Graduate Program Planning Chatbot

@Hrolgar

The 'update via config, no code' line in your acceptance criteria is the part I'd build around first. A YAML or JSON knowledge base file that gets edited every application cycle, with a weighted ranking engine reading straight off it, keeps the dialogue layer and the ranking layer on separate code paths entirely. GPT runs the interview, asks about interests, coursework, location and goals, hands a structured profile to the ranking engine, and the engine scores each program against the config and shows its reasoning next to the recommendation rather than just a ranked list. One thing that'll move the number once scope's locked: whether GPT here means a hosted API key or a local model, since that changes the deployment story for your 'simple web UI, local deployment' requirement, and how many weighted criteria the ranking engine needs to surface in its reasoning. 45000 INR, 7 days, three milestones: M1: knowledge base schema, config file structure, dialogue flow design, 14850 INR, 2 days. M2: GPT interview integration and the weighted ranking engine reading off the config, 15000 INR, 3 days. M3: local web UI, deployment, end to end testing against sample program data, 15150 INR, 2 days. Send me the program data format you're currently working from and I'll have a tighter number back tomorrow.

@OutsourceMan

Hi Valuable Client, CnEL India can build the Graduate Program Planning Chatbot with a focused academic-advising workflow and an easily maintainable knowledge base. Our methodology: • Define the graduate-specific conversation flow, user profiles, and program-selection criteria. • Integrate an LLM to provide natural conversations and ask relevant clarifying questions. • Build a structured, file/API-driven knowledge base for programs, requirements, tuition, locations, research areas, and other relevant data. • Develop transparent matching logic using interests, research fit, location, budget, career goals, and admission competitiveness. • Return shortlisted programs with clear reasoning rather than unexplained recommendations. • Create a simple responsive React/web chat interface. • Keep prompts, scoring parameters, and configurable variables outside the core code where practical. • Test different student profiles to validate conversation quality, program matching, and graduate-level scope. • Provide commented source code, setup instructions, configuration guidance, and sample conversations. We can structure the project so program data can be updated each application cycle without requiring major code changes. Regards, Chanchal CnEL India

@rakhshanz3

With nearly two decades of experience in the realm of AI, your search for a graduate program planning chatbot ends with me. I have honed my skills across academia and industry, providing real-world solutions that enable organizations to leverage AI's transformative power. This includes creating impactful chatbots and voice agents similar to what your project requires, to offer intuitive and context-aware guidance. Drawing on my deep understanding of Natural Language Processing systems, I can make this chatbot truly conversational. Unlike rigid question-answer tree designs, my AI applications employ NLP engines such as OpenAI GPT or Rasa to replicate human-like interaction, giving your users a comfortable and accommodating experience. Furthermore, my expertise in building updatable knowledge bases will ensure that the bot's program recommendations remain accurate and aligned with changing admission cycles. My PhD in Artificial Intelligence uniquely positions me to deliver on your vision for an all-encompassing academic advisor. Having served as a CTO at an AI startup, I amalgamate strategic thinking with technical flair - assuring you of not just the solution itself but also a systematic approach towards tweaking variables and maintaining easy expandability in future upgrades as stated in your acceptance criteria.

@Shrutibimpl

Hello, I can build the intelligent chat interface to help prospective graduate students navigate program selection. My approach involves integrating a popular NLP engine to power a natural conversational flow tailored specifically to graduate-level admissions, research tracks, and career goals. I will build custom selection logic to evaluate criteria like location, tuition, and research interests, backed by an updatable file-driven knowledge base so you can refresh program data annually without changing code. You will receive the commented source code, a React web component, clear local deployment instructions, and a sample conversation transcript demonstrating multi-program recommendations. 1) What format do you prefer for the updatable knowledge base files, such as JSON or CSV? 2) Do you want the chat interface to connect directly to an external LLM API like OpenAI, or use a self-hosted alternative? Thanks, Bharat

@tamannarajput18

Hi! I’m Tamanna. I can build this graduate-program advising chatbot with a clean React interface and an OpenAI-powered NLP layer. I’ll focus the logic specifically on master’s/PhD applicants, including research interests, location, tuition, career goals, thesis options, faculty/research fit, and admission competitiveness. The program database can be updated through a simple config/data file without changing the core code. I’ll deliver: • Natural conversational guidance with clarifying questions • Transparent program shortlisting with reasoning • Reliable source links for program and admission information • Easy-to-edit configuration and knowledge base • One-command local setup and browser deployment • Commented source code, setup guide, and sample conversations I can also structure the project so new programs and application-cycle data can be added easily. I’m happy to discuss the preferred stack and demonstrate the workflow with sample graduate profiles. Best Regards, Tamanna

