Jasper Features

Checks for grammar errors like misspellings, sentence run-on, etc.

Evaulates emotional tone of words written.

Ensures sentences are formatted properly.

Checks for instances of plagirism.

Input different types of content and edit text formats, fonts, font sizes, and colors

Assists in the ideation process for creating new content, including themes, content types, titles and more

Generates sentences, paragraphs, or papers based on sample text or a topic.

Application is available as a standlone product.

Utilizes artificial intelligence algorithms to generate high-quality images.

Generate images based on specific text prompts or keywords.

Provides customization options for users to control the style, composition, or color palette of the generated images.

Create different variations inspired by an original image

Supports different aspect ratios for image generation.

Software program that continuously adjusts its behavior based on observed data

Create images based on given inputs or prompts

Provides tools for adjusting the balance between image prompts and text prompts.

Provides negative prompting features to remove specific elements, such as plants, from the generated images.

Gives the user the ability to specify a seed number for consistent image generation.

Produces high quality images.

Has options available to switch between different image generation models.

Has options to add or select image styles.

Generates seamless tileable images for creating patterns or textures.

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.

Produces finished or near-finished content with minimal human intervention beyond templating and prompting.

Generates high-quality content that adheres to brand guidelines.

Provides content generation at scale with efficient response times and quick turnaround.

Generates content that adheres to predefined brand voice and messaging guidelines.

Generates multimodal content including text, images, audio, or video from user prompts, instructions, or contextual inputs.

Generates and adapts content for multiple languages or regional audiences.

Acts as a central hub for teams to collaborate and coordinate on large-scale content efforts.

Maintains regulatory compliance to ensure company data privacy and protection.

Features guardrails to prevent harmful or offensive content generation.

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

Allow users to generate images with rights cleared for commercial use (e.g., marketing, resale, business use).

Clearly state the type of license associated with generated images (e.g., royalty-free, CC0, restricted use).

Identify and map entities within content to improve semantic understanding by AI systems

Connect content to entities and knowledge graph relationships to strengthen contextual signals

Evaluate content context, topic coverage, and meaning to improve semantic discoverability

Strengthen topical authority signals so AI systems recognize content as a credible source

Find prompts where competitors appear but your brand does not.

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

See where your brand appears in AI-generated answers.

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

Connect data to tools like GA4, Looker Studio, Tableau, and more

Connect data to tools like GA4, Looker Studio, Tableau, and more

Structure content into retrievable passages optimized for AI search and retrieval pipelines

Optimize content structure and clarity to increase the likelihood of AI-generated citation

Analyze whether content is technically and structurally ready for AI retrieval systems

Evaluate how well content aligns with natural language prompts used in AI search environments

Assess how AI engines classify and represent the brand as an entity.

Track references and citations of organizational content within AI answer engines

Monitor when and how content appears within AI-generated responses

Analyze visibility and performance across AI-powered search and answer environments

Monitor brand visibility across regions and languages.

Measure brand prominence in AI-generated answers to specific queries.

Track which AI bots visit and index your site.

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

Structure digital content so AI-powered search engines and answer systems can interpret and retrieve information accurately

Enhance content with structured data and schema markup to improve machine-readable meaning

Format headings, passages, and metadata to improve how AI systems parse and extract information

Prepare content for retrieval and citation within large language model search and answer systems

Provides guardrails to prevent harmful, offensive, or non-compliant content generation.

Supports AI-generated content labeling or disclosure requirements.

Maintains enterprise-grade security, regulatory compliance, and data privacy protections.

Integrates with marketing channels, CMS platforms, or publishing tools for content distribution.

Supports content approval workflows and content lifecycle management processes.

Centralizes management of generated content and brand assets across teams and campaigns

Generative AI models can create personalized recommendations for users based on their preferences and behavior.

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

Generative AI models can be used for image and video editing tasks that can automatically enhance images, remove noise or change styles

Edit, touch up, and convert images for publishing

Use artificial intelligence (AI) to turn photos into professional headshots for CVs, resumes, etc.

Create a higher resolution version, or enlarge image or video, without loss in quality

Pre-designed layouts or themes

Generative AI can aid in creative design tasks by generating novel and innovative designs

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

Erase, replace, or add elements to images/photos

Representation of any object in 3D

Remove backgrounds from images or other types of content

Review the style of written or visual content

Content policy to prevent users from generating harmful, violent, or explicit content

Use AI to expand images/photos beyond their original borders

Manage and support multiple languages

Generative AI can be employed to create virtual characters, avatars, or digital personas

Drawing and modeling designs within 2D flat dimensions

Use a brush, or other tool, to remove and add new objects to images

Process and analyze human language in text or audio form

Popular class of generative models that use a two-player adversarial game between a generator and a discriminator.

Upload images, videos, and other types of media

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

Access the system via a mobile application

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

Designer tool for creating color combinations that work together well

Generative AI can be employed to generate content in different forms, such as text, images, music, and videos

Track overall brand presence in AI with a unified metric.

Measure brand presence as a percentage of AI-generated conversations.

Audit and rate content for AI citation readiness.

Attribute web sessions and conversions to AI platforms.

Cluster queries by topic for clearer analysis.

Identify and rank cited domains to inform content strategy.

Check if key pages are accessible to AI crawlers.

Ability that lets users rebrand the software to make it look like their own

Preview content changes’ impact on AI responses before publishing.

Review and enhance schema for better AI comprehension.

Create and manage llms.txt files for AI crawler guidance.

Track brand visibility across ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude, and more.

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

Generate AI-ready articles and FAQs within the platform.

Access curated or suggested prompts for coverage.

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

Filter visibility data by buyer persona or job role.

Manage multiple brands with separate dashboards.

Optimize and manage the search engine optimization efforts for a website or digital content

Alert teams to AI-generated brand inaccuracies or errors.

Access authentic user queries sent to AI platforms.

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

Compare brand frequency and position versus competitors in AI content.

Track what was updated, who made the changes, compare two revisions, and revert or perform another revision

Utilizes artificial intelligence to provide content suggestions to users as they type

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

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

Search and/or filter for items using names, keywords, descriptions, tags, metadata, etc.

Choose the desired tone for content to be generated

Manage and support multiple languages

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

Autocompletion of a word or phrase that the user is typing

Export content in multiple document formats such as .pdf, .txt, .doc, .xls, and more based on requirements

Dictionary/Thesaurus

Create and save approved content for re-use across the team or business

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

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

Create, design and manage workflows for repetitive tasks

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

Rules followed by the software/AI can be configured by users to suit their specific needs

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

Automatic correction of spelling and/or grammatical mistakes

Process and analyze human language in text or audio form

Identify different languages

Platforms that assist marketers in identifying relevant keywords for their content, websites, or advertising campaigns

Edit text as needed

Automatically saves entered text/data

Provides centralized location and shareable capabilities for storage, distribution, and editing of brand guidelines

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

Create, design and manage workflows for repetitive tasks

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

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

Connects LLMs with business data sources and systems such as CRMs and knowledge bases to enable data-driven, context-aware interactions

Teach AI to follow brand guidelines and tone, generating branded, enterprise-grade content in text, images, audio, video, and more.

Handles digital content throughout its lifecycle, from creation and storage to distribution and archiving

Supports AI-generated content labeling or disclosure requirements.

Create content in various formats, such as print, PDF, HTML and more

Notifications/alerts for upcoming events or tasks

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

Features guardrails to prevent harmful or offensive content generation.

Maintain security, compliance, and data privacy protocols for all interactions

Optimize and manage the search engine optimization efforts for a website or digital content

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