Dataiku Features

Reports interface for standard and self-service reports is intuitive and easy to use.

Requires a minimal number of steps/clicks to answer business question.

Offers a variety of attractive graph and chart formats.

Score cards visually track KPI's.

Provides business users an interface to easily design, refine and collaborate on their dashboards

Alter the layout and content of reports

Reports specific to marketing and associated campaigns

Reports specific to sales analysis for trends and strategies

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Edit and personalize data view as needed

Alter the layout and content of reports

Alter the layout and content of reports

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Alter the layout and content of dashboards

Using formulas based on existing data elements, users can create and calculate new field values.

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Users can drill down and explore data to discover new insights.

Ability to search global data set to find and discover data.

Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms.

Tool automatically suggests data types, schemas and hierarchies.

Ability to interact with the application using human languages such as English

Process of visually navigating data and applying analytics to detect patterns, gain insight, and answer specific business queries.

Merge data from multiple sources to a single data set

Merge data from multiple sources to a single data set

Analyze current and historical trends to make predictions about future events.

Communicate complex information clearly and effectively through advanced graphical techniques.

Ability to handle large, complex, and/or siloed data sets.

Analyze and gain insights into data in real-time

View and track pertinent metrics to find patterns and gain insights from data

Analyze and gain insights into data in real-time

View and track pertinent metrics to find patterns and gain insights from data

Interact with data visualization elements, such as charts and graphs, to drill down into data

Converts data formats of source data into the format required for the reporting system without mistakes.

Ability to (re)structure data in a manner that allows extracting insights fast and accurate.

Provides business users an interface to easily design and refine their dashboards and reports. (What You See Is What You Get)

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications.

Receive data and information in real time

Receive data and information in real time

Set up connections to third-party platforms to improve business processes

Set up connections to third-party platforms to improve business processes

Supports a variety of scripting environments

Mines data from databases and prepares data for analysis

Applies statistical algorithms to selected data

Analyzes both structured and unstructured data

Interacts with data to prepare it for visualizations and models

Series of data points indexed in time order

Review data from past periods to reveal recurring tendencies and predict future performance

Offers modeling capabilities

Creates data visualizations or graphs

Generates reports of data performance

Unifies information on a singular platform

Alter the layout and content of reports

Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript

Offers the ability for developers to drag and drop pieces of code or algorithms when building models

Provides users with pre-built algorithms for simpler model development

Supplies large data sets for training individual models

Supports common databases such as MySQL and Oracle

Manage and support multiple languages

Transforms raw data into features that better represent the underlying problem to the predictive models

Offers image recognition services

Offers natural language processing services

Offers natural language generation services

Offers artificial neural networks for users

Offers natural language understanding services

Provides deep learning capabilities

Manages the intelligent application for the user, reducing the need of infrastructure

Allows users to insert machine learning into operating applications

Provides easily scaled machine learning applications and infrastructure

Allows users to input models built in a variety of languages.

Allows users to choose the framework or workbench of their preference.

Records versioning as models are iterated upon.

Provides a way to quickly and efficiently deploy machine learning models.

Offers a way to scale the use of machine learning models across an enterprise.

Allows users to input models built in a variety of languages.

Allows users to choose the framework or workbench of their preference.

Records versioning as models are iterated upon.

Provides a way to quickly and efficiently deploy machine learning models.

Offers a way to scale the use of machine learning models across an enterprise.

Facilitates analysis of high-volume, real-time data.

Allows user to query data through query languages like SQL.

View and track pertinent metrics to find patterns and gain insights from data

Predict future data based on historical data sets

Interact with data visualization elements, such as charts and graphs, to drill down into data

Aligns processing and distribution workflows on top of Apache Hadoop

Aligns processing and distribution workflows on top of Apache Spark

Integrates data from multiple external databases.

Facilitates the dissemination of collected big data throughout parallel computing clusters.

Receive data and information in real time

Import, collect, and capture data from multiple sources

Review data from past periods to reveal recurring tendencies and predict future performance

Provides varying estimates based on different scenarios

Apply statistical/mathematical models to sets of data

Merge data from multiple sources to a single data set

Set up connections to third-party platforms to improve business processes

Processes data and represents interpretations in a variety of graphic formats.

Strings together specific functions and datasets to automate analytics iterations.

Isolates certain datasets and facilitates management of data access.

Allows big data tool to run and record data within external applications.

Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations

Discover and connect variety of data sources to the application for analysis

Control model usage and performance in production

Deploy mission-critical ML applications where and when you need them

Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance.

Records and organizes all machine learning models that have been deployed across the business.

Tracks the performance and accuracy of machine learning models.

Provisions users based on authorization to both deploy and iterate upon machine learning models.

Allows users to manage model artifacts and tracks which models are deployed in production.

Records and organizes all machine learning models that have been deployed across the business.

Tracks the performance and accuracy of machine learning models.

Provisions users based on authorization to both deploy and iterate upon machine learning models.

Gives user ability to import a variety of data sources for immediate use

Receive data and information in real time

Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications.

Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data

Using formulas based on existing data elements, users can create and calculate new field values

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Allows the user to combine data from multiple sources into a functioning dataset.

Import, collect, and capture data from multiple sources

Provides personalized responses to interlocator based on segmentation or past responses.

Has tools (e.g. dashboards and reports) to better understand conversations Intelligent Virtual Assistants have had.

Can have a natural, human-like conversation with an interlocator.

Manage and support multiple languages

Allows business to edit conversations to meet the unique needs of one's business.

Gives users the ability to update systems, like CRM, based on conversations.

Allows users to maintain and observe the accuracy and viability of Intelligent Virtual Assistants.

Editing tool that allows users to drag and drop images, icons, widgets, or other components

Agents pause for human input at key steps and hand off tasks when beyond their confidence or authority.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Provides the ability to generate images from a text prompt.

Use AI to generate content in the form of text, images, videos, etc.

Ensures that the service is reliable and available when needed, minimizing downtime and service interruptions.

Allows the user to scale the training of models efficiently, making it easier to deal with larger datasets and more complex models.

Provides the user the ability to get quick and low-latency responses during the inference stage, which is critical for real-time applications.

Offers the user a transparent pricing model for API calls, enabling better budget planning and cost control.

Provides the user the ability to allocate computational resources based on demand, making it cost-effective.

Allows the user to minimize energy usage during both training and inference, which is becoming increasingly important for sustainable operations.

Offers the user the flexibility to deploy across multiple cloud providers, reducing the risk of vendor lock-in.

Provides the user the ability to seamlessly connect with various data sources and pipelines, simplifying data ingestion and pre-processing.

Allows the user to easily integrate the generative AI models into existing workflows and systems via APIs.

Helps the user maintain compliance with GDPR and other data protection regulations, which is crucial for businesses operating globally.

Allows the user to set up access controls based on roles within the organization, enhancing security.

Ensures that data is encrypted during transit and at rest, providing an additional layer of security.

Provides the user with comprehensive and clear documentation, aiding in quicker adoption and troubleshooting.

Allows the user to gauge the level of community support and third-party extensions available, which can be useful for problem-solving and extending functionality.

Allows users to automate responses to customer inquiries across various channels.

Allows users to automate responses to customer inquiries across various channels.

Allows users to automate the process of generating and qualifying sales leads.

Allows users to automate the handling, processing, and management of documents.

Provides users the ability to automate the collection and analysis of feedback from customers, employees, or other stakeholders.

Process and analyze human language in text or audio form

Generative AI can generate synthetic data and simulate scenarios for training and testing purposes.

Allows the AI agent to learn from interactions and adapt its responses accordingly.

Allows the AI agent to learn from interactions and adapt its responses accordingly.

Provides the AI agent the ability to execute tasks without requiring constant user input.

Allows the AI agent to identify and resolve issues without user intervention.

Supports integration with multiple data sources for seamless data input.

Set up connections to third-party platforms to improve business processes

Enhances output accuracy and speed through efficient ingestion and processing of training data.

Generates actionable insights by applying learned patterns to key issues.

Continuously improves and adapts to new data using specified algorithms.

Provides users with the ability to test and optimize prompts to improve LLM output quality and efficiency.

Gives users a collection of reusable prompt templates for various LLM tasks to accelerate development and standardize output.

Offers tools for users to compare multiple LLMs side-by-side based on performance, speed, and accuracy metrics.

Provides users with a user-friendly interface for fine-tuning LLMs on their specific datasets, allowing better alignment with business needs.

Gives users tools to integrate LLM functionality into their existing applications through SDKs and APIs, simplifying development.

Offers users the capability to deploy models quickly to production environments with minimal effort and configuration.

Provides users with tools to automatically scale LLM resources based on demand, ensuring efficient usage and cost-effectiveness.

