LEANGOOGS AI

Building the Data Infrastructurefor the Global South.

We help organisations build, evaluate and improve AI using high-quality human data.Global South human intelligence at scale.Collection, annotation, evaluation and quality assurance across banking, healthcare, technology, education and research. Language is one of our greatest strengths; our capability goes well beyond it.

DataHuman IntelligenceAI Evaluation
What we do

Data services for AI, end to end.

Collection through to evaluation, delivered by trained people and checked by a quality process rather than assumed to be right.

Data Collection

Structured, human-generated data gathered to your specification across formats, languages and specialist domains.

  • Text and document data
  • Audio and speech data
  • Image and video data
  • Survey and human-response data
  • Conversational data
  • Multilingual data
  • and 2 more

Annotation & Labelling

Datasets prepared for machine learning, annotated against a written specification and measured for consistency.

  • Text annotation
  • Image annotation
  • Video annotation
  • Audio annotation
  • Document annotation
  • Classification
  • and 5 more

AI Evaluation

Model outputs assessed by people against stated criteria, with the reasoning recorded rather than a bare score.

  • AI output evaluation
  • Human preference evaluation
  • Response quality assessment
  • Accuracy and relevance evaluation
  • Safety evaluation
  • Translation evaluation
  • and 3 more

Quality Assurance

Multi-stage human review designed to find errors rather than confirm that work was done.

  • Data validation
  • Quality checks
  • Human review
  • Error identification
  • Data cleaning
  • Double annotation
  • and 2 more

Language & Multilingual Data

Collection, translation, transcription, annotation and evaluation across languages that conventional pipelines reach poorly.

  • Translation and localisation
  • Transcription
  • Speech and voice data
  • Dialect and regional variation
  • Low-resource language collection
  • Code-switched and mixed-language data
  • and 1 more

Domain Expertise

Projects matched to people who understand the subject matter behind the data, not only the annotation task.

  • Clinical and health content
  • Legal and regulatory content
  • Financial and commercial content
  • Agricultural content
  • Educational content
  • Government and public service content
  • and 1 more

Custom Data Projects

Tell us the requirement. We design the collection, annotation, evaluation and quality-control workflow around it.

  • Bespoke workflow design
  • Multi-stage pipelines
  • Mixed data types
  • Ongoing data production
  • Dedicated project teams
Where to start

What do you need?

The problem

AI doesn't fail everywhere in the same way.

The same system can be reliable in one market and quietly wrong in another. Performance shifts with language, culture, geography, profession and the conditions people actually use it in.

Generic datasets and evaluation methods cannot always capture those differences.

Evaluation runstreaming

Prompt · identical across all three

My transfer failed but my account was debited. What should I do?

English0.00

Nigerian Pidgin0.00

Omits the dispute path and the reference number the customer needs.

Yoruba0.00

Materially incomplete. Misses reversal window, reference and dispute process.

Illustrative of a failure pattern we measure, not a published benchmark result.

Performance shifts along every one of these

That's where we come in.

We connect AI builders with the people, knowledge, data and evaluation capabilities required to understand how AI performs in real-world markets.

Where we work

Built for the contexts global AI cannot afford to overlook.

The Global South is not one market. It is thousands of languages, communities, industries, environments and cultural contexts — and every one of them enters the same controlled pipeline.

Markets

  1. 01Collect
  2. 02Structure
  3. 03Evaluatea share rejected at review
  4. 04Deliverproduction-ready

Hover a market to trace its path through the system.

The world's AI systems increasingly operate in markets whose languages, cultures and real-world contexts have historically received less representation in AI infrastructure. LeanGoogs builds the local intelligence needed to evaluate and improve AI within those contexts.

Explore the Global South
Our global network

Global reach. Local expertise.

Our network connects trained professionals, language contributors, annotators and domain experts across 22+ countries, so projects can be resourced close to the people and languages they concern.

These are the countries our contributors live and work in, not offices we operate. That distinction matters: it is what lets us recruit for local context, dialect and domain knowledge that a remote team cannot supply.

Africa

15 countries

NigeriaKenyaTanzaniaEthiopiaRwandaZambiaGhanaMalawiBeninCameroonDjiboutiEgyptMoroccoUgandaSouth Africaand more

Asia & Middle East

5 countries

IndiaPakistanSaudi ArabiaBangladeshPhilippinesand more

Europe & Eurasia

2 countries

UkraineRussiaand more

Not only language speakers.

