Debt Collection Projects
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A YouTube video intro and outro
We are expanding our popular audio podcast to YouTube, and we require the creation of a captivating video intro and outro to enhance the viewing experience for our audience. Our podcast features engaging content and a dedicated following, and we aim to replicate that success in the video format. To kickstart this project, we have already gathered a collection of graphics, including our logo and social media templates, which can serve as valuable inspiration for the video intro and outro. Additionally, we have pre-recorded audio idents that can be incorporated into the video to create a seamless and cohesive experience. We are seeking a talented freelancer with experience in video production to bring our vision to life. The ideal candidate should have a keen eye for design, a strong understanding of audio and video editing techniques, and the ability to work collaboratively with our team to achieve our goals. The video intro and outro should be approximately 10 seconds long each and should seamlessly integrate our graphics, audio idents, and any additional elements you may suggest. We are open to creative suggestions and are eager to work with you to create a visually stunning and memorable introduction and conclusion to our YouTube videos. If you are a passionate video producer with a track record of creating engaging content, we would love to hear from you. Please submit your portfolio and a proposal outlining your approach to this project, including your estimated timeline and cost. We look forward to collaborating with you to take our podcast to the next level on YouTube.
21 days ago28 proposalsRemoteSAMPLE MACHINIST NEEDED FOR RTW TAILORING PRE PROD SAMPLES.
Our brand is built upon the principles of craftsmanship, timelessness, and sustainability, and we are actively seeking an experienced garment machinist with expertise in sewing tailored garments such as blazers and coats. Our inaugural collection will feature meticulously crafted pieces made from only the finest natural materials and luxury fabrications, such as 100% virgin wool and 100% cashmere. Every aspect of our garments, from the design to the construction, is meant to showcase the highest level of quality and longevity, which is why we require the skills of a true master in the art of tailoring. As a brand that values sustainability, we are dedicated to minimizing our environmental impact and promoting ethical practices throughout our supply chain. We believe that by working with a skilled artisan like yourself, who possesses a deep understanding of garment construction and tailoring techniques, we can create pieces that not only look beautiful but also stand the test of time, reducing the need for frequent replacements and contributing to a more sustainable fashion industry. Your experience in sewing tailored garments, particularly blazers and coats, would be invaluable in ensuring that our pre-production samples meet our exacting standards and reflect the brand's ethos of timeless craftsmanship. We are seeking a collaborator who can bring our designs to life with precision and attention to detail, ensuring that every stitch and seam is executed flawlessly. If you are interested in working with us on this exciting project, please let me know. We would be thrilled to discuss our vision and requirements in more detail and to learn more about your skills, experiences, and expertise in tailoring. Together, we can create timeless pieces that celebrate the art of garment making while prioritizing sustainability.
20 days ago13 proposalsRemoteopportunity
Software Developer Wanted - Need Automation Bot For TikTok Shop
Hi, I would like to get an automation bot created for doing messaging outreach on TikTok Shops. This will be a long term part time or full time position since I will need your help to make adjustments to the bot as needed. I will be using this bot for my own personal purposes but I also want to be able to sell the bot as a paid monthly service so that other TikTok Shop Owners can use it as well. This position is ideal for someone that has very strong knowledge of software development. In a perfect world - I would like the bot to be able to offer some sort of personalization so that the TikTok user thinks its a unique message and that we are not mass messaging them. This might be possible to do with Chatgpt...but I'm not sure. If you have knowledge on how we can incorporate Chatgpt or AI into this bot to offer personalization then that would be a very big advantage for you. If you have an idea of how we can offer personalization into the messaging then please be sure to mention that in the message you write to me. Here are the list of features that I want the bot to have: - It needs to be able to select the filters that I want and send a pre written message one by one to the TikTok user that appear in the search results. - It needs to be able to send a pre written follow up message to TikTok users that did NOT reply to the initial message that the bot sent out. - It needs to be able to skip a TikTok users profile if the software has already messaged them (Is this possible to do?) - If the TikTok user has an email address in the bio then I would like to have the bot collect the email address and store it separately in an excel file (Is this possible to do?) Please reply back with your answers to these questions: 1. Have you created an automation bot before in the past? If so, can you please provide me with a link to the bot you created or a description of the bots features that you have created? 2. The bot needs to mimc human behavior so that it avoids detection from TikTok. It will need to have a random timer in between messages that it sends out. Do you have any other suggestions as to what else we can implement to avoid detection by TikTok? 3. What is your desired hourly pay? 4. What is the rough total cost for this project to be completed? 5. How long will it take you to create this bot? 6. Should this bot be web based, a desktop app that the customer downloads, chrome extension…etc? What do you recommend and why do you recommend that?
