May 15, 2025
Blog
Why inline AI aims to revolutionize the world with document creation AI
Why inline AI aims to revolutionize the world with document creation AI
Yi Sang-yeon
Yi Sang-yeon
Why Document Creation Remains a Challenge in the AI Era
"Attorney, when will you send the opinion letter? I'd like to review the draft before it goes to court."
"When will the draft of the paper be ready? The conference is asking. You know the submission deadline is approaching, right?"
"Teacher, have you completed the student records? Let's all finish them this week."
'Document work' constitutes a significant portion of tasks not only for office workers but also for professional occupations.
In reality, however, documents are merely the results that convey thoughts, expertise, and know-how, rather than the core of one's professional capabilities.
Still, it's a fact that document work consumes a substantial amount of time.
Attorneys spend more time drafting documents than on case analysis or trial strategy preparation.
Researchers spend more time reading others' research contributions or completing assignments from professors and writing documents for government-supported projects, rather than delving into their own research.
Teachers likewise spend more time writing student records and responding to education office requests than preparing for classes.
Thus, many professionals are spending too much time on document creation rather than their core duties.
Our Inline AI team sought to solve this issue.
We all have experienced spending more time on 'document writing' than on 'essential tasks' in our respective specialties.
It's a significant problem that professionals waste precious time on repetitive tasks like data organization and document writing instead of focusing on their specialization, and it ultimately leads to a substantial loss for society.
<Last year alone, I wrote over 500 documents that went unread.>
Problems Observed on the Ground by the Inline AI Team
Our team conducted interviews with dozens of experts from the legal, academic, and educational fields and identified three major issues.
1. Difficulty in Analyzing and Integrating Data
"There's so much data, but I don't know how to piece it all together."
Experts possessed a vast amount of data. They had various types of information such as reports, papers, case law, textbooks, and website data stored on computers or drives.
Nevertheless, due to the immense amount of time and effort needed to systematically analyze and integrate these materials, they were often left unutilized or completely neglected.
Lawyers must read and analyze dozens to hundreds of cases and client materials, researchers must summarize and translate hundreds of papers each month, and teachers face the daily challenge of synthesizing multiple textbooks and reference materials.
2. Challenging 'Drafting' Process even for Experts
"Getting those first words down is the hardest part."
Many experts found the 'initiation' of a document the most challenging part.
The process of deciding the structure, contents to include, and where to begin took considerable time.
Particularly for documents like legal papers or academic theses, which are extensive and complex by nature, the difficulty in setting the 'starting line' was more pronounced.
3. Repetitive Revision Work
"Even after drafting, it's not finished; I end up working late or on weekends due to revisions and finalizations."
Professional document writing doesn't end with the initial draft.
Revisions incorporating feedback, adaptations to changing situations, and structural changes result in time-consuming, repetitive tasks for experts.
The Birth of Inline AI
Recognizing these issues made us curious.
"Could AI resolve this problem?"
Recent advances in AI technology have achieved spectacular progress in text generation and comprehension capabilities. However, general-purpose generative AI solutions, such as ChatGPT, Claude, and Perplexity, had several limitations.
They did not accurately grasp the context of the material. AI only responds to prompts provided by the user and does not fully understand the real data's content and context that the user attaches.
They did not sufficiently reflect the user's intent. The results proposed by AI were unilateral, making it challenging to subtly adjust the document to the user's desired direction.
They did not take into account the specificity of professional fields. Areas like law, academia, and education have unique formats and expressions. Existing AI fails to sensitively reflect these, and since they are developed overseas, they do not consider the characteristics of each domestic industry.
To overcome these limitations, our Inline AI team embarked on developing a specialized AI solution to support professional document creation earlier this year.
We closely collaborated with experts in law, academia, and education, designing a solution that reflects their real needs.
<Inline AI, like a real human, understands context and intent when provided with material.>
"AI Proposes the Starting Line after Understanding the Material"
Based on user feedback, we established this vision.
Solution: AI proposes the starting line after understanding the material.
This concise statement encapsulates the core values of Inline AI. More specifically, it’s as follows:
AI that Reads and Comprehends Material
Inline AI is not just a simple text generator. It is a solution that deeply analyzes and comprehends user materials.
