Sintérgica AI
Back the research

The AI that understands our context is being built here.

Sintérgica Labs researches how to make Artificial Intelligence process our languages, operate within our regulatory framework and train the next generation of researchers. The results are public. Your organization can be part of that work.

Since
2024
Active lines
7
Ongoing projects
8
Status
Non-profit
Context

The models now deciding about us were trained in another context

The consequences show up in the processes where those models already operate.

01

A model trained in another language and under another legal system does not recognize the structure of a CFDI, cannot distinguish Mexican case law from an opinion piece and does not identify an indigenous language as a language. When that model intervenes in a procedure, a contract or a case file, its blind spots transfer to the institution using it.

02

Sintérgica Labs was established in 2024 in Boca del Río, Veracruz, to address that problem through applied research. It maintains seven active lines simultaneously: explainability of a model's decisions, curation of datasets representative of the region and processing of Mexico's indigenous languages, among others.

03

The laboratory is the non-profit division of Sintérgica AI. That relationship provides access to infrastructure and to real industry problems, while research results are published, presented at conferences and taken to universities and government settings. The aim is not a product: it is the methodological foundation on which others can build.

Where resources go

What each contribution makes possible

Four destinations, all tied to the laboratory's institutional objectives.

Bringing languages into technology

Every advance in processing Mexico's indigenous languages narrows the representation gap in the AI systems now being built.

Talent development without displacement

Residencies and theses for researchers in training who today would access frontier research only outside the state or the country.

Regulatory context as the model's foundation

Curating data from Mexico and Latin America is specialized work and marks the difference between a model that understands context and one that infers it.

Dissemination of results

Publication, conference participation and workshops. The knowledge generated fulfils its purpose when it travels beyond the laboratory.

Institutional commitment

Accountability for every contribution

Every contribution is assigned, documented and reported.

Progress report

A report on the progress of the line supported, with concrete results rather than general indicators.

Recognition

Mention of the person or organization as a backer in the materials and publications of the corresponding line, where preferred.

Early access

Results from the line supported are shared prior to publication.

Participation in activities

An invitation to the seminars, workshops and academic events organized by the laboratory.

Modalities

Forms of contribution

Four modalities, all with direct impact on the research.

01

Financial contribution

One-off or recurring, from a person or an organization. The destination is agreed jointly and the corresponding progress is reported.

02

Compute and infrastructure

Cloud credits, GPU access or hardware. This is the modality with the greatest effect on the laboratory's experimental work.

03

Data

Corpora, archives or document collections suitable for curation and use in research, under the terms of use established.

04

Institutional agreement

Universities, agencies and foundations wishing to support a complete line or a joint project.

The modality, the destination of the resources and the documentation your organization requires are agreed beforehand.

Institutional contact

Share your details and the laboratory's director will be in touch to agree the modality.

Your data is used solely to follow up on your contribution.