@shailender18

Hello, I can build this as a graduate-focused AI advising assistant that turns a student’s interests, coursework, location, budget and career goals into transparent, explainable program shortlists rather than generic education advice. With 5+ years of AI integration and full-stack development experience, I can implement a conversational interface using an LLM such as OpenAI GPT with a structured program-selection layer. The bot will ask targeted clarifying questions, evaluate factors such as tuition, location, research fit, thesis/non-thesis options and admission competitiveness, then return a ranked shortlist with clear reasoning. The knowledge base will be file/API-driven so program information, requirements, faculty research and source URLs can be updated each application cycle without modifying application logic. Responses can prioritize official university/department sources and clearly distinguish sourced information from generated guidance. I’ll provide a simple React/web interface, configurable variables, commented source code, local one-command setup, documentation and sample conversations covering different graduate profiles. Relevant AI/advising examples can be shared where applicable; I won’t fabricate demo links or project history. Best Regards, Shailender

@hassam945

Hi, First of all, please see my profile and portfolio projects demonstrating my experience in NLP, LLMs, RAG and AI-powered applications, especially intelligent chatbots. You can see my portfolio project “AI-Tutor” , which teaches students like a real teacher. The main challenge is making this chatbot a focused graduate advisor, not a generic chatbot. I can build a system that understands a student’s interests, background, location, budget and goals, then uses structured program data to shortlist suitable Master’s or PhD programs with clear reasoning. I can implement natural conversation, intelligent clarification, program matching, RAG with trusted academic sources, transparent recommendations, file/API-based knowledge updates, React UI and configurable prompts/rules. I have strong practical experience building LLM, NLP, RAG and knowledge-based AI systems and can share relevant examples. I am very easy to collaborate with we can discuss your requirements, agree on the approach, and build it step by step. You can also first to evaluate my work. I will give 100% to the project I accept, and your satisfaction is always my first priority. Let’s build a graduate-advising assistant students can genuinely rely on.

@bohdan38

Hi there, Program data is scattered across departments and admission criteria vary by program; this can cause stale or mismatched guidance. A config-driven knowledge base plus an NLP matcher and transparent ranking will keep recommendations current and tailored by location, tuition tolerance, and research interests. I built an academic-advisor bot using a modular KB, API-fed program data, and ranking logic that produced three solid program shortlists with reasons. Smart improvement: add a confidence score and live-source links to official pages. Would you like to see a quick rough mockup? Thank you, - Bohdan

@karanp686

I can build a graduate program planning chatbot that efficiently guides users through program options and application steps. With experience in AI-powered chatbot integrations, backend architecture, and custom automation, I’ll deliver a scalable, user-friendly solution tailored to help prospective graduates navigate your offerings smoothly.

@SAMRADDHA2

Hi I have built conversational tools before using GPT based NLP so I can get this feeling like a real advisor rather than a rigid question tree. I'll design the flow around graduate specific context right from the start covering thesis versus non thesis tracks research fit and interdisciplinary paths so it never slips into generic undergraduate advice. For the program matching logic I'll set up a scoring system based on location tuition research interest and admission competitiveness with the reasoning shown transparently to the user. The program data will live in a config or JSON file so you can update it each cycle without touching any code. I'll deliver a simple web interface that runs with one install command a setup guide commented source code and a sample transcript showing at least three different user profiles getting distinct program recommendations.

@Chirag3147

As a full-stack and AI automation developer with 4+ years of experience, I am uniquely equipped to create your Graduate Program Planning Chatbot. I have a proven track record in implementing NLP engines, such as OpenAI GPT or Rasa, into web applications for natural and flowing conversations. By leveraging my expertise in AI systems such as GPT, LLM integrations and RAG-based systems, I can ensure that your chosen stack fits seamlessly into the functionality of your application. One of my key strengths is my ability to design systems that are easily updatable and adaptable. I can build a file-driven or API-fed knowledge base for your chatbot, which will enable you to refresh program data each application cycle without ever having to touch the code. This level of flexibility ensures that the chatbot will always provide users with accurate and relevant information on program selection parameters like location, tuition tolerance, research interests, career outlook, and admission competitiveness. All in all, I believe my holistic skills incorporating AI development, web development, mobile apps development, and AI automation system building make me perfectly suited to undertake this project with you. Choose me for a chatbot that transforms your future graduate students' planning process from mundane to delightful!

@ravikumarsingh1

I can build this as an AI-powered graduate program advisor using a practical, maintainable architecture with an LLM, structured program data, and a simple web/React interface. I can handle: OpenAI GPT-based conversational advisor with graduate-level context Clarifying questions around interests, coursework, location, tuition, career goals, and research direction Transparent program matching/shortlisting with explanations rather than opaque recommendations File/API-driven knowledge base so program information can be updated without changing application code Retrieval from structured program data, official department information, accreditation sources, faculty/research profiles, etc. Config-driven prompts, scoring/matching criteria, and application settings Simple React/web interface with one-command local setup Validation to keep responses focused on master's/PhD admissions and program selection Commented source code, setup guide, and sample conversations covering different student profiles I have experience building AI/RAG systems, OpenAI API integrations, knowledge bases, conversational workflows, Python APIs, and React/web interfaces. I have done this type of AI/RAG work before and can show relevant examples of my current/previous projects if we start talking.

