Method and system for automatically generating bidding document based on bid invitation requirement

Abstract

The invention discloses a method and system for automatically generating a bidding document based on a bidding requirement, and relates to the technical field of bidding, and the method comprises the steps: obtaining a bidding requirement file, analyzing and extracting core information, collecting historical materials, building an enterprise bidding database, comparing the core information with database resources, and obtaining matched resources; building a framework filling content according to the matching resources and the bidding specifications to form a draft, and finally verifying and perfecting to make a final bidding file; according to the method, manpower, material resources and time consumption of bidding document making can be reduced, the omission or misunderstanding risk during manual bidding requirement interpretation is reduced, the bidding discarding possibility is reduced, repeated labor caused by enterprise bidding resource dispersion is avoided, the making efficiency is improved, meanwhile, the problem of content inconsistency is reduced, and the making quality of the bidding document is fundamentally improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bidding, more particularly to a method and system for automatically generating a bid file based on bidding requirements. BACKGROUND

[0002] Currently, in the current bidding activities, the production of the bid file often needs to consume a large amount of manpower, material resources and time. The bidder needs to carefully read the bidding requirements, and then collects and organizes relevant qualification files, technical data, case information, etc. from the enterprise, and then writes and formats according to the format and content of the bidding requirements.

[0003] The traditional bid file production method has many drawbacks: on the one hand, the bidding requirements are usually complex, containing a large number of clauses and details, and manual interpretation is easy to miss or misinterpret, resulting in the bid file not meeting the requirements and being rejected; on the other hand, the bidding resources of the enterprise are scattered, and each time the bid file is produced, it needs to be searched, organized and edited again, which is a lot of repetitive work, low efficiency, and easy to cause inconsistent content.

[0004] With the development of information technology, although some bid file production auxiliary tools have appeared, these tools mostly only provide templates and cannot automatically match and fill the content according to the bidding requirements, still requiring a large amount of manual operation, and failing to fundamentally solve the above problems.

[0005] Therefore, there is an urgent need for a method for automatically generating a bid file based on bidding requirements to improve the efficiency and quality of bid file production. SUMMARY

[0006] Therefore, the present application provides a method and system for automatically generating a bid file based on bidding requirements to solve the problems in the background art.

[0007] In order to achieve the above purpose, the present application adopts the following technical solutions:

[0008] A method for automatically generating a bid file based on bidding requirements, comprising:

[0009] S1, obtaining a bidding requirement file and analyzing the bidding requirement file to extract core information of the bidding requirements;

[0010] S2, collecting historical qualification materials, project cases and technical scheme template data to build an enterprise bid database;

[0011] S3, comparing the core information extracted in S1 with the resources in the enterprise bid database to obtain matched bid resources;

[0012] S4, constructing a bidding file framework according to the matched bidding resource and the bidding demand file composition specification, and filling in the content to form a bidding file draft;

[0013] S5, verifying and perfecting the bidding file draft to produce a final bidding file.

[0014] Optionally, the analysis of the bidding demand file and the extraction of the bidding demand core information specifically include:

[0015] According to the industry type, the bidding demand files are classified to obtain industry bidding demands, and the binary conversion is respectively implemented on the bidding demands of each industry to obtain binary images;

[0016] The inclination correction is implemented on each binary image to obtain a corrected image, and the noise reduction conversion is implemented on each corrected image to obtain a noise reduction image;

[0017] The title position of each noise reduction image is obtained by positioning and identifying the title of each noise reduction image, and the title paragraph is obtained by segmenting the noise reduction image according to the title position;

[0018] The structured conversion is implemented on each title paragraph to obtain the bidding demand core information.

[0019] Optionally, the construction of the enterprise bidding database specifically includes:

[0020] The historical qualification materials, project cases, and technical scheme template data are collected as historical bidding materials and material keywords associated with the historical bidding materials;

[0021] The label library is called, and the material labels of each historical bidding material are defined according to the label library and the material keywords, wherein the label library includes the mapping relationship between keywords and labels;

[0022] The enterprise bidding database is constructed according to the association relationship between the historical bidding materials and the material labels.

