About Travelyqor

Intelligence,engineeredwith purpose.

An applied AI engineering company: we build knowledge assistants, workflow automation, and the evaluation and deployment around them.

Why the companywas started.

AI prototypes can demonstrate possibility in a few days. Turning that possibility into a dependable product requires software, data, evaluation, security, and operations to work together.

Travelyqor AI Systems closes that gap by designing the complete production system around a meaningful operational problem.

What we believe

Engineering principlesfor responsibleproduction AI.

  1. 01

    Solve the right problem

    Begin with user value, operating context, and measurable outcomes.

  2. 02

    Build for production

    Architecture, security, operations, and adoption are part of the product.

  3. 03

    Measure AI quality

    Use evaluation datasets, traces, feedback, and clear acceptance criteria.

  4. 04

    Design for failure

    Make uncertainty, limits, escalation, and recovery explicit.

Client data

How we handle client data.

AI projects often touch sensitive information. These are the boundaries every engagement starts from; the specific terms are part of each written agreement.

  1. 01

    Before an agreement

    Enquiries need only a nonconfidential summary. Please do not send credentials, personal data, or proprietary documents until scope and terms are agreed.

  2. 02

    Agreed in writing

    Which data a system may use, where it is processed, and its security boundaries are agreed during design, before any build starts.

  3. 03

    Least access

    Integrations are limited to the permissions each step needs, and knowledge assistants enforce what each user is allowed to retrieve.

  4. 04

    Where your data may live

    Cloud, private-cloud, or fully local deployment, chosen around what your data is allowed to leave.

  5. 05

    Traceable actions

    Automated workflows keep a log of every action they take, so decisions can be reviewed afterwards.

Leadership

The peoplebehind the company.

Dr. Anuja Prasad S leads applied AI and ML engineering. Dr. Felix M. Philip, a director of the company, is an Associate Professor whose research covers IoT, image processing, and intelligent sensing. Experience listed under each profile was gained at the organisations named, not as Travelyqor client work.

Dr. Anuja Prasad S, co-owner of Travelyqor AI Systems
Co-owner & AI/ML Engineering Leader

Dr. Anuja Prasad S

Generative AI, computer vision, MLOps, cloud platforms, and intelligent automation

Dr. Anuja Prasad S has 10 years of hands-on Python and AI/ML engineering and 12 years of university teaching. Her recent work covers LLM applications and RAG pipelines, computer vision, security automation, and cloud ML deployment. Her PhD research was on automatic road-traffic analysis with machine learning.

Changanacherry, Kerala, India

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Core expertise

  • LLM applications, RAG pipelines, and model fine-tuning (LoRA, QLoRA, quantization)
  • Vector search: Pinecone, Weaviate, pgvector, FAISS
  • Computer vision: detection, classification, and segmentation
  • MLOps on AWS, Azure, and GCP with Docker, Kubernetes, MLflow, and Databricks
  • Security automation with Cortex XSOAR, SIEM, and SOAR
  • Full-stack delivery with Django, REST APIs, and React

Professional experience

Oct 2025 - Present

Data Scientist

Algoworks

  • Builds and deploys LLM applications and RAG pipelines, and optimises inference cost with LoRA, QLoRA, and quantization.
  • Develops MLOps pipelines across AWS, Azure, and GCP, and Cortex XSOAR playbooks for security-incident automation.
Jun 2025 - Sep 2025

Senior AI Developer

Appletechsoft

  • Fine-tuned BLIP, SigLIP, and CLIP models on fashion data and built image-to-text and text-to-image pipelines.
  • Built Pinecone and FAISS similarity search for recommendations, with MLflow experiment tracking.
Aug 2023 - Apr 2025

Computer Vision Engineer

Energyscape Renewables

  • Developed computer-vision systems for automatic rooftop solar-panel placement, deployed on Azure Databricks.
  • Built Django applications and Databricks ETL pipelines for solar-installation data.
Mar 2022 - Jul 2023

Senior Machine Learning Engineer

Aunva Labs

  • Deployed threat-detection and anomaly-detection models within Cortex XSOAR and Azure SIEM/SOAR workflows.
Sep 2018 - Jan 2021

Project Fellow, AI-based Traffic Analysis

Rajiv Gandhi Institute of Technology

  • Led a research team building real-time vehicle detection, classification, and licence-plate identification.
2005 - 2017

Lecturer, Assistant Professor, and Head of ECE

Engineering colleges in Kerala, including GISAT

Selected projects

Automatic rooftop solar-panel placement

At Energyscape Renewables

Rooftop segmentation with computer vision and visual transformers, delivered through a Django web application.

Cybersecurity threat detection

At Aunva Labs

Malware and phishing detection models integrated with SIEM and SOAR platforms, including Cortex XSOAR and Microsoft Azure.

Vehicle detection and classification from traffic video and audio

Doctoral research, Rajiv Gandhi Institute of Technology

Deep neural networks combining audio and visual cues for traffic data collection.

Education

2025

PhD in Artificial Intelligence

A P J Abdul Kalam Technological University

2012

ME in Applied Electronics

Noorul Islam

BTech in Electronics and Communication Engineering

Cochin University

Publications

  1. Anuja Prasad S, Leena Mary, and Bino I. Khoshy. Detection and Classification of Vehicles Using Audio Visual Cues. Multimedia Tools and Applications.
  2. Anuja Prasad S, Leena Mary, and David Solomon George. Classification of Vehicles in Heterogeneous Traffic Video Collected from a Moving Vehicle. Communication in Information and Software Technology.
  3. Anuja Prasad S and Leena Mary. A Comparative Study of Different Features for Vehicle Classification. 2019 IEEE International Conference on Computational Intelligence in Data Science (ICCIDS), Chennai, India, pp. 1-5.
  4. Joseph Jissy, Anuja Prasad S, and Leena Mary. A Study on Localization Techniques for Automatic License Plate Recognition Systems. 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Vol. 1, pp. 1090-1099.
Dr. Felix M. Philip, director of Travelyqor AI Systems
Director · Associate Professor & Researcher

Dr. Felix M. Philip

Internet of Things, Image Processing, Smart Systems, Precision Agriculture, and Arctic Ocean Monitoring

Dr. Felix M. Philip is an Associate Professor with research and academic experience in Internet of Things (IoT), image processing, embedded systems, and intelligent sensing technologies. His work focuses on developing technology-driven solutions for precision agriculture, environmental monitoring, marine and Arctic applications, and automated image-based analysis. His research interests include IoT-enabled sensing, underwater imaging, automated biological monitoring, deep learning-based image classification, and interdisciplinary technology applications.

Kochi, Kerala, India

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Core expertise

  • Internet of Things (IoT) and IoT-enabled sensing
  • Image processing and deep learning-based image classification
  • Embedded systems and intelligent sensing technologies
  • Smart systems and precision agriculture
  • Environmental, marine, and Arctic Ocean monitoring
  • Underwater imaging and automated biological monitoring
  • Interdisciplinary technology applications

Professional experience

Associate Professor & Researcher

JAIN (Deemed-to-be University), Kochi, Kerala, India

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