@abhilashr53

I can deliver 'Graduate Program Planning Chatbot' end to end — clean architecture, tests, and deployment. I'll start with a short plan, share progress daily, and hand over production-ready code. Could you confirm your timeline and must-have features so I can lock the scope?

@Web1devloper

As an experienced Data Analyst and Scientist with a specialization in data storytelling, I believe I am the perfect fit for your Graduate Program Planning Chatbot project. My 8+ years in the field have exposed me to and equipped me with high capabilities in Natural Language Processing engines like OpenAI GPT, Rasa, and more. This allows me to transform extensive and intricate datasets into comprehensible and relatable insights, providing the perfect foundation for any intelligent chat interface. I am passionate about leveraging data to clarify, optimize, and enrich operations; something that aligns well with your project's expectations of creating "natural, flowing" dialogues for prospective graduate students. Previous experiences using my skills—for instance integrating APIs as part of ETL processes—have offered me ample understanding on how to develop updatable knowledge bases which would be crucial for your project's smooth running during application cycles. Moreover, I bring with me a unique combination of analytical skills—which include proficient use of tools such as Python, Power BI, Looker, SQL among others— and soft-skills like communication and insights extraction. This would ensure a not only technically sound but also user-friendly end product which successfully addresses your target users' requirements at a granular level while providing comprehensive guidance on program selections based on their interests, geography, future goals and more.

@mmdans

hey, can help. pm me here or discord (mk_142), ill send you my works. cant send here ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

@NEHABHAT92

As an enthusiastic and seasoned web and mobile developer with over 9+ years of professional experience, I have honed my skills in designing effective and user-friendly applications - a crucial aspect for your Graduate Program Planning Chatbot. My expertise lies in understanding the specific needs of users and translating those into intelligent interfaces, making conversations feel natural and engaging. Moreover, having worked extensively on E-commerce platforms, I understand the significance of accurate data and the ability to update it without touching the code. So, your updatable knowledge base feature is well within my grasp. With proficiency in platforms such as OpenAI GPT, Rasa, Java and PHP, I am equipped with the right tools to create a chatbot that satisfies all your prerequisites, including program logic and ranking parameters. Lastly, my commitment to providing top-notch IT services and turning ideas into reality makes me more than just a provider for this project; I'm a partner that will walk you through every step of this project journey ensuring your satisfaction is fully achieved.

@braing2

Hi — the trap with an advising bot is that a raw GPT will happily invent a program, a deadline or a tuition figure with total confidence, and a student acts on it. For advising that's the whole risk. So the core isn't the chat, it's grounding: the bot answers from your program knowledge base and cites the source, and if it lacks the data it says so and points to the official department page instead of guessing. How it'd work: your program data lives in simple files (or an API) — location, tuition, research areas, thesis/non-thesis, entry requirements, competitiveness. The bot holds a natural conversation, pulls the user's interests, coursework, location and goals, then retrieves and ranks matching programs with the reasoning shown. Refresh the files each cycle, no code changes. React front-end, one command to run, config file for model, prompts and ranking weights. Two questions: roughly how many programs in the initial knowledge base, and tied to OpenAI specifically or open to any model (it's a one-line swap)? On proof — instead of a link, send me 5 sample programs and I'll wire a working mini-version and record it advising three different student profiles, before you commit. Same milestone, I'll add the sample transcript you asked for and a "sources" panel so every recommendation shows where the data came from. I do this full time, so I deliver 10x faster and 5x lesser in cost.

@digitaldotsent

Hello, you need a conversational advisor that moves beyond rigid Q and A trees to actually reason about program fit, combining a users research interests, coursework background, location and tuition preferences into a ranked shortlist with transparent justification, while pulling from a knowledge base you can refresh yourself each admissions cycle. I would build this with a RAG pipeline, storing program data, entry requirements and faculty research summaries in a vector store like pgvector on Postgres so you simply update a structured file or feed a new source and the bot reindexes without code changes. GPT would handle the natural dialogue and reasoning layer, orchestrated through a Python backend or n8n workflow for the retrieval, ranking logic and API calls. For the UX I would deliver a simple React chat interface with clear setup instructions, one command local run, plus commented source code and a sample transcript showing at least three distinct profiles getting different ranked recommendations. This would run on my own Hetzner server using Docker and Caddy during development. Could you tell me what format your current program data is in, spreadsheet, PDF or scraped web pages, so I can plan the ingestion step correctly. Syed, Digital Dots

@Lenard007

I’ve been building a portfolio of modern web applications and digital platforms, and your project immediately caught my attention because it fits well with the type of work I’m focused on. I can help turn your idea into a clean, professional, and user-friendly chatbot solution built around what you actually need. I noticed you mentioned the need for a natural, flowing conversation using an NLP engine. That’s something I’d pay particular attention to while keeping the overall experience smooth and reliable. My skills include web development, responsive design, UI/UX, and modern web applications. You can view examples of my work in my portfolio at www.lenard007portfolio.com. I’d be happy to discuss your idea before anything is decided. Send me a message and we can see if I’m the right fit for your project. Regards, Lenard007