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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

FLIGHTER-AI – AI BASED FLIGHT BOOKING ASSISTANT

P. Vinesh Sri Sai MD. Saud Baig S. Akhil Rajesh R. Sathvik Reddy

Dr. K. S. R. K. Sarma

Dept of CSE (Data Science) Vidya Jyothi Institute of Technology Hyderabad Telangana India
DOI:https://doi.org/10.55041/ijcope.v2i4.938

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

Flight booking applications help users search, compare, and reserve airline tickets efficiently. It is important for such systems to provide accurate, real-time information and a smooth booking experience to meet user expectations. This project focuses on developing an AI-based flight booking application that allows users to search for available flights, compare fares, and complete bookings through a single platform. By using live flight data such as departure time, arrival time, travel duration, and ticket price, the system presents clear and standardized information to users for better decision-making. The application integrates real-time airline data services to fetch up-to-date flight information and uses secure online payment processing to complete reservations. A relational database is used to store booking, passenger, and transaction details reliably. Automated confirmation and ticket delivery improve efficiency and reduce manual effort. The system also supports future enhancements such as personalized recommendations and intelligent fare analysis. The goal of this project is to provide a reliable, scalable, and user-friendly flight booking solution that enhances the overall travel booking experience.

How to Cite this Paper

Sai, P. V. S., Baig, M. S., Rajesh, S. A. & Reddy, R. S. (2026). FLIGHTER-AI – AI Based Flight Booking Assistant. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.938

Sai, P., et al.. "FLIGHTER-AI – AI Based Flight Booking Assistant." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.938.

Sai, P.,MD. Baig,S. Rajesh, and R. Reddy. "FLIGHTER-AI – AI Based Flight Booking Assistant." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.938.

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References

[1] T. M. Mitchell, Machine Learning. New York, USA: McGraw-Hill, 1997.

[2] Vaswani et al., “Attention Is All You Need,” Advances in Neural Information Processing Systems (NeurIPS), 2017.

[3] OpenAI, “GPT Models and Applications,” Available: https://platform.openai.com/docs/

[4] Groq Inc., “Groq LPU and LLaMA Model Documentation,” Available: https://groq.com/

[5] Amadeus for Developers, “Flight Offers Search API,” Available: https://developers.amadeus.com/

[6] Tavily, “AI Search API Documentation,” Available: https://tavily.com/

[7] Stripe, “Stripe Checkout and Webhooks Documentation,” Available: https://stripe.com/docs

[8] FastAPI Documentation, Available: https://fastapi.tiangolo.com/

[9] PostgreSQL Global Development Group, “PostgreSQL Documentation,” Available: https://www.postgresql.org/docs/

[10] React Documentation, Available: https://react.dev/

[11] SQLAlchemy Documentation, Available: https://docs.sqlalchemy.org/

[12] PyJWT Documentation, Available: https://pyjwt.readthedocs.io/

[13] Hugging Face, “Transformers Library Documentation,” Available: https://huggingface.co/docs/transformers

[14] Jurafsky, D. and Martin, J. H., Speech and Language Processing, 3rd ed., Pearson, 2023.

[15] Amatriain, X., “Building Machine Learning Powered Applications,” O’Reilly Media, 2020.

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: May 01 2026
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