Gives users the ability to set boundaries and filters to prevent inappropriate or sensitive outputs from the LLM.

Offers users tools to ensure their LLMs adhere to compliance standards such as GDPR, HIPAA, and other regulations, reducing risk and liability.

Gives users notifications when the LLM performance deviates significantly from expected norms, indicating potential model drift or data issues.

Provides users with live insights into model accuracy, latency, and user interaction, helping them identify and address issues promptly.

Provides users with encryption capabilities for data in transit and at rest, ensuring secure communication and storage when working with LLMs.

Offers users tools to set access permissions for different roles, ensuring only authorized personnel can interact with or modify LLM resources.

Provides users with middleware to route requests efficiently to the appropriate LLM based on criteria like cost, performance, or specific use cases.

Gives users tools to process multiple inputs in parallel, improving inference speed and cost-effectiveness for high-demand scenarios.

Supports configuration using natural language instructions.

Allows users to customize the tone of agent.

Enables definition of clear security guardrails for agent actions.

Protect APIs from threats using authentication, access control and encryption

Protect sensitive data for digital privacy

Verify the identity of users/devices to enable secure access

Provides support across web, mobile, messaging apps, and other channels.

Allows customization of agent branding, including visual appearance and conversational style.

Equips agents with proactive response capabilities based on predefined triggers.

Facilitates seamless escalation to human employees for complex issues.

Supports various file formats

Processing different types of input like text, voice, images etc.

Provides analytics and reporting on agent performance and interactions.

Offers agents the ability to maintain contextual awareness across interactions.

Ensures compliance with data privacy and governance requirements.

Automates workflows and actions based on agent responses.

Allows the use of APIs for advanced agent configuration.

Enables interoperability with multiple platforms for unified experiences.

Allows integration with CRM data to ground agent responses in business context.

Set up connections to third-party platforms to improve business processes

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Set up connections to third-party platforms to improve business processes

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Set up connections to third-party platforms to improve business processes

Lets teams configure execution order and dependencies among AI components, ensuring workflows run smoothly and logically.

Streamlines the management of multiple AI models and agents by bringing them together into cohesive, automated workflows for complex business tasks.

Connects with a wide array of AI model APIs and external services, regardless of provider, within a single orchestration platform.

Enables the construction of sophisticated, multi-step AI workflows that combine specialized models for end-to-end process automation.

Integrates seamlessly with enterprise platforms such as CRMs, databases, and business applications for unified data and process flow.

Supports the setup of live data pipelines that move information instantly between AI components and enterprise systems.

Offers comprehensive dashboards to visualize KPIs and performance metrics for all orchestrated AI workflows.

Generates in-depth reports on workflow performance, resource consumption, and the overall business impact of AI orchestration.

Tracks and displays resource usage across all AI components, enabling proactive performance tuning and troubleshooting.

Dynamically manages and allocates computational resources, including GPU clusters, to maximize efficiency based on current workflow needs.

Scales AI workloads up or down automatically, adapting to fluctuations in processing demands and user traffic.

Provides insights into data flow, processing times, and success rates for each individual AI component within a workflow.

Ensures all AI workflows adhere to relevant regulatory standards and industry requirements.

Empowers organizations to enforce governance policies and compliance controls across orchestrated AI operations.

Facilitates the setup of role-based permissions and approval workflows for sensitive AI operations and deployments.

Maintains comprehensive logs and audit trails of workflow executions to support compliance and troubleshooting efforts.

Applies robust security protocols and policies to protect sensitive AI deployments and data flows.

Enables non-technical users to build dashboards through intuitive, drag-and-drop interfaces

Enables automated report generation and scheduled delivery to stakeholders

Allows dashboards and analytics to be embedded into external apps with branding flexibility

Supports integration with major data sources like cloud data warehouses, SQL/NoSQL databases, and SaaS applications

Allows users to manage data from a number of sources

Tool that allows users to create and execute database queries without needing to know the underlying syntax of the database

Efficiently processes large datasets with minimal lag and ensures high performance under load

Maintains performance and uptime during high traffic from multiple users or teams

Supports common databases such as MySQL and Oracle

Supports semantic data layers, role-based access controls, and metadata governance

Integrates with Jupyter, Python, or R for custom analytics and modeling

Provides native tools for statistical analysis, forecasting, and trend prediction

Uses AI to generate textual summaries, key takeaways, and data stories from dashboards

Allows users to query data and build reports using conversational or plain language