It recognizes nearly all kinds of material formats, including PDFs, PPTs, Word documents, HWP, and web pages, understanding their content, structure, and context.
To achieve this, we developed specialized analysis algorithms tailored to various material types. Algorithms understanding the structure of PDF documents, extracting key content from web pages, identifying semantic relationships between texts, and adopting the best approaches for each material type were applied.
The most challenging part of development was identifying interrelationships between materials.
For example, enabling AI to understand how various case laws and legal provisions are connected, or how multiple research papers can be integrated, was a significant challenge.
We enhanced this ability through thousands of hours of learning and testing and are finally reaching our desired target.
AI that Proposes the Starting Line
'Starting line' is a key concept of Inline AI. Our goal is to provide a 'starting point' where users can commence substantial work instead of a finished document.
This starting line is offered in three main forms:
Data Processing and Insight Extraction: AI analyzes the data and presents key insights to the user.
Document Structure Drafting: Suggests the flow and briefly guides what content should be included in each part.
Draft Document Creation: Generates a draft with the material fully integrated, allowing the user to start from an 80% starting line.
What we valued most during this process was that 'users should be in control.'
Inline AI is designed so that the AI supports, rather than leads the process, with the user taking charge. Through the human-in-the-loop approach, users can modify AI's suggestions and adjust the direction at any time.
Thus, users can 'accept' the AI's proposals as is, or 'reject' them and finely adjust the relevant parts.
AI helps users 'start from the 80% mark.' Developing a document by utilizing the unique expertise and know-how of humans to fill in the remaining 20%, you can meet deadlines at a speed ten times faster than before by leaving most of the factual writing to AI.
<Experience a Perfect Draft Written by AI.>
👉 Try it for Free
Challenges and Triumphs in AI Development
The journey to develop Inline AI was by no means smooth. We faced numerous technical challenges and other problems encountered on site.
Technical Barriers
Firstly, processing various data formats consistently was challenging. Each format like PDF, PPT, and web pages had different data extraction methods, and getting AI to identify the context and meaning to the level of a human expert in vast, unstructured raw data was a significant challenge.
Secondly, elevating the quality of the 'starting line' proposed by AI was not easy. Developing an AI that goes beyond mere data summarization to grasp the essence of the material and suggest creative structures was a complex task.
Thirdly, designing a mechanism to effectively incorporate user feedback was challenging, a problem even big tech companies cannot easily solve. AI continues to require improvements in accurately understanding user intent and adjusting the starting line accordingly.
Field Tests and Feedback
To overcome these challenges, we prioritized field tests with actual users. We tested prototypes and gathered live feedback from law firms, research institutions, and educational sites.
In one law firm, Inline AI was used for legal opinion letters and various applications. Initially, there was an issue where AI did not capture the nuances of legal terms accurately, but it has been perfectly improved through continuous learning.
Research institutions used Inline AI for drafting paper prototypes, particularly appreciating its ability to systematically organize related research trends.
The most frequent feedback was that it was "too difficult." Being AI service developers, we focused on precisely fine-tuning AI for requested specifications. We realized that it was difficult for the general public to understand such services from a non-developer's perspective.
For example, many confused the function "Add Background Knowledge" for finely adjusting the context of AI answers and the function "@" for adding data to the instructions.
Thus, we integrated these two functions, leaving only the feature of adding material to AI instructions with "@".
Based on this feedback, we are currently overhauling inline AI to make it "much easier."
This field testing and feedback played a crucial role in the advancement of Inline AI.
<Inline AI was created through interviews with over 100 professionals, thousands of hours of learning, and hundreds of hours of coding.>
<Shortly after Inline AI's launch, we received thank-you letters from many users.>
The Present and Future of Inline AI
Currently, Inline AI is establishing itself as a specialized solution supporting document creation in legal, academic, educational, and business fields.
Attorneys use it for factual organization and document draft creation, researchers for paper translation/summary and draft creation, and teachers for drafting various documents and student records with Inline AI.
The response from users is far more positive than we anticipated.