[0023] Optionally, the enterprise bidding database also pre-stores standard content information, various bidding file specification format materials, qualification picture materials, technical materials, and fixed text materials having a mapping relationship with the keywords; the enterprise bidding database is stored in the enterprise bidding database according to the mapping mode of keyword-text, keyword-table, keyword-picture, and keyword-keyword.

[0024] Optionally, S3 specifically includes:

[0025] The extracted core information of the bidding demand is compared with the material tags and standard content information corresponding to the same keyword in the enterprise bidding database, effective fields in the content information before and after the core information of the bidding demand are identified, the effective fields are associated and bound with the core information of the bidding demand, and the associated data is classified and saved into the enterprise bidding database according to the data categories.

[0026] Optionally, the S4 is specifically:

[0027] The content format of the bidding document is called, the called content format is compared with the saved various bidding document specification format materials in the enterprise bidding database, and a standard format bidding document template is created in the form of a word document according to the comparison result;

[0028] The qualification key words, technical key words and other contents are extracted from the extracted core information of the bidding demand, the corresponding qualification picture materials, technical materials and fixed text materials in the enterprise bidding database are called according to the qualification key words, technical key words and other contents, the called qualification picture materials, technical materials and fixed text materials are filled into the corresponding positions in the bidding document template, and thus a bidding document draft is formed.

[0029] Optionally, the formed bidding document draft is further saved in a target file storage directory, specifically including: determining a file storage directory to be packaged, and checking whether there is a subdirectory folder under the file storage directory;

[0030] If there is, the next level subdirectory folder under the subdirectory folder is determined by using a recursive algorithm, and all the folders are stored in a file compression package in a pre-set output packaging directory according to the current recursive order;

[0031] If there is not, the files under the file storage directory are stored in a file compression package in a pre-set output packaging directory.

[0032] Optionally, the storing of all the folders in a file compression package in a pre-set output packaging directory according to the current recursive order includes:

[0033] In the case that the input file directory is a folder, it is determined to continue to search all the folders and files under the folder by using a recursive method until the file is found, and a single-level directory and file packaging method is used to implement compression packaging;

[0034] All the subdirectories under the first layer directory are traversed one by one, and after all the files are confirmed, the files are uniformly stored in the file compression package in the output packaging directory.

[0035] Optionally, the verifying and perfecting of the draft of the bidding document specifically comprises implementing document detection on the draft of the bidding document.

[0036] Implementing spelling detection on the draft of the bidding document to obtain a spelling detection result;

[0037] Implementing semantic detection on the draft of the bidding document to obtain a semantic detection result;

[0038] The document detection result comprises the semantic detection result and the spelling detection result;

[0039] Implementing document revision on the draft of the bidding document according to the document detection result, and exporting the final bidding document after the document revision.

[0040] A system for automatically generating a bidding document based on bidding requirements, comprising:

[0041] A file parsing module that obtains a bidding requirement document and analyzes the bidding requirement document to extract core information of the bidding requirement;

[0042] A resource library construction module that collects historical qualification materials, project cases and technical scheme template data to build an enterprise bidding resource library;

[0043] A bidding resource matching module that compares the extracted core information with resources in the enterprise bidding resource library to obtain matched bidding resources;

[0044] A document preliminary draft generation module that builds a bidding document framework according to the matched bidding resources and a document composition specification of the bidding requirement, and fills in the content to form a draft of the bidding document;

[0045] A document revision module that verifies and perfects the draft of the bidding document to produce a final bidding document.