Detects and notifies users about KPI anomalies or significant metric changes in real time

Recommends next questions, analyses, or exploration paths using autonomous AI agents

Learns from historical user interactions to improve and personalize query results over time

Tailors dashboard views and suggestions based on user roles, access levels, and past behavior

Supports AI-driven exploration via prompts or multi-turn conversations for iterative querying

One-off queries made on an as-needed basis

Interact with data visualization elements, such as charts and graphs, to drill down into data

Analyzes incoming datasets to surface missing values, distributions, outliers, and data quality issues automatically

Enables users to ingest data from diverse sources (databases, APIs, cloud storage, spreadsheets) without custom coding

Automatically alerts users when incoming data’s schema deviates from expected structure over time

Suggests or auto‑selects candidate algorithms and hyperparameters based on dataset characteristics

Allows users to insert custom code (e.g. Python, R, SQL) or custom modules into pipeline stages for flexibility

Automatically proposes or applies derived features to improve model performance

Assemble applications and processes by dragging over and arranging pre-built components

Securely stores data to prevent data loss or breaches

Import and export data to and from software applications

Add customized logos and colors to align with company branding

Creation and customization of dashboards

Define levels of authorization for access to specific files or systems

Active reporting of data and metrics

Collect and maintain structured information that describes data or content

Form predictions based on past and present data/trends

Manage and store data in a database

Generate one-off reports that meet information requirements

Move from one database to another, or upgrade the version of database software being used

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Access, combine, transform, and store data without the help of an IT department

Search and filter data across systems to locate required information by entering keywords or certain criteria

Track the management and flow of data throughout the organization

Observe and track the demand, usage, progress or quality of a system, product, or user

Categorize emotions expressed in written text or images and identify if they are positive, negative or neutral

Manage user accounts, profiles, roles, permissions, and other details across applications, devices or networks

Analyze the current state of sales data to accurately understand trends and forecast future sales numbers.

Manage patient documentation describing all clinical interactions, diagnoses, procedures, medications, etc.

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

A set of indicators that tracks the performance of networks, applications, systems, teams, etc.

Alerts or notifications of various types such as pop-up messages, sounds, banners, or badges

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

An extended application or connector that enables users to perform additional services with their current set of tools

Ability to present data insights in the form of a story to the audience

Review data from past periods to reveal recurring tendencies and predict future performance

Provides a channel for team members to share media files, communicate, and work together

Financing arranged by the dealership

Generate reports on your own without IT involvement

Tracking the status of previously identified performance measurements

Assembly of graphs and charts for visualizing and tracking statistics/metrics

Application programming interface that allows for integration with other systems/databases

Combining data from different sources and providing a unified view

Visual representation of performance data, enabling users to monitor progress, identify trends, and make data-driven decisions

Ability to handle large datasets

Create, manage and track all task activities and progression

Reporting on how each user, task or process has advanced since its initiation

Connect to big data sources

Graphical representation of data

Evaluate the degree to which business operations bring monetary gains

Monitor the progress of projects from start to finish

At a high level, visualize a preferred outcome, define goals and identify specific steps to achieve them

Establish measurable goals and objectives and track their progress over a specific period of time

Share pre-configured sets of data organized and presented in a specific manner with the organization

Predict future data based on historical data sets

Active monitoring of systems, applications, or networks

Sample files or documents that could be customized as needed or used as is

Access software remotely via mobile devices

Pre-designed layouts that can be customized to match preferences and requirements

Create, design and manage workflows for repetitive tasks

Generate reports to assess the financial performance of an organization

Plan, schedule, and execute organization's accounts and assets to ensure compliance with policies and laws

Online Analytical Processing technology for performing high-speed complex queries or multidimensional analysis on large volumes of data

Allow users to access multiple services after entering their login credentials once

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Multiple agents work together, share tasks, and coordinate to achieve common goals.