Our community brings professional judgement to the data, which is what separates a usable clinical or financial dataset from a literal one. A medical record annotated by someone who has read records before is a different artefact.

PhD holdersAcademic researchersDoctors and cliniciansEngineersAccountantsLegal professionalsScientistsManagersEducators and lecturersLinguistsAgronomistsTechnology professionals
The network

People are part of the infrastructure.

A verified network of local contributors and subject-matter experts, structured by language, professional background and demonstrated capability — not a generic freelancer pool.

Matchingrouting

Incoming task

Evaluate a clinical assistant in Yoruba

Language

Yoruba
Hausa
Igbo
Swahili
Pidgin

Expertise

Healthcare
Finance
Law
Agriculture
Education

Capability

Evaluation
Annotation
Red teaming
Transcription
Expert review

Matched to a qualified contributor: Yoruba · Healthcare · Evaluation

YorubaHausaIgboNigerian EnglishNigerian PidginSwahiliAmharicFrenchArabicPortugueseand growing
How it works

From definition to delivery.

Every engagement runs the same controlled path, so you know what happens to your work at each stage.

01

Define

Tell us what your AI system needs — the languages, markets, expertise and the standard it has to meet.

02

Match

We identify the right languages, locations, skills and subject-matter expertise for the work.

03

Execute

Qualified contributors and experts complete the work through controlled workflows.

04

Validate

Our quality systems and reviewers evaluate the outputs before anything reaches you.

05

Deliver

You receive production-ready data, evaluation results or intelligence.

Why LeanGoogs

Quality isn't a feature. It's the system.

The difference between usable data and expensive noise is the process around the people producing it.

Local depth

We build networks within markets rather than treating entire regions as anonymous data sources.

Verified expertise

Contributors are matched according to language, professional background, skills and demonstrated performance.

Quality by design

Our workflows are built around qualification, review, gold standards and continuous measurement.

Built for AI

We don’t simply provide labour. We build data and evaluation systems designed around AI development.

The quality system

Four layers, running continuously.

Security and trust
01

Qualification

Contributors are assessed for language, professional background and demonstrated skill before they are eligible for work.

02

Gold standards

Known-answer items are seeded through live work so quality is measured continuously, not sampled at the end.

03

Review

Independent reviewers check output against the brief, with escalation paths for disagreement.

04

Measurement

Agreement, accuracy and consistency are tracked over time and fed back into who is matched to what.

Why LeanGoogs

Built for quality. Designed for scale.

We prioritise quality over quantity. Every project is structured around accuracy, consistency and the specific requirements of the client.

01

Quality first

We prioritise accuracy, consistency and reliability over volume. A large dataset built on inconsistent judgement cannot be corrected in a single pass; a smaller uniform one can be extended.

02

Built for scale

Our trained contributor and professional network lets projects grow to the size a client requires, without recruiting from scratch each time.

03

Fast delivery

Structured workflows move a project from requirements to production and quality assurance without a long discovery phase for every engagement.

04

Human expertise

Our network includes professionals across industries and disciplines, so a project can be matched to people who understand the subject matter, not only the annotation task.

05

Global South expertise

Strength in underserved languages and markets gives access to human data that conventional pipelines reach poorly or not at all.

06

End-to-end workflow

Collection, annotation, validation, quality assurance, evaluation and delivery run as one process, so responsibility for the final dataset does not fall between vendors.

How a project runs

CollectionAnnotationValidationQuality assuranceEvaluationDelivery

One process, one accountable team. Where collection and review sit with different vendors, the errors that matter most are the ones nobody owns.

For AI teams

One partner for the human side of AI development.

Instead of assembling four vendors and reconciling four standards of quality, the data, the experts and the evaluation come from one system.

  • Data collection
  • Data annotation
  • Expert data
  • Multilingual data
  • Human preference data
  • Model evaluation
  • Red teaming
  • Domain experts
  • Local-market evaluation
  • Continuous evaluation

Ready to build AI that works in more places?

Tell us the markets, languages and systems involved, and we will scope the data, expertise or evaluation the work needs.