[0046] According to the above technical solution, compared with the prior art, the present disclosure provides a method and system for automatically generating a bidding document based on bidding requirements, which obtains a bidding requirement document and analyzes and extracts core information, collects historical materials to build an enterprise bidding resource library, compares the core information with resources in the resource library to obtain matched resources, builds a framework according to the matched resources and a bidding specification, fills in the content to form a draft, and finally verifies and perfects the draft to produce a final bidding document. The present disclosure can reduce the consumption of manpower, material resources and time in producing a bidding document, reduce the risk of omission or misunderstanding when manually interpreting bidding requirements to reduce the possibility of disqualification, avoid repetitive labor caused by the dispersion of enterprise bidding resources, improve production efficiency, reduce content inconsistency, and fundamentally improve the production quality of bidding documents. BRIEF DESCRIPTION OF DRAWINGS

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the method flow provided by the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] This invention discloses a method for automatically generating tender documents based on bidding requirements, such as... Figure 1 As shown, it includes:

[0051] S1. Obtain the tender requirements document, analyze the tender requirements document, and extract the core information of the tender requirements;

[0052] S2. Collect historical qualification materials, project cases, and technical solution templates to build a corporate bidding information database;

[0053] S3. Compare the core information extracted in S1 with the resources in the enterprise bidding database to obtain matching bidding resources;

[0054] S4. Based on the document composition specifications of the matching bidding resources and bidding requirements, construct the bid document framework, fill in the content, and form a draft bid document;

[0055] S5. Verify and improve the draft tender documents, and prepare the final tender documents.

[0056] In a specific embodiment, analyzing the bidding requirements document and extracting the core information of the bidding requirements specifically includes:

[0057] The bidding requirements documents are categorized according to industry type to obtain industry bidding requirements, and then binarized into binarized images for each industry bidding requirement.

[0058] Tilt correction is applied to each binarized image to obtain a corrected image, and noise reduction conversion is applied to each corrected image to obtain a noise-reduced image;

[0059] The file titles in each denoised image are located and identified to obtain the title positions. Based on the title positions, each denoised image is divided into paragraphs to obtain the title paragraphs.

[0060] The structure of each heading paragraph is transformed to obtain the core information of the bidding requirements.

[0061] This process involves using web scraping technology to retrieve bidding requirement documents from the internet for the entire industry, categorizing them by industry to obtain various bidding requirement documents. In this step, a layout analysis technique can be used to extract the textual information (paragraphs, table content, etc.) of the bidding requirement documents in a structured manner to obtain the core information of the bidding requirements.

[0062] In a specific embodiment, building a corporate bidding data database involves the following steps:

[0063] Collect historical qualification materials, project cases, and technical solution templates as historical bidding materials and related keywords;

[0064] Specifically, historical bidding materials can be collected to build a corporate bidding database, and semantic analysis can be performed on the acquired historical bidding materials. That is, keywords can be extracted from the historical bidding materials using the SBERT model to obtain the material keywords associated with each historical bidding material.

[0065] Retrieve the tag library and define the material tags for each historical bidding material based on the tag library and material keywords. The tag library contains the mapping relationship between keywords and tags.

[0066] Specifically, material tags refer to the categories or content used to mark historical bidding materials. They are key information that identifies historical bidding materials and serve as a tagging tool to facilitate searching and locating. The tag library includes the correspondence between keywords and tags.

[0067] Optionally, material tags for each historical bidding material can be defined based on the tag library and material keywords, including: determining whether the tag library contains material keywords; if so, using the tags in the tag library corresponding to the material keywords as material tags; otherwise, using the tags entered by the user as material tags.

[0068] Specifically, since the tag library includes the correspondence between tags and keywords, after determining the material keyword, it can be determined whether the tag library contains the material keyword, that is, whether the material keyword already has a corresponding tag. If so, the tag in the tag library corresponding to the material keyword is used as the material tag; otherwise, it means that the material keyword does not have a tag, and the user-set tag will be used as the material tag.

[0069] A database of enterprise bidding materials is built based on the relationships between historical bidding materials and material tags.

[0070] Specifically, since each historical bidding material has a corresponding material tag, a corporate bidding data database can be built based on the correspondence between historical bidding materials and material tags. After the corporate bidding data database is built, the bidding materials that match the bidding requirements document can be determined based on the material tags.

[0071] In one specific embodiment, the enterprise bidding database also pre-stores standard content information that has a mapping relationship with keywords, various bidding document specification formats, qualification image data, technical data, and fixed text data; the enterprise bidding database stores these according to the mapping methods of keyword-text, keyword-table, keyword-image, and keyword-keyword.

