students using AI. Also, their support team is very helpful.

What do you dislike most about this product?

It is bit complex to use and need proper training to use smoothly. And it does not have pre-trained models so I think it is a downside.

What recommendations would you give to someone considering this product?

If anyone want to use customer AI solution, it is a best platform.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Srikanth C.

Role: Information Technology
Industry: Engineering
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Oct 2024

Ml at our fingertips

Likeliness to Recommend

8 /10

What differentiates deepsense.ai from other similar products?

Deepsense.ai provides top notch collaboration feature where It emphasizes high level collaboration, allowing teams to work together seamlessly on projects, which is often lacking in other platforms.

What is your favorite aspect of this product?

Deepsense.ai provides tools for the entire machine learning lifecycle, from data preparation and model training to deployment and monitoring. This makes it so that no other tool is required to complete our Ml model.

What do you dislike most about this product?

Depending on the scale in which we are using the product, the pricing can be a concern for small sizes enterprises. Limited community support is also an issue.

What recommendations would you give to someone considering this product?

Learning on the Ml life cycles and algorithms is must if you want to use the platform.

Pros

Trustworthy
Efficient Service
Caring
Fair

deepsense.ai

What is deepsense.ai?

Company Details

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Awards & Recognition

deepsense.ai Ratings

87 Likeliness to Recommend

94 Plan to Renew

1 Since last award

94 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+99 Net Emotional Footprint

How much do users love deepsense.ai?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Explainability Ability to explain/ visualize the model.

Model Tuning Ability to fine-tune models based on monitoring feedback within the platform.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Feature Engineering Ability to extract and build features from raw data.

Data Labeling Ability to annotate/ label data to create a training data set.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

deepsense.ai Reviews

Prisca Nwanneka E.

Powerful AI solutions

Likeliness to Recommend

Pros

Mohammad O.

Powerful AI tools, but it is not beginner-friendly

Likeliness to Recommend

Pros

Srikanth C.

Ml at our fingertips

Likeliness to Recommend

Pros

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Feature Ratings

Data Pre-Processing

Explainability

Model Tuning

Pre-Packaged AI/ML Services

Performance and Scalability

Model Monitoring and Management

Data Exploration and Visualization

Algorithm Recommendation

Feature Engineering

Data Labeling

Openness and Flexibility

Vendor Capability Ratings

Usability and Intuitiveness

Ease of IT Administration

Ease of Implementation

Business Value Created

Vendor Support

Ease of Data Integration

Availability and Quality of Training

Breadth of Features

Quality of Features

Product Strategy and Rate of Improvement

Ease of Customization