21 days ago10 proposalsRemoteopportunity
Automated Semantic Text Analysis Pipeline
Comprehensive Use Case Specification: Automated Semantic Text Analysis Pipeline Objective Develop an automated semantic text analysis pipeline that processes and analyses textual data extracted from documents. This pipeline enriches text with metadata for deeper insights and enables semantic search capabilities through a user-friendly interface. This stage of the project is for a MVP system should leverage AWS services such as Textract for text extraction, a text categorising stage with a simple to use GUI, all-mpnet-base-v2 for embedding, and Postgres with a vector extension. This job posting is for the MPV stage only, but we must be mindful of the stage two development and facilitate rapid and straightforward scalability in any stage one MPV processes. System Overview The solution encompasses AWS services for storage and processing, a custom interface for metadata enrichment, all-mpnet-base-v2 for generating text embeddings, Postgres and a vector extension for efficient storage and retrieval of vectors, and a custom-built web interface for user interaction. RAG will be implemented with a broad a context as possible to the model across a large document set. Phase 1: MVP Stage 1. Document Storage and Processing Trigger - Tool: Amazon S3. - Process: Upload documents (PDFs initially) to designated S3 buckets, documents will be remained in accordance with a set naming convention and key metadata relating to the document entered into the database for future reference. This triggers the subsequent text extraction process. For test purposes the uploads will be made manually, and at later stages a web scraper will be added that automatically places PDF documents into relevant S3 buckets. 2. Text Extraction - Tool: AWS Textract. - Process: Text is extracted from uploaded PDF documents and temporarily stored in A3 buckets to facilitate further processing. 3. Text Enrichment Developer to advise on best method of adding labels / categories to the text, via an easy to use interface. Labels to be added at a granular level to allow the return of text snippets, providing context to the LLM in formulating it's responses from a broad range of documents without exceeding the token limit. 4. Text Vectorization - Embedding tool: all-mpnet-base-v2 - LLM: Amazon SageMaker (using LLaMA 2). - Process: The text is processed with LLaMA 2 to generate vector embeddings, capturing semantic information for advanced analysis and search functionalities. 5. Vector Storage - Tool: Postgres with a vector extension - Process: Text vectors are stored in the database, allowing for efficient management and retrieval of vectorized data for semantic searches. 6. Front-end Web Application and Search Functionality - Front-end Technology: React.js. - Key Features: - Semantic search input and results display. - email input field for collecting contact information for marketing purposes, forwarding to the client's email address. - Homepage containing descriptive marketing text. - 3 pages total: home page, interaction page, contact page, plus a pop up with GDPR info. Graphics provided as template guidance. - Back-end Technology: Python with FastAPI. Phase 2: Full Automation and Scaling 1. Automated Document Ingestion - Process: A web scraping tool is implemented to automatically identify and upload new documents to the S3 bucket, facilitating a continuous flow of data into the pipeline without manual intervention. 2. Scalable Architecture - Deployment: The application components are containerized using Docker and managed with Kubernetes (Amazon EKS), ensuring the system can scale efficiently to accommodate increased data volumes and user queries. 3. Enhanced Processing Capabilities - Improvements: Integrate additional NLP and ML models for broader and more nuanced text analysis. Consider fine-tuning custom models for specific domain applications. 4. User registration and user management system integration. Please note the attached contract agreement that will be deemed agreed to upon acceptance of the project. Your price given on PPH will be deemed to be your full and final price, and you will be deemed to have fully understood the scope, brief, and specification. To provide context, the project business plan has been uploaded. This is for context only and does not form part of the brief.