Feedback like "I save over 10 hours a week thanks to this tool," from an attorney, "Paper summary and draft creation time reduced by 30%," from a researcher, and "Thanks to it, I could finish the business plan in a day" from an aspiring entrepreneur bring us great satisfaction.
Our journey is just beginning. Moving forward, Inline AI aims to develop in the following directions:
Support for More Material Types: In addition to currently supported PDFs, PPTs, web pages, and texts, we plan to strengthen our multimedia data analysis capabilities for formats like audio and video.
Document Template Support: We will learn the specialized document formats and structures of each professional field to suggest more professional starting lines.
Enhanced Collaboration Features: Considering the reality that many documents are created in teams, we plan to develop features for multiple users to utilize Inline AI collaboratively.
Our Vision: To Enable All Professionals to Focus on Their Core Tasks
The ultimate vision of Inline AI is clear. It is to help experts free themselves from the repetitive task of document writing and reinvest more time into their true expertise.
Legal experts will be able to invest more in legal research and strategy development. Researchers will focus more on in-depth experiments and analyses. Teachers will deploy more capacity to care for individual students and offer customized guidance.
This is how Inline AI aims to 'change the world.'
It's not just about writing more documents faster, but rather helping experts in each field realize their true value. This is the reason behind the development of Inline AI and the driving force that will continue to spur its advancement.
With Inline AI, liberate yourself from the burden of document creation and fully showcase your true expertise.
We will continue to tirelessly strive to suggest even better 'starting lines.'
Thank you.
The Only AI That Understands Your Material and Proposes the Starting Line
👉 Try it for Free
📺 Watch AI Write a Perfect Document Draft - Demo Video
Why Document Creation Remains a Challenge in the AI Era
"Attorney, when will you send the opinion letter? I'd like to review the draft before it goes to court."
"When will the draft of the paper be ready? The conference is asking. You know the submission deadline is approaching, right?"
"Teacher, have you completed the student records? Let's all finish them this week."
'Document work' constitutes a significant portion of tasks not only for office workers but also for professional occupations.
In reality, however, documents are merely the results that convey thoughts, expertise, and know-how, rather than the core of one's professional capabilities.
Still, it's a fact that document work consumes a substantial amount of time.
Attorneys spend more time drafting documents than on case analysis or trial strategy preparation.
Researchers spend more time reading others' research contributions or completing assignments from professors and writing documents for government-supported projects, rather than delving into their own research.
Teachers likewise spend more time writing student records and responding to education office requests than preparing for classes.
Thus, many professionals are spending too much time on document creation rather than their core duties.
Our Inline AI team sought to solve this issue.
We all have experienced spending more time on 'document writing' than on 'essential tasks' in our respective specialties.
It's a significant problem that professionals waste precious time on repetitive tasks like data organization and document writing instead of focusing on their specialization, and it ultimately leads to a substantial loss for society.
<Last year alone, I wrote over 500 documents that went unread.>
Problems Observed on the Ground by the Inline AI Team
Our team conducted interviews with dozens of experts from the legal, academic, and educational fields and identified three major issues.
1. Difficulty in Analyzing and Integrating Data
"There's so much data, but I don't know how to piece it all together."
Experts possessed a vast amount of data. They had various types of information such as reports, papers, case law, textbooks, and website data stored on computers or drives.
Nevertheless, due to the immense amount of time and effort needed to systematically analyze and integrate these materials, they were often left unutilized or completely neglected.
Lawyers must read and analyze dozens to hundreds of cases and client materials, researchers must summarize and translate hundreds of papers each month, and teachers face the daily challenge of synthesizing multiple textbooks and reference materials.
2. Challenging 'Drafting' Process even for Experts
"Getting those first words down is the hardest part."
Many experts found the 'initiation' of a document the most challenging part.
The process of deciding the structure, contents to include, and where to begin took considerable time.
Particularly for documents like legal papers or academic theses, which are extensive and complex by nature, the difficulty in setting the 'starting line' was more pronounced.
3. Repetitive Revision Work
"Even after drafting, it's not finished; I end up working late or on weekends due to revisions and finalizations."
Professional document writing doesn't end with the initial draft.
Revisions incorporating feedback, adaptations to changing situations, and structural changes result in time-consuming, repetitive tasks for experts.
