TECHNOLOGIES · AWS · ADVANCED PARTNER

BlueMetrics + Amazon Web Services

BlueMetrics is an AWS Advanced Partner. Our default Applied AI infrastructure is AWS-first: Bedrock, SageMaker, Textract, Glue, S3, and QuickSight, with more than 200 projects delivered and over 10 active certification types on the team.

AWS Advanced Tier Services Partner

Advanced Tier Services Partner

POSITIONING · AWS-FIRST WITH FLEXIBILITY

AWS is our technical default.

The default infrastructure is AWS, and that is where the team's depth shows. When a client runs multi-cloud, requires Azure or GCP by corporate contract, or has a hybrid stack with on-premises, we evaluate the case and adjust scope with the same governance discipline. The delivery standard does not change: White Box AI, client-owned code, MLOps, and provider-independent governance.

TECHNICAL COMPETENCY AREAS

Four areas where the team has proven depth.

genai

Generative AI

LLM applications in production, anchored in client data, with governance and White Box AI from day one.

Amazon BedrockTextractRekognitionQ in Connect

data

Data Engineering

Pipelines, lakehouse and governance in regulated environments. Focus on auditability and predictable cost.

GlueS3RedshiftAthenaLake Formation

ml

Machine Learning

Predictive and detection models in production, with MLOps and continuous drift monitoring.

SageMakerComprehendForecast

bi

Analytics and BI

Corporate dashboards with QuickSight and embedded BI with Sisense when delivery goes inside the client product.

QuickSightAthenaSisense embedded

AWS STACK MASTERED

The coverage, in chips. What goes into a real project.

GenAI

Bedrock Textract Rekognition Comprehend Q in Connect

Data

S3 Glue Redshift Athena Lake Formation

Machine Learning

SageMaker Forecast

App & Infra

Lambda Step Functions API Gateway Cognito QuickSight CloudWatch

CERTIFICATIONS WALL

Over 10 active AWS certification types on the team.

The depth that backs "Advanced Partner" at the human level. Continuous renewal is part of the operation.

AWS Cloud Practitioner

Cloud Practitioner

AWS AI Practitioner

AI Practitioner

AWS Solutions Architect Associate

Solutions Architect Associate

AWS Developer Associate

Developer Associate

AWS Data Engineer Associate

Data Engineer Associate

AWS ML Engineer Associate

ML Engineer Associate

AWS ML Specialty

ML Specialty

AWS GenAI Developer Professional

GenAI Developer Professional

PRODUCTION CASES ON AWS

Four proofs in production.

Results audited by clients on AWS. Each card shows the metric, the core service behind the delivery, and the sector.

FOURBANK

GenAI

document validation

Document validation with Bedrock + Textract in production. Multimodal pipeline on AWS, in the client's account.

Bedrock · Textract Read case →

DIRECIONAL

−46%

default rate

Risk model in SageMaker, AWS-first, with the real estate developer's internal data. From hypothesis to go-live in short waves.

SageMaker

FRAUDE PIX

confidential
R$ 1,5M

avoided · detection <1s

Real-time anti-fraud for a regulated fintech. SageMaker + Lambda, client-owned code, MLOps running. Confidential case.

SageMaker · Lambda

LOBBY CRE

BI

embedded in SaaS

White-label BI embedded in a real estate SaaS platform. Sisense Compose SDK on AWS, Lobby governance behind it.

AWS · Sisense

FAQ · TECHNICAL DECISION-MAKER

Six answers before the first meeting.

The default infrastructure is AWS, and most projects go into the client's own AWS account. When a client requires Azure, GCP, on-premises, or a hybrid stack, the case is evaluated and the scope adjusts. AWS-first is the default, not a mandate.

The standard is the client's AWS account. Environment isolation, auditable logs, and code delivered to the client are part of the model. BlueMetrics does not access production data unless the continuous operation contract (AI as a Service) explicitly provides for it.

Advanced is the tier that requires multiple certifications, validated cases, and proven technical capacity. BlueMetrics operates at this level with more than 10 active certification types on the team and 200+ projects on AWS.

Most generative AI implementations use Bedrock, for the isolation, the governance, and the ability to switch models without rebuilding the pipeline. Direct models (the Anthropic API, OpenAI) come in when the case needs a resource not yet available in Bedrock.

The team is certified in ML Engineer Associate and ML Specialty, with training, deployment, and monitoring pipelines in production in cases such as Direcional (46% lower default rate) and Pix fraud detection models (R$1.5M avoided, under 1s latency).

The operation accounts for the applicable regulatory framework (LGPD, BACEN, sector rules). Auditable logs, environment isolation, and White Box AI give the traceability that audits require. AWS Advanced Partner does not replace compliance work. It sustains the infrastructure that makes compliance work feasible.

A technical conversation before the sales meeting.

A direct way to talk to engineering: stack, constraints, data, governance. No funnel, no pre-qualification. If the fit is clear, the commercial part comes later.