[0072] In a specific embodiment, S3 specifically includes:

[0073] The core information of the extracted bidding requirements is compared with the material tags and standard content information corresponding to the same keyword in the enterprise's bidding data database. The effective fields in the content information before and after the core information of the bidding requirements are identified, and the effective fields are associated and bound with the core information of the bidding requirements. The associated data is then saved to the enterprise's bidding data database according to the data category.

[0074] In a specific embodiment, S4 is specifically:

[0075] Retrieve the content format of the bidding documents, compare the retrieved content format with various standard bidding document formats stored in the enterprise's bidding data database, and create a standard format bidding document template in the form of a Word document based on the comparison results;

[0076] Specifically, in the past, the format requirements for the attachments to the tender documents had to be strictly followed during the tender document preparation process. These included the cover, table of contents, and bid summary table. In this method, multiple types of tender document formats are pre-stored, and the required content for each format is associated with keywords. Upon obtaining a new tender document format, each format is matched against the company's bid database. For each format, statistical analysis is performed on table format types, text word count, keyword frequency, and punctuation frequency, and corresponding parameter values ​​are set. Simultaneously, the company's bid database defines specific parameter ranges based on the original format's table parameter values. If the new table parameter values ​​match the range, the format is considered a perfect match with the database's preset formats. If the format deviates from the database's preset formats, the original tender document format is used, and the deviation is highlighted in a different color, entered into the database, and the preset format's parameter range is modified. After the matching process is complete, a bid document template in the prescribed format is generated as a Word document.

[0077] From the core information of the extracted bidding requirements, qualification keywords, technical keywords, and other content are selected and extracted. Based on the qualification keywords, technical keywords, and other content, the corresponding qualification images, technical documents, and fixed text documents are retrieved from the enterprise bidding data database. The retrieved qualification images, technical documents, and fixed text documents are then filled into the corresponding positions in the bid document template to form a draft bid document.

[0078] Specifically, the main contents of a tender document generally include qualification information, technical information, and fixed text (or other documents).

[0079] This method manages qualification documents from recent years, automatically inputting them from the company's bidding database, associating qualification images with corresponding keywords, and alerting users to any missing or outdated qualification documents based on recent bidding requirements. When qualification-based bidding content is needed, the method automatically retrieves qualification image data from the company's bidding database based on qualification keywords and inputs it into the corresponding location in the draft bid document.

[0080] Technical content typically includes service commitments, technical training materials, and descriptions of technical performance parameters. This method automatically downloads policy documents and regional documents from recent years, performs text analysis on the document content, associates policy documents using keywords and weights, and extracts background, guiding principles, and timelines from the policy documents, linking and storing these elements in the enterprise's bidding database. When technical bidding content is required, the method matches the bidding documents with the content in the enterprise's bidding database based on the industry type, technology-related type, and region information. The Sunday string matching algorithm is used to determine the frequency of occurrence of strings such as industry type, and appropriate service commitments, technical training materials, descriptions of technical performance parameters, and policy documents are selected based on the frequency of occurrence. Simultaneously, key content from the policy documents is automatically entered into the designated location of the technical content, thus completing the generation of technical content.

[0081] Fixed text (the content of the performance commitment letter generally includes the company name, date, company seal, etc.). When a fixed text needs to be generated, the enterprise bidding database is read, and the content is generated in the designated location of the draft bid document.

[0082] In one specific embodiment, the method further includes saving the resulting draft tender document in the target file storage directory, specifically including: specifying the file storage directory to be packaged, and checking whether there are subdirectories or folders under the file storage directory;

[0083] The storage directory for the files to be packaged can be determined by the user, who can choose one of the categories as the storage directory; or the root directory where the report file is stored can be directly used as the storage directory for the files to be packaged.

[0084] If it exists, use a recursive algorithm to identify the next level subdirectory folder under the subdirectory folder, and store all folders in the file archive in the pre-set output packaging directory according to the current recursive order;

[0085] The output packaging directory refers to the confirmed storage location for the compressed file. This can be determined based on the actual situation, and other directories can be selected.