The Birth of Inline AI
Recognizing these issues made us curious.
"Could AI resolve this problem?"
Recent advances in AI technology have achieved spectacular progress in text generation and comprehension capabilities. However, general-purpose generative AI solutions, such as ChatGPT, Claude, and Perplexity, had several limitations.
They did not accurately grasp the context of the material. AI only responds to prompts provided by the user and does not fully understand the real data's content and context that the user attaches.
They did not sufficiently reflect the user's intent. The results proposed by AI were unilateral, making it challenging to subtly adjust the document to the user's desired direction.
They did not take into account the specificity of professional fields. Areas like law, academia, and education have unique formats and expressions. Existing AI fails to sensitively reflect these, and since they are developed overseas, they do not consider the characteristics of each domestic industry.
To overcome these limitations, our Inline AI team embarked on developing a specialized AI solution to support professional document creation earlier this year.
We closely collaborated with experts in law, academia, and education, designing a solution that reflects their real needs.
<Inline AI, like a real human, understands context and intent when provided with material.>
"AI Proposes the Starting Line after Understanding the Material"
Based on user feedback, we established this vision.
Solution: AI proposes the starting line after understanding the material.
This concise statement encapsulates the core values of Inline AI. More specifically, it’s as follows:
AI that Reads and Comprehends Material
Inline AI is not just a simple text generator. It is a solution that deeply analyzes and comprehends user materials.
It recognizes nearly all kinds of material formats, including PDFs, PPTs, Word documents, HWP, and web pages, understanding their content, structure, and context.
To achieve this, we developed specialized analysis algorithms tailored to various material types. Algorithms understanding the structure of PDF documents, extracting key content from web pages, identifying semantic relationships between texts, and adopting the best approaches for each material type were applied.
The most challenging part of development was identifying interrelationships between materials.
For example, enabling AI to understand how various case laws and legal provisions are connected, or how multiple research papers can be integrated, was a significant challenge.
We enhanced this ability through thousands of hours of learning and testing and are finally reaching our desired target.
AI that Proposes the Starting Line
'Starting line' is a key concept of Inline AI. Our goal is to provide a 'starting point' where users can commence substantial work instead of a finished document.
This starting line is offered in three main forms:
Data Processing and Insight Extraction: AI analyzes the data and presents key insights to the user.
Document Structure Drafting: Suggests the flow and briefly guides what content should be included in each part.
Draft Document Creation: Generates a draft with the material fully integrated, allowing the user to start from an 80% starting line.
What we valued most during this process was that 'users should be in control.'
Inline AI is designed so that the AI supports, rather than leads the process, with the user taking charge. Through the human-in-the-loop approach, users can modify AI's suggestions and adjust the direction at any time.
Thus, users can 'accept' the AI's proposals as is, or 'reject' them and finely adjust the relevant parts.
AI helps users 'start from the 80% mark.' Developing a document by utilizing the unique expertise and know-how of humans to fill in the remaining 20%, you can meet deadlines at a speed ten times faster than before by leaving most of the factual writing to AI.
<Experience a Perfect Draft Written by AI.>
👉 Try it for Free
Challenges and Triumphs in AI Development
The journey to develop Inline AI was by no means smooth. We faced numerous technical challenges and other problems encountered on site.
Technical Barriers
Firstly, processing various data formats consistently was challenging. Each format like PDF, PPT, and web pages had different data extraction methods, and getting AI to identify the context and meaning to the level of a human expert in vast, unstructured raw data was a significant challenge.
Secondly, elevating the quality of the 'starting line' proposed by AI was not easy. Developing an AI that goes beyond mere data summarization to grasp the essence of the material and suggest creative structures was a complex task.
Thirdly, designing a mechanism to effectively incorporate user feedback was challenging, a problem even big tech companies cannot easily solve. AI continues to require improvements in accurately understanding user intent and adjusting the starting line accordingly.
Field Tests and Feedback
To overcome these challenges, we prioritized field tests with actual users. We tested prototypes and gathered live feedback from law firms, research institutions, and educational sites.