Collection of processes, policies, and standards to manage the storage & usability of enterprise data

Process of carefully designing and constructing prompts or input instructions to achieve desired behaviors or outputs from AI models

Collecting, analyzing, and utilizing feedback from users or customers to improve a product or service

Build applications without the use of code

Track revisions and updates made to files and navigate between different versions

Set & manage permission levels based on user roles and restrict access to only authorized individuals

Model the varying behavior of a system over time through diagrams

Application programming interface that allows for integration with other systems/databases

Store and save retrievable data

Observe and track the demand, usage, progress or quality of a system, product, or user

Manage a growing amount of work to meet increased demand without compromising performance

Manage budgets, track and optimize spending and align capacity to workload demand

Plan availability and assign specific time slots for tasks and resources

Interact with agents using conversational language

Define levels of authorization for access to specific files or systems

Ability to interact with various large language models, such as GPT-4, Claude 3, Gemini, Llama 3, and more

Identify which applications need to exchange data and enable these data connections

Flexible architecture allowing tailored configurations

Pre-defined templates within a library for common cases such as contracts, websites, emails, and more

Tools for the systematic analysis of various types of data or statistics

Helps understand a user's intentions/actions

Interprets what a user is doing based on context and helps guide them through the process.

Automates and streamlines business processes by creating a sequence of predefined rules and actions that govern the flow of work

Bots that work alongside humans on tasks that cannot be fully automated

Assemble applications and processes by dragging over and arranging pre-built components

Used as a promotional or demonstration tool in sales and marketing presentations

Use AI to generate content in the form of text, images, videos, etc.

Helps automate and manage information, tasks, and procedures by establishing routines and patterns associated with processes

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Set up connections to third-party platforms to improve business processes

Allows communication with customers or users via multiple channels such as phone, email, live chat, etc.

Categorize emotions expressed in written text or images and identify if they are positive, negative or neutral

Artificial neural networks using multiple layers of processing are used to extract progressively higher level features from data.

Assemble applications and bots from pre-made building blocks without having to write software code or knowing a programming language

Track and manage adherence to policies for any service, product, process, or supplier

Automatic reply functionality for incoming messages

Gather, organize, share, and analyze knowledge in terms of resources, documents, and people skills

Transfer queries and organize messages between agents

Adjust communications based on previous interactions or personal preferences

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Track and understand a customer's overall satisfaction with a product or service to identify areas of improvement.

Program systems that assist users with their daily administrative responsibilities

AI-based platform which conducts a conversation via auditory or textual methods

Train your system to interpret and transcribe voice messages

View and track pertinent metrics to find patterns and gain insights from data

Create, manage and track all task activities and progression

Initiate interactions with customers by proactively starting conversations or providing informational content

Software program that continuously adjusts its behavior based on observed data

Configure existing workflows to meet your organization's needs

Automate processes from start to finish without human assistance

Recording, transcription, and analysis of sales calls for the purpose of training and generating insights

Streamlining repetitive tasks and activities through automated and predefined workflows

Managing and resolving errors that occur during program execution to maintain stability

Alter the layout and content of reports

Provides a channel for team members to share media files, communicate, and work together

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Manage and store data in a database

Generate one-off reports that meet information requirements

View and track pertinent metrics to find patterns and gain insights from data

Predict future data based on historical data sets

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Define levels of authorization for access to specific files or systems

Interact with data visualization elements, such as charts and graphs, to drill down into data

Track the management and flow of data throughout the organization

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Apply statistical/mathematical models to sets of data

Organize and group data or items based on various criteria

Review data from past periods to reveal recurring tendencies and predict future performance

Examines, analyzes, and organizes data to create relevant summaries or graphs.

Graphical representation of data

Application programming interface that allows for integration with other systems/databases

Allows users to manage data from a number of sources

Categorize emotions expressed in written text or images and identify if they are positive, negative or neutral

Search and filter data across systems to locate required information by entering keywords or certain criteria

Import and export data to and from software applications

Import, collect, and capture data from multiple sources

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Observe and track the demand, usage, progress or quality of a system, product, or user

Connect to big data sources

Transforming unstructured text into a structured format to identify meaningful patterns and new insights

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

Analyzing historical and current data and generating a model to help predict future outcomes.

Analyze and gain insights into data in real-time

Configure existing workflows to meet your organization's needs

Attach digital tags to documents and assets for identification, search, or monitoring purposes

Track status, assign actions, and control access to systems for devices within the organization

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Transforming raw data to run it through machine learning algorithms to uncover insights or make predictions.

Examine established processes and records to ensure accuracy, compliance, and policy adherence

Examine large amounts of data to uncover hidden patterns, correlations, and other insights

Share, track, and store machine learning models and data.