21 days ago11 proposalsRemoteopportunity
Local Council Chatbot utilising Llama2 and dataset of PDF docs.
Full stack developer with relevant experience in AWS services and LLM deployment. Description Develop an MVP that provides a chat interface allowing users to query a dataset of local council documents, which will variously include minutes and policy documents. A dataset that contains all information relating to the purpose, policies, news, information, and decision making by that council. The dataset would contain approximately 100 PDF documents, and the chatbot would return meaningful and coherent answers to user prompts, while providing reference links to documents that information in the response is taken from. The client acknowledges the current limitations of LLMs in returning responses from queries across multiple documents, especially given current token limits and processing cost restrictions. A developer is sought that can leverage techniques to embed metadata in the text, allowing techniques such as RAG to extract snippets of data from multiple documents relating to the query and collate them into a response to the user, while adhering to token limits. Objective Develop an automated semantic text analysis pipeline that processes and analyses textual data extracted from documents using Llama2. This pipeline enriches text with metadata for deeper insights and enables semantic search capabilities through a user-friendly interface. This stage of the project is for a MVP system, leveraging AWS services such as Textract for text extraction, a text categorising stage with a simple to use GUI, all-mpnet-base-v2 for embedding, and Postgres with a vector extension. This job posting is for the MPV stage only, but we must be mindful of the stage two development and facilitate rapid and straightforward scalability in any stage one MPV processes. System Overview The solution encompasses AWS services for storage and processing, a custom interface for metadata enrichment, all-mpnet-base-v2 for generating text embeddings, Postgres and a vector extension for efficient storage and retrieval of vectors, and a custom-built web interface for user interaction. RAG will be implemented with a broad a context as possible to the model across a large document set. Phase 1: MVP Stage 1. Document Storage and Processing Trigger Tool: Amazon S3. Process: Upload documents (PDFs initially) to designated S3 buckets, documents will be renamed in accordance with a set naming convention and details of the document entered into the database. This triggers the subsequent text extraction process. For test purposes the uploads will be made manually, and at later stages a web scraper will be added that automatically places PDF documents into relevant S3 buckets. 2. Text Extraction - Tool: AWS Textract. - Process: Text is extracted from uploaded PDF documents and temporarily stored in A3 buckets to facilitate further processing. 3. Text Enrichment Developer to advise on best method of adding labels / categories to the text, via an easy to use interface. Labels to be added at a granular level to allow the return of text snippets from within the chunks of data, but with relevant metadata. The purpose of this is to provide context to the LLM in formulating responses from a broad range of documents without exceeding the token limit. 4. Text Vectorization • Embedding tool: all-mpnet-base-v2 • LLM: Amazon SageMaker (using LLaMA 2). Process: The text is processed with LLaMA 2 to generate vector embeddings, capturing semantic information for advanced analysis and search functionalities. 5. Vector Storage Tool: Postgres with a vector extension Process: Text vectors are stored in the database, allowing for efficient management and retrieval of vectorized data for semantic searches. 6. Front-end Web Application and Search Functionality Front-end Technology: • React.js. Key Features: • Semantic search input and results display. • email input field for collecting contact information for marketing purposes, forwarding to the client's email address. • Homepage containing descriptive marketing text. 3 pages total: home page, interaction page, contact page, plus a pop up with GDPR info. Graphics provided as template guidance. Back-end Technology: • Python with FastAPI. 7. Fine Tuning Allow for fine tuning based on a series of questions and responses to be provided by the client, until such point that coherent responses to queries are achieved. Phase 2: Full Automation and Scaling Beyond the scope of this job. Notes: The developer is to provide guidance and feedback on the capabilities of the technologies and is free to provide their own guidance and suggestions. However, the functionality of the system in providing coherent responses based on text snippets drawn from a large dataset is both the challenge and the absolute requirement. Please only bid with your full and final price. Placeholders will not be accepted. Completion with approximately two weeks. Please respond by explaining how you would handle the text enrichment?
21 days ago17 proposalsRemote