[0086] The function for packaging multi-level directories and subdirectories: If the input file directory is a folder, a recursive method is used to continue searching for all folders and files under that folder until a file is found. At that point, the single-level directory and file packaging method is called to compress and package the file. All subdirectories under the first-level directory are traversed one by one until all files are identified, and then all files are output together to the compressed file package in the output packaging directory. Alternatively, all files output to the output packaging directory can retain their original format, or each subfolder can be packaged and input as a compressed file package.

[0087] If the file does not exist, the file in the file storage directory will be stored in a compressed file package in the pre-set output packaging directory.

[0088] Single-level directory and file packaging function: If the input file storage directory does not contain any folders, then directly package the files in that storage directory. For example, the ZIP tool code is used directly for file compression and packaging.

[0089] In one specific embodiment, all folders are stored in a pre-set compressed file package in the current recursive order, including:

[0090] If the input file directory is a folder, then a recursive method will be used to continue searching for all folders and files under the folder until the file is found. Then, the single-level directory and file packaging method will be used to compress and package the file.

[0091] Iterate through all subdirectories under the first-level directory one by one until all files are confirmed, and then save them all into a compressed file in the output packaging directory.

[0092] In a specific embodiment, verifying and improving the draft tender document specifically includes performing document inspection on the draft tender document:

[0093] Spell check was performed on the draft tender documents, and the spell check results were obtained;

[0094] Perform semantic analysis on the draft tender documents and obtain the semantic analysis results;

[0095] The document detection results include semantic detection results and spelling detection results;

[0096] Specifically, spell detection on the draft bid document can effectively detect spelling errors; semantic detection on the draft bid document can effectively detect semantic errors. Both spelling and semantic detection can be performed using existing models.

[0097] Based on the document inspection results, revise the draft tender document and export the final revised tender document.

[0098] Specifically, the revised final tender documents can also be submitted to human reviewers for final review. The reviewers can make further adjustments and revisions to ensure that the tender documents meet the actual situation and customer requirements.

[0099] A system for automatically generating tender documents based on bidding requirements, comprising:

[0100] The document parsing module obtains the bidding requirements document, analyzes the bidding requirements document, and extracts the core information of the bidding requirements.

[0101] The resource library construction module collects historical qualification materials, project cases, and technical solution templates to build a database of enterprise bidding materials.

[0102] The bidding resource matching module compares the extracted core information with the resources in the enterprise bidding database to obtain matching bidding resources;

[0103] The document draft generation module builds a bid document framework based on the document composition specifications of the matching bidding resources and bidding requirements, and fills in the content to form a bid document draft.

[0104] The document revision module verifies and improves the draft tender documents, producing the final tender documents.

[0105] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0106] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for automatically generating tender documents based on bidding requirements, characterized in that, include: S1. Obtain the tender requirements document, analyze the tender requirements document, and extract the core information of the tender requirements; S2. Collect historical qualification materials, project cases, and technical solution templates to build a corporate bidding information database; S3. Compare the core information extracted in S1 with the resources in the enterprise bidding database to obtain matching bidding resources; S4. Based on the document composition specifications of the matching bidding resources and bidding requirements, construct the bid document framework, fill in the content, and form a draft bid document; S5. Verify and improve the draft tender documents, and prepare the final tender documents.

2. The method for automatically generating tender documents based on bidding requirements according to claim 1, characterized in that, The analysis of the bidding requirements document and the extraction of the core information of the bidding requirements specifically includes: The bidding requirements documents are categorized according to industry type to obtain industry bidding requirements, and then binarized into binarized images for each industry bidding requirement. Tilt correction is applied to each binarized image to obtain a corrected image, and noise reduction conversion is applied to each corrected image to obtain a noise-reduced image; The file titles in each denoised image are located and identified to obtain the title positions. Based on the title positions, each denoised image is divided into paragraphs to obtain title paragraphs. The structure of each heading paragraph is transformed to obtain the core information of the bidding requirements.