In one law firm, Inline AI was used for legal opinion letters and various applications. Initially, there was an issue where AI did not capture the nuances of legal terms accurately, but it has been perfectly improved through continuous learning.
Research institutions used Inline AI for drafting paper prototypes, particularly appreciating its ability to systematically organize related research trends.
The most frequent feedback was that it was "too difficult." Being AI service developers, we focused on precisely fine-tuning AI for requested specifications. We realized that it was difficult for the general public to understand such services from a non-developer's perspective.
For example, many confused the function "Add Background Knowledge" for finely adjusting the context of AI answers and the function "@" for adding data to the instructions.
Thus, we integrated these two functions, leaving only the feature of adding material to AI instructions with "@".
Based on this feedback, we are currently overhauling inline AI to make it "much easier."
This field testing and feedback played a crucial role in the advancement of Inline AI.
<Inline AI was created through interviews with over 100 professionals, thousands of hours of learning, and hundreds of hours of coding.>
<Shortly after Inline AI's launch, we received thank-you letters from many users.>
The Present and Future of Inline AI
Currently, Inline AI is establishing itself as a specialized solution supporting document creation in legal, academic, educational, and business fields.
Attorneys use it for factual organization and document draft creation, researchers for paper translation/summary and draft creation, and teachers for drafting various documents and student records with Inline AI.
The response from users is far more positive than we anticipated.
Feedback like "I save over 10 hours a week thanks to this tool," from an attorney, "Paper summary and draft creation time reduced by 30%," from a researcher, and "Thanks to it, I could finish the business plan in a day" from an aspiring entrepreneur bring us great satisfaction.
Our journey is just beginning. Moving forward, Inline AI aims to develop in the following directions:
Support for More Material Types: In addition to currently supported PDFs, PPTs, web pages, and texts, we plan to strengthen our multimedia data analysis capabilities for formats like audio and video.
Document Template Support: We will learn the specialized document formats and structures of each professional field to suggest more professional starting lines.
Enhanced Collaboration Features: Considering the reality that many documents are created in teams, we plan to develop features for multiple users to utilize Inline AI collaboratively.
Our Vision: To Enable All Professionals to Focus on Their Core Tasks
The ultimate vision of Inline AI is clear. It is to help experts free themselves from the repetitive task of document writing and reinvest more time into their true expertise.
Legal experts will be able to invest more in legal research and strategy development. Researchers will focus more on in-depth experiments and analyses. Teachers will deploy more capacity to care for individual students and offer customized guidance.
This is how Inline AI aims to 'change the world.'
It's not just about writing more documents faster, but rather helping experts in each field realize their true value. This is the reason behind the development of Inline AI and the driving force that will continue to spur its advancement.
With Inline AI, liberate yourself from the burden of document creation and fully showcase your true expertise.
We will continue to tirelessly strive to suggest even better 'starting lines.'
Thank you.
The Only AI That Understands Your Material and Proposes the Starting Line
👉 Try it for Free
📺 Watch AI Write a Perfect Document Draft - Demo Video
Why Document Creation Remains a Challenge in the AI Era
"Attorney, when will you send the opinion letter? I'd like to review the draft before it goes to court."
"When will the draft of the paper be ready? The conference is asking. You know the submission deadline is approaching, right?"
"Teacher, have you completed the student records? Let's all finish them this week."
'Document work' constitutes a significant portion of tasks not only for office workers but also for professional occupations.
In reality, however, documents are merely the results that convey thoughts, expertise, and know-how, rather than the core of one's professional capabilities.
Still, it's a fact that document work consumes a substantial amount of time.
Attorneys spend more time drafting documents than on case analysis or trial strategy preparation.
Researchers spend more time reading others' research contributions or completing assignments from professors and writing documents for government-supported projects, rather than delving into their own research.
Teachers likewise spend more time writing student records and responding to education office requests than preparing for classes.
Thus, many professionals are spending too much time on document creation rather than their core duties.
Our Inline AI team sought to solve this issue.
We all have experienced spending more time on 'document writing' than on 'essential tasks' in our respective specialties.
It's a significant problem that professionals waste precious time on repetitive tasks like data organization and document writing instead of focusing on their specialization, and it ultimately leads to a substantial loss for society.
