amawta
Applied R&D Partner · Chile
amawta

Applied GenAI R&D for sensitive operations.

Useful, measurable, auditable, and safe internal systems

Amawta turns generative AI into useful, measurable, auditable, and safe internal systems, from internal knowledge to critical business operations.

EvaluateValue and risk
GovernControls
ImplementWorkflows
Architecture

Amawta is an Applied GenAI R&D Lab.

We use scientific research as the engine for technical judgment, applied R&D as the commercial interface, and operational governance as the framework for safe adoption.

Applied GenAI R&D
Organizations

We turn generative AI into governable internal systems.

We work with teams that need to move models into real processes: define use cases, measure impact, integrate workflows, and reduce operational risk.

  • AI adoption diagnostics
  • Internal copilots
  • RAG and document intelligence
  • Process automation
  • Output evaluation
  • LLM red teaming
  • Operational AI governance
Amawta Research
Research

We research evidence-based, verifiable AI workflows.

Scientific research remains visible and protected. It keeps us focused on evaluation, falsification, traceability, and systems that can support technical decisions.

  • Scientific workflow automation
  • Model evaluation and falsification
  • Technical AI governance
  • Computational complexity
  • Auditable systems
  • AI for scientific discovery
Operating model

Research does not sit outside the applied offer. It informs better diagnostics, better tests, and stronger technical decisions.

Research

Engine for technical authority, judgment, and differentiation.

Applied R&D

Commercial interface for turning hypotheses into prototypes and workflows.

Governance

Framework for operating AI with controlled risk, traceability, and human approval.

What we do

From available models to reliable internal systems

Companies already have access to models. The difference is choosing real use cases, measuring results, governing risks, and integrating workflows that teams can sustain.

01

AI adoption diagnostics

We identify real opportunities, data constraints, risks, and cases where AI can create measurable value.

02

Operational governance

We design policies, controls, risk matrices, traceability, and human approval criteria.

03

Internal copilots and RAG

We build assistants over documents, processes, and internal knowledge with permissions, sources, and evaluation.

04

LLM red team

We test prompt injection, data leakage, tool abuse, RAG poisoning, and automation failures.

05

AI automation

We integrate models into real workflows with metrics, logs, evaluation, and human fallback.

For security, risk, and digital transformation partners

Amawta can operate as an expert applied generative AI R&D unit.

The partner keeps the commercial relationship and trust. Amawta contributes technical evaluation, architecture, prototyping, red teaming, and operational AI governance.

Packages

Four clear ways to start

Not every case needs a full implementation on day one. We package the work to evaluate, govern, security-test, or build a measurable prototype.

01

AI Readiness Assessment

Initial diagnostic to decide whether an organization is ready to use generative AI in a specific process.

Outputs
  • Use-case map
  • Data and risk constraints
  • Impact-effort prioritization
02

AI Governance Sprint

Design of rules, controls, and evidence for adopting generative AI with operational responsibility.

Outputs
  • Usage policy
  • AI risk matrix
  • Human approval criteria
03

LLM/RAG Red Team

Security and failure testing for copilots, RAG systems, agents, and model-driven automations.

Outputs
  • Prioritized findings
  • Technical reproduction
  • Recommended controls
04

Applied AI Prototype

Measurable prototype to validate utility, adoption, and risk before scaling into operation.

Outputs
  • Functional workflow
  • Success metrics
  • Implementation plan

Each package ends with actionable evidence: what works, what does not, what risk remains, and the next reasonable step.

Methodology

Applied R&D for controlled adoption

We combine scientific AI research, experimental evaluation, and technical implementation to turn generative AI into traceable internal workflows.

01

Evaluate

We define the problem, available data, risks, and utility metric before building.

02

Govern

We design controls, usage limits, owners, and approval criteria.

03

Prototype

We build measurable tests with users, sources, metrics, and expected failures.

04

Implement

We integrate workflows that internal teams can use, audit, measure, and maintain.

Methodology

Our work must be measurable and falsifiable

We test each solution against objectives, risks, available data, and failure cases. When a test fails, we refine, narrow, or discard it.

4Stages
LogsTraceability
HumanApproval
Work

Technology, demos, and applied cases

Experimental products show technical capability, but the core offer is Amawta as an expert applied generative AI R&D unit.

01

Applied R&D

Diagnostics, prototypes, and generative AI workflows for real internal processes.

02

Governance and security

Controls, traceability, LLM red team, and criteria for safe adoption.

03

Eigen Suite

EigenDB, EigenKV, and EigenWeights as technical evidence of proprietary applied research.

We separate products, benchmarks, demos, and cases so research does not compete with the commercial offer.

Get in touch

Contact

Do you have a generative AI use case that needs evaluation, governance, or implementation?

LocationSantiago, Chile

From Santiago, Chile, we work as an external applied GenAI R&D partner. We combine scientific research, experimental evaluation, and technical implementation with internal teams.

🇨🇱Applied GenAI R&D Lab