Frontier research in Artificial Intelligence from Mexico
We are the non-profit research division of Sintérgica AI, a Mexican deeptech laboratory. We conduct fundamental and applied research in Artificial Intelligence and Data Science, with technology transfer to the productive sector and standing collaboration between academia, industry and government.
- Founded
- 2024
- Headquarters
- Boca del Río, Veracruz
- Active lines
- 7
- Ongoing projects
- 8
A place to generate knowledge and transfer it
The Laboratory is dedicated to generating scientific knowledge, technological development and innovation through frontier research in Artificial Intelligence, Data Science and related disciplines.
Sintérgica Labs is the non-profit research division of Sintérgica AI, a Mexican deeptech laboratory dedicated to developing artificial intelligence models (the Na'at and Séeb families), the Lattice ecosystem and private, secure AI solutions for companies and governments.
We carry out fundamental and applied research in Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Evolutionary Computation, Intelligent Systems, Optimization and Collective Intelligence. As a cross-cutting axis we work on AI alignment, ethics, governance and constitutionality, to create transparent, explainable, safe and socially responsible models.
Beyond scientific research, the laboratory promotes technology transfer, the development of highly specialized talent, national and international collaborations and participation in high-impact projects that strengthen the country's scientific and technological ecosystem.
General objective
To conduct scientific research and technological development in Artificial Intelligence and related areas through a responsible innovation approach, grounded in principles of ethics, governance and social responsibility, generating knowledge, methodologies and applications that contribute to the advancement of science, innovation and the solution of real problems.
Mission
To generate scientific knowledge and develop high-impact technological solutions through applied and frontier research in Artificial Intelligence, data science and related disciplines, promoting innovation, interdisciplinary collaboration and the training of human capital to address scientific, industrial and social challenges.
Vision
To be a research laboratory recognized nationally and internationally for the excellence of its scientific contributions, technology transfer, researcher training and the development of innovative solutions in Artificial Intelligence, establishing itself as a reference in linking academia, industry and government.
Seven fronts of work
From the laboratory to publication, to transfer and to the classroom.
01
Research
- Develop original research in AI, Machine Learning, NLP, Philosophy and Ethics of AI, Computer Vision, Evolutionary Computation and related areas.
- Publish results in high-impact scientific journals and conferences.
- Foster interdisciplinary research with other areas of knowledge.
02
Governance and responsible development
- Design, develop and evaluate AI models and systems according to the laboratory's framework of ethics, governance and constitutional principles.
- Define methodologies for transparency, traceability, explainability, safety and accountability.
- Establish evaluation, audit and continuous improvement processes across the entire model life cycle.
- Promote national and international good practices in AI governance.
03
Technological development
- Develop prototypes suitable for transfer to the productive sector.
- Design AI algorithms, models and systems with practical applications.
- Promote the generation of intellectual property and specialized software.
04
Talent development
- Train researchers through research projects, theses and residencies.
- Train professionals in emerging AI-related technologies.
- Support the development of young researchers.
05
Partnerships
- Establish collaborations with universities, research centers, companies and government bodies.
- Take part in national and international research and innovation projects.
06
Outreach
- Share progress through conferences, workshops, seminars and outreach publications.
- Organize academic events in industry and government settings.
- Bring AI and Data Science closer to society.
07
Innovation
- Identify technology transfer opportunities.
- Drive the creation of solutions with economic and social impact.
- Promote science and technology based entrepreneurship.
Seven active lines
Fundamental and applied research, taking the context of Mexico and Latin America as the starting point.
| No. | Research line | Category |
|---|---|---|
| 01 | AI alignment, governance and constitutionalityMethodologies to ensure that AI models and systems operate ethically, transparently, safely and aligned with constitutional principles, regulatory frameworks and human values. | Governance |
| 02 | NLP for native languages of MexicoNatural Language Processing models and resources for the preservation, analysis and generation of text in Mexico's indigenous languages, promoting their inclusion in AI technologies. | Data and languages |
| 03 | Data curation for Mexico and Latin AmericaMethodologies for collecting, cleaning, annotating and validating datasets representative of the region, toward more accurate, inclusive and contextualized AI models. | Data and languages |
| 04 | Explainability of neural networks in NLP tasksMethods to interpret, analyze and explain the decisions of neural networks applied to NLP, strengthening their transparency, reliability and comprehension. | Explainability |
| 05 | Efficient knowledge distillation from language modelsTechniques to transfer knowledge from complex models to smaller, more efficient ones, preserving performance and reducing computational requirements. | Efficient models |
| 06 | Fine-tuning language models with few resourcesStrategies to adapt pre-trained models to specific tasks with limited amounts of data and compute, maintaining high performance and efficiency. | Efficient models |
| 07 | Neural network performance through evolutionary computationEvolutionary Computation methods to optimize architectures, hyperparameters and training processes of neural networks in NLP tasks. | Optimization |
Eight ongoing research projects
Active work of the laboratory as of the date of the institutional curriculum.