Ability to handle large datasets

Track and document all activities across devices, networks, and other systems

Protect sensitive data for digital privacy

Create, design and manage workflows for repetitive tasks

Track revisions and updates made to files and navigate between different versions

Manage a growing amount of work to meet increased demand without compromising performance

Adjust communications based on previous interactions or personal preferences

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Event-driven HTTP callback that automatically sends real-time data between applications

Application programming interface that allows for integration with other systems/databases

Process and analyze human language in text or audio form

Automatically switching to secondary AI model(s) during failure or hallucinations

Assemble applications and processes by dragging over and arranging pre-built components

Ability to interact with various large language models, such as GPT-4, Claude 3, Gemini, Llama 3, and more

Chatbot or AI assistant that answers queries and provides recommendations within an application

Execution of software tests by leveraging automation tools

Collection of processes, policies, and standards to manage the storage & usability of enterprise data

Provides a channel for team members to share media files, communicate, and work together

Pre-defined templates within a library for common cases such as contracts, websites, emails, and more

Designing how agent will communicate, take decisions and behave in different scenarios via flowcharts, scripts, or visual editors

Artificial neural networks using multiple layers of processing are used to extract progressively higher level features from data.

Process of testing an ML algorithm by feeding it training data to learn from

Tools for the systematic analysis of various types of data or statistics

Allow users to access multiple services after entering their login credentials once

Detect and remove errors

Manage the processes involved when making the application ready for use

Managing and resolving errors that occur during program execution to maintain stability

Central repositories of integrated data from various sources

Assemble applications and processes by dragging over and arranging pre-built components

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Connect to big data sources

Generate one-off reports that meet information requirements

Alter the layout and content of reports

System alerts about the need to escalate an issue or request

Sample files or documents that could be customized as needed or used as is

Form predictions based on past and present data/trends

Move from one database to another, or upgrade the version of database software being used

Translate EDI formats into data suitable for use with company applications.

Define levels of authorization for access to specific files or systems

Application programming interface that allows for integration with other systems/databases

Removes data that is incomplete, inaccurate, or irrelevant from a dataset

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Creation and customization of dashboards

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Protect sensitive data for digital privacy

Security protocol that ensures secure, encrypted communication over the internet, safeguarding sensitive data from unauthorized access

Provides a channel for team members to share media files, communicate, and work together

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Process and analyze large volume of data

Supports common databases such as MySQL and Oracle

Search and filter data across systems to locate required information by entering keywords or certain criteria

Use AI to generate content in the form of text, images, videos, etc.

Analyzing historical and current data and generating a model to help predict future outcomes.

Configure existing workflows to meet your organization's needs

Attach digital tags to documents and assets for identification, search, or monitoring purposes

Import and export data to and from software applications

Application programming interface that allows for integration with other systems/databases

Predict future data based on historical data sets

Graphical representation of data

Track status, assign actions, and control access to systems for devices within the organization

Allows users to manage data from a number of sources

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Transforming raw data to run it through machine learning algorithms to uncover insights or make predictions.

Examine established processes and records to ensure accuracy, compliance, and policy adherence

Provides a channel for team members to share media files, communicate, and work together

Examine large amounts of data to uncover hidden patterns, correlations, and other insights

Share, track, and store machine learning models and data.

Ability to handle large datasets

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Import, collect, and capture data from multiple sources

Track and document all activities across devices, networks, and other systems

Connect to big data sources

Protect sensitive data for digital privacy

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

Create, design and manage workflows for repetitive tasks

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Forecast customer demand using historical insights and simulations

Software program that continuously adjusts its behavior based on observed data

Assemble applications and processes by dragging over and arranging pre-built components

Software designed for the healthcare industry

Form predictions based on past and present data/trends

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Set up connections to third-party platforms to improve business processes

Tools that provide relevant information at specific times to support judgments and courses of action

Using physical, mathematical, or logical models as a basis for simulations to generate data for managerial or technical decision-making

Alerts or notifications of various types such as pop-up messages, sounds, banners, or badges

View and track pertinent metrics to find patterns and gain insights from data

Allows users to manage data from a number of sources

For Retail Stores

Used for educational purposes

Discover and connect variety of data sources to the application for analysis

Create, design and modify the flow and processes of tasks in a project

A set of indicators that tracks the performance of networks, applications, systems, teams, etc.

Define and maintain business rules that determine workflow capabilities and criteria

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Process and analyze human language in text or audio form

Translate EDI formats into data suitable for use with company applications.

Clustering or grouping objects based on data similarities

Application programming interface that allows for integration with other systems/databases

Merge data from multiple sources to a single data set

Grouping log entries based on similar attributes.

Create, design and manage workflows for repetitive tasks

Streamlining repetitive tasks and activities through automated and predefined workflows