3. The method for automatically generating tender documents based on bidding requirements according to claim 1, characterized in that, The establishment of the enterprise bidding data database specifically refers to: Collect historical qualification materials, project cases, and technical solution templates as historical bidding materials, as well as related keywords for these historical bidding materials; Retrieve the tag library and define the material tags for each historical bidding material based on the tag library and the material keywords, wherein the tag library contains the mapping relationship between keywords and tags; A database of enterprise bidding materials is built based on the relationships between the historical bidding materials and material tags.

4. The method for automatically generating tender documents based on bidding requirements according to claim 3, characterized in that, The enterprise bidding database also pre-stores standard content information that has a mapping relationship with the keywords, various bidding document standard format materials, qualification image materials, technical materials, and fixed text materials; the enterprise bidding database stores information according to the mapping methods of keywords-text, keywords-table, keywords-image, and keywords-keyword.

5. The method for automatically generating tender documents based on bidding requirements according to claim 4, characterized in that, S3 specifically includes: The core information of the extracted bidding requirements is compared with the material tags and standard content information corresponding to the same keyword in the enterprise's bidding data database. The effective fields in the content information before and after the core information of the bidding requirements are identified, and the effective fields are associated and bound with the core information of the bidding requirements. The associated data is then saved to the enterprise's bidding data database according to the data category.

6. The method for automatically generating tender documents based on bidding requirements according to claim 1, characterized in that, Specifically, S4 is: Retrieve the content format of the bidding documents, compare the retrieved content format with various standard bidding document formats stored in the enterprise's bidding data database, and create a standard format bidding document template in the form of a Word document based on the comparison results; From the core information of the extracted bidding requirements, qualification keywords, technical keywords, and other content are selected and extracted. Based on the qualification keywords, technical keywords, and other content, the corresponding qualification images, technical documents, and fixed text documents are retrieved from the enterprise bidding data database. The retrieved qualification images, technical documents, and fixed text documents are then filled into the corresponding positions in the bid document template to form a draft bid document.

7. The method for automatically generating tender documents based on bidding requirements according to claim 6, characterized in that, It also includes saving the resulting draft tender documents in the target file storage directory, specifically including: specifying the file storage directory to be packaged, and checking whether there are subdirectories or folders under the file storage directory; If it exists, a recursive algorithm is used to identify the next level subdirectory folder under the subdirectory folder, and all folders are stored in the file archive in the pre-set output packaging directory according to the current recursive order; If the file does not exist, the file in the file storage directory will be stored in a compressed file package in the pre-set output packaging directory.

8. The method for automatically generating tender documents based on bidding requirements according to claim 7, characterized in that, The step of storing all folders in the pre-set output packaging directory in the current recursive order includes: If the input file directory is a folder, then a recursive method will be used to continue searching for all folders and files under the folder until the file is found. Then, the single-level directory and file packaging method will be used to compress and package the file. Iterate through all subdirectories under the first-level directory one by one until all files are confirmed, and then store them all in the compressed file package in the output packaging directory.

9. The method for automatically generating tender documents based on bidding requirements according to claim 1, characterized in that, The verification and improvement of the draft bid documents specifically includes document inspection of the draft bid documents: Spell check was performed on the draft tender documents, and the spell check results were obtained; Perform semantic analysis on the draft tender documents and obtain the semantic analysis results; The document detection results include the semantic detection results and the spelling detection results; Based on the document inspection results, revise the draft tender document and export the final revised tender document.

10. A system for automatically generating tender documents based on bidding requirements, characterized in that, A method for automatically generating tender documents based on tender requirements according to any one of claims 1-9, comprising: The document parsing module obtains the bidding requirements document, analyzes the bidding requirements document, and extracts the core information of the bidding requirements. The resource library construction module collects historical qualification materials, project cases, and technical solution templates to build a database of enterprise bidding materials. The bidding resource matching module compares the extracted core information with the resources in the enterprise bidding database to obtain matching bidding resources; The document draft generation module builds a bid document framework based on the document composition specifications of the matching bidding resources and bidding requirements, and fills in the content to form a bid document draft. The document revision module verifies and improves the draft tender documents, producing the final tender documents.

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