<Last year alone, I wrote over 500 documents that went unread.>
Problems Observed on the Ground by the Inline AI Team
Our team conducted interviews with dozens of experts from the legal, academic, and educational fields and identified three major issues.
1. Difficulty in Analyzing and Integrating Data
"There's so much data, but I don't know how to piece it all together."
Experts possessed a vast amount of data. They had various types of information such as reports, papers, case law, textbooks, and website data stored on computers or drives.
Nevertheless, due to the immense amount of time and effort needed to systematically analyze and integrate these materials, they were often left unutilized or completely neglected.
Lawyers must read and analyze dozens to hundreds of cases and client materials, researchers must summarize and translate hundreds of papers each month, and teachers face the daily challenge of synthesizing multiple textbooks and reference materials.
2. Challenging 'Drafting' Process even for Experts
"Getting those first words down is the hardest part."
Many experts found the 'initiation' of a document the most challenging part.
The process of deciding the structure, contents to include, and where to begin took considerable time.
Particularly for documents like legal papers or academic theses, which are extensive and complex by nature, the difficulty in setting the 'starting line' was more pronounced.
3. Repetitive Revision Work
"Even after drafting, it's not finished; I end up working late or on weekends due to revisions and finalizations."
Professional document writing doesn't end with the initial draft.
Revisions incorporating feedback, adaptations to changing situations, and structural changes result in time-consuming, repetitive tasks for experts.
The Birth of Inline AI
Recognizing these issues made us curious.
"Could AI resolve this problem?"
Recent advances in AI technology have achieved spectacular progress in text generation and comprehension capabilities. However, general-purpose generative AI solutions, such as ChatGPT, Claude, and Perplexity, had several limitations.
They did not accurately grasp the context of the material. AI only responds to prompts provided by the user and does not fully understand the real data's content and context that the user attaches.
They did not sufficiently reflect the user's intent. The results proposed by AI were unilateral, making it challenging to subtly adjust the document to the user's desired direction.
They did not take into account the specificity of professional fields. Areas like law, academia, and education have unique formats and expressions. Existing AI fails to sensitively reflect these, and since they are developed overseas, they do not consider the characteristics of each domestic industry.
To overcome these limitations, our Inline AI team embarked on developing a specialized AI solution to support professional document creation earlier this year.
We closely collaborated with experts in law, academia, and education, designing a solution that reflects their real needs.
<Inline AI, like a real human, understands context and intent when provided with material.>
"AI Proposes the Starting Line after Understanding the Material"
Based on user feedback, we established this vision.
Solution: AI proposes the starting line after understanding the material.
This concise statement encapsulates the core values of Inline AI. More specifically, it’s as follows:
AI that Reads and Comprehends Material
Inline AI is not just a simple text generator. It is a solution that deeply analyzes and comprehends user materials.
It recognizes nearly all kinds of material formats, including PDFs, PPTs, Word documents, HWP, and web pages, understanding their content, structure, and context.
To achieve this, we developed specialized analysis algorithms tailored to various material types. Algorithms understanding the structure of PDF documents, extracting key content from web pages, identifying semantic relationships between texts, and adopting the best approaches for each material type were applied.
The most challenging part of development was identifying interrelationships between materials.
For example, enabling AI to understand how various case laws and legal provisions are connected, or how multiple research papers can be integrated, was a significant challenge.
We enhanced this ability through thousands of hours of learning and testing and are finally reaching our desired target.
AI that Proposes the Starting Line
'Starting line' is a key concept of Inline AI. Our goal is to provide a 'starting point' where users can commence substantial work instead of a finished document.
This starting line is offered in three main forms:
Data Processing and Insight Extraction: AI analyzes the data and presents key insights to the user.
Document Structure Drafting: Suggests the flow and briefly guides what content should be included in each part.
Draft Document Creation: Generates a draft with the material fully integrated, allowing the user to start from an 80% starting line.
What we valued most during this process was that 'users should be in control.'
Inline AI is designed so that the AI supports, rather than leads the process, with the user taking charge. Through the human-in-the-loop approach, users can modify AI's suggestions and adjust the direction at any time.
