Sintérgica Labs: Frontier research from Mexico
Non-profit research lab. We position Mexico and Latin America at the frontier of AI knowledge.
- released models
- 4
- papers & research
- 10+
- academic partners
- 5+
Collectively advancing the science of AI in LATAM
Open Science Initiative
By building an open science community and releasing our models, we are empowering the next era of technological progress in the region.
View on HuggingFaceData Sovereignty
Curation of high-quality datasets with regulatory, cultural, and linguistic context from Mexico and Latin America to train models without WEIRD bias.
Institutional Collaboration
We provide access to infrastructure and models to academic partners and civic institutions for projects driving real-world impact through AI.
Lattice Na’at: toward the global frontier
Sintérgica AI developed the largest AI model in LATAM with 1 trillion parameters. This is the path to the global frontier.
Lattice Na'at 1T
Largest foundational model built in LATAM. 1 trillion (1T) parameters trained on a regulatory, cultural, and linguistic corpus from Mexico and Latin America.
- Active2025
1T
Lattice Na’at
Largest AI model developed in LATAM. Regulatory, cultural, and linguistic knowledge base for Mexico and LATAM. Active production.
- In development2027
1T
Na’at Scale
Advanced MoE architecture
Scaling toward 1 trillion parameters with advanced MoE architecture. Enhanced reasoning and extended context.
- Goal2030
Frontier
Na’at Global
Position a Latin American-origin model at the global frontier of AI knowledge. Regional cognitive sovereignty.
Sintérgica AI implements private AI for regulated sectors in Mexico and Latin America.
Explore Na’at in detailNine frontier research lines
Applied research focused on real AI challenges for non-Anglo-Saxon contexts.
- 01Efficient models
Efficient knowledge distillation
Transfer of capabilities from large models (1T+) to compact models without significant performance loss.
- 02Efficient models
Low-cost fine-tuning (LoRA, QLoRA)
Parameter-efficient fine-tuning methods for adapting base models to specific domains with limited resources.
- 03Data & languages
Dataset curation for MX and LATAM
Building high-quality corpora with regulatory, cultural, and linguistic context from Mexico and Latin America.
- 04Data & languages
NLP for indigenous languages
Models and tools for natural language processing of Nahuatl, Maya, and other indigenous languages of Mexico.
- 05Evaluation
Non-WEIRD benchmarks
Spanish HELM and MMLU-LatAm: model evaluation with metrics that don't assume Western, Educated, Industrialized context.
- 06Evaluation
Cultural bias mitigation
Identification and reduction of WEIRD biases in models trained predominantly on Anglo-Saxon data.
- 07Reasoning
Tensorial logical representations
Encoding of structured knowledge and logical relations in tensorial spaces for explicit reasoning.
- 08Reasoning
Efficient recursive reasoning
Architectures and strategies for multi-step reasoning with computational efficiency at inference time.
- 09Reasoning
SLMs for agentic systems
Specialized small models as components of multi-agent systems with verifiable governance.
Publications and Models
WEIRD bias mitigation in LLMs
Coming soon
MMLU-LatAm: Evaluating regional context
Coming soon
Lattice Séeb 9B
2025
Join the research
Sintérgica Labs is an open project. We seek collaborators who want to build the future of AI from Latin America.
Researchers
Access & publication
- Early access to models and datasets
- Co-authorship in publications
- Shared compute infrastructure
- LATAM researcher network
Universities
Partnerships & projects
- Formal collaboration agreements
- Thesis and graduate projects
- Joint workshops and seminars
- Research grants
Developers
Open source & APIs
- Contribute to open source models
- Research APIs (early access)
- Bounties for technical improvements
- Technical mentorship
Organizations
Funding & data
- Contribution of specialized data
- Funding of research lines
- Real use cases as benchmarks
- Recognition in publications
Access Labs' work
All our open work lives on GitHub and HuggingFace.