- 01
Training language models with data from Mexico.
- 02
Data extraction from large-scale language models.
- 03
Classifiers and traditional machine learning for question-answering systems.
- 04
Retrieval-augmented information systems for Mexican logistics laws and regulations.
- 05
Efficient stigmergic swarms: using digital ants to make local models more efficient.
- 06
The problem of human dependence on language models and anthropomorphism.
- 07
The problem of the concept of learning: applying new definitions of learning in Machine Learning.
- 08
What is similarity? Applying new definitions of similarity to language models and NLP systems.
Who does the research
The laboratory team and their roles.
| Name | Role |
|---|---|
| MCD. Axel Javier Jara Mújica | President · Data Scientist |
| MIA. José Clemente Hernández Hernández | Director and Research Lead |
| Luis Feliciano Bautista Romero | Data Scientist |
| Alejandra Cano | Data Curation |
| Axel Jesús López Flores | Data Curation |
Publications and talent development
Scientific results and people training inside the laboratory.
Scientific output
2026
Using Classifiers for Question-Answering: a Mexican Dataset Case Study
Bautista-Romero, Luis-Feliciano; Hernández-Hernández, José-Clemente
Proceedings of the XVIII Mexican Congress on Artificial Intelligence (COMIA), Cuernavaca, Morelos
To be published in Communications in Computer and Information Science, Springer
Professional internships
Luis Feliciano Bautista Romero
Tecnológico Nacional de México, Campus Veracruz
Edson Martínez Hernández
Tecnológico Nacional de México, Campus Veracruz
Where we have been
The laboratory's participation in academic, government and industry settings.
| Date | Activity | Institution |
|---|---|---|
| 9 Oct 2025 | Workshop lead Student Colloquium«Ethics in science: uses and limits of AI» | Instituto de Ecología, A.C. (INECOL) · SECIHTI |
| 21 Nov 2025 | Organizer First Veracruz AI SummitSintérgica Labs as organizing institution | Sintérgica Labs |
| 18 Feb 2026 | Speaker Inventors' Day«The Journey of an AI: from Research to Market». Veracruz Innovations That Transform | COVEICYDET · Veracruz Ministry of Education (SEV) |
| 26–27 Mar 2026 | Workshop lead Academic Bodies Meeting«Applying AI to higher education» | Tecnológico Nacional de México · SEP · SEV |
| 29 Apr 2026 | Speaker Applied AI for Institutional Communication | Organismo Público Local Electoral (OPLE) Veracruz |
Two ways to take part
One for those who wish to join the research. One for the institutions and organizations that wish to support it.
Laboratory repositories
The code and models we release live on GitHub and HuggingFace.
Partnerships and joint initiatives
The laboratory seeks strategic partnerships and joint initiatives in research, technological development and innovation.
Universities and research centers
Agreements and projects
- Formal research collaborations
- Thesis projects and residencies
- Joint workshops and seminars
- Interdisciplinary research
Government bodies
Governance and training
- Good practices in AI governance
- Academic events in public settings
- Applied research projects
- Technical staff training
Companies
Technology transfer
- Prototypes transferable to the productive sector
- Intellectual property and specialized software
- Real problems as case studies
- Science based entrepreneurship
Funding bodies
High-impact projects
- Funding for research lines
- National and international projects
- Indicators and evidence of track record
- Scientific, technological and social impact
Contact
MIA. José Clemente Hernández Hernández
Director and Research Lead
- clemente.hernandez@sintergica.ai
- +52 228 139 2643
- Boca del Río, Veracruz
Contact the laboratory
State the reason for your interest and the institution you represent. The laboratory's director replies directly.