Thus, users can 'accept' the AI's proposals as is, or 'reject' them and finely adjust the relevant parts.
AI helps users 'start from the 80% mark.' Developing a document by utilizing the unique expertise and know-how of humans to fill in the remaining 20%, you can meet deadlines at a speed ten times faster than before by leaving most of the factual writing to AI.
<Experience a Perfect Draft Written by AI.>
👉 Try it for Free
Challenges and Triumphs in AI Development
The journey to develop Inline AI was by no means smooth. We faced numerous technical challenges and other problems encountered on site.
Technical Barriers
Firstly, processing various data formats consistently was challenging. Each format like PDF, PPT, and web pages had different data extraction methods, and getting AI to identify the context and meaning to the level of a human expert in vast, unstructured raw data was a significant challenge.
Secondly, elevating the quality of the 'starting line' proposed by AI was not easy. Developing an AI that goes beyond mere data summarization to grasp the essence of the material and suggest creative structures was a complex task.
Thirdly, designing a mechanism to effectively incorporate user feedback was challenging, a problem even big tech companies cannot easily solve. AI continues to require improvements in accurately understanding user intent and adjusting the starting line accordingly.
Field Tests and Feedback
To overcome these challenges, we prioritized field tests with actual users. We tested prototypes and gathered live feedback from law firms, research institutions, and educational sites.
In one law firm, Inline AI was used for legal opinion letters and various applications. Initially, there was an issue where AI did not capture the nuances of legal terms accurately, but it has been perfectly improved through continuous learning.
Research institutions used Inline AI for drafting paper prototypes, particularly appreciating its ability to systematically organize related research trends.
The most frequent feedback was that it was "too difficult." Being AI service developers, we focused on precisely fine-tuning AI for requested specifications. We realized that it was difficult for the general public to understand such services from a non-developer's perspective.
For example, many confused the function "Add Background Knowledge" for finely adjusting the context of AI answers and the function "@" for adding data to the instructions.
Thus, we integrated these two functions, leaving only the feature of adding material to AI instructions with "@".
Based on this feedback, we are currently overhauling inline AI to make it "much easier."
This field testing and feedback played a crucial role in the advancement of Inline AI.
<Inline AI was created through interviews with over 100 professionals, thousands of hours of learning, and hundreds of hours of coding.>
<Shortly after Inline AI's launch, we received thank-you letters from many users.>
The Present and Future of Inline AI
Currently, Inline AI is establishing itself as a specialized solution supporting document creation in legal, academic, educational, and business fields.
Attorneys use it for factual organization and document draft creation, researchers for paper translation/summary and draft creation, and teachers for drafting various documents and student records with Inline AI.
The response from users is far more positive than we anticipated.
Feedback like "I save over 10 hours a week thanks to this tool," from an attorney, "Paper summary and draft creation time reduced by 30%," from a researcher, and "Thanks to it, I could finish the business plan in a day" from an aspiring entrepreneur bring us great satisfaction.
Our journey is just beginning. Moving forward, Inline AI aims to develop in the following directions:
Support for More Material Types: In addition to currently supported PDFs, PPTs, web pages, and texts, we plan to strengthen our multimedia data analysis capabilities for formats like audio and video.
Document Template Support: We will learn the specialized document formats and structures of each professional field to suggest more professional starting lines.
Enhanced Collaboration Features: Considering the reality that many documents are created in teams, we plan to develop features for multiple users to utilize Inline AI collaboratively.
Our Vision: To Enable All Professionals to Focus on Their Core Tasks
The ultimate vision of Inline AI is clear. It is to help experts free themselves from the repetitive task of document writing and reinvest more time into their true expertise.
Legal experts will be able to invest more in legal research and strategy development. Researchers will focus more on in-depth experiments and analyses. Teachers will deploy more capacity to care for individual students and offer customized guidance.
This is how Inline AI aims to 'change the world.'
It's not just about writing more documents faster, but rather helping experts in each field realize their true value. This is the reason behind the development of Inline AI and the driving force that will continue to spur its advancement.
With Inline AI, liberate yourself from the burden of document creation and fully showcase your true expertise.
We will continue to tirelessly strive to suggest even better 'starting lines.'
Thank you.