WHY THIS STACK
Three technical decisions that show up in every project.
01 · INFRA
AWS-first, with flexibility where the use case calls for it.
The house standard is AWS: Bedrock, SageMaker, Glue, S3. When a client runs Azure, GCP, on-premises, or a hybrid stack, we evaluate the case and adjust scope with the same governance discipline. A declared preference for AWS, proven capability across other clouds.
02 · MODELOS
The use case decides the model.
Anthropic Claude for high context volume, explainability, and agentic tasks. OpenAI for targeted generation, embeddings, and fine-tuning. Open-source via Bedrock when the case calls for it. The decision is always technical.
03 · DADOS
A Databricks lakehouse when volume and governance call for it.
For projects with critical data volume, multi-source ingestion, and pipeline governance in regulated environments, Databricks becomes the data layer. For smaller bases, S3 + Glue + Redshift handle it without the extra complexity.
COVERAGE MAP
Four technologies mastered in production.
Each one solves a different part of the delivery. AWS is the anchor partnership, where the depth shows at scale.
CERTIFICATIONS WALL
Over 10 active certification types on the team.
AWS families, with several certifications in each, plus Sisense Gold Partner and Compose SDK. This is what backs "AWS-first" and "Gold Partner" at the human level.
Cloud Practitioner
AI Practitioner
Solutions Architect Associate
Developer Associate
Data Engineer Associate
ML Engineer Associate
ML Specialty
GenAI Developer Professional
Sisense Compose SDK
Sisense Gold Partner
STACK IN NUMBERS
Depth that shows up in the contract.
Four indicators that make the delivery concrete. No abstract metrics.
CASES BY TECHNOLOGY
Four proofs in production.
Four projects in production, organized by the core technology behind each delivery.
TECHNOLOGY · SISENSE
Where it all began: Sisense Gold Partner since 2016.
BlueMetrics started on Sisense in 2016 and never left. Today it is one of six Gold Partners for the platform worldwide, with more than 60 global clients served. It is the rarest credential in the portfolio, and it comes in when BI needs embedded analytics, white-label, or Compose SDK in production.
FAQ — TECHNICAL VALIDATION
Five answers before the sales meeting.
The default infrastructure is AWS, and most projects go into the client's own AWS account. When a client requires another provider (Azure, GCP, on-premises) or runs a hybrid stack, the team evaluates it case by case. AWS-first is not AWS-only.
Anthropic Claude is the default for cases with high context volume, explainability requirements, and agentic tasks. OpenAI GPT comes in for specific cases such as content generation, embeddings, and fine-tuning when applicable. The choice follows the use case, not the brand.
Databricks comes in when a client has critical data volume, multi-source ingestion, and pipeline governance requirements in a regulated environment. The Delta lakehouse solves cases where the S3 + Glue + Redshift stack would start getting expensive to operate. For most projects, AWS-native handles it.
BlueMetrics operates with 8 active AWS certification families on the team (Cloud Practitioner, AI Practitioner, Solutions Architect Associate, Developer Associate, Data Engineer Associate, ML Engineer Associate, ML Specialty, GenAI Developer Professional) plus Sisense certifications in Compose SDK. Continuous renewal is part of the operation.
Yes, when the case justifies it. The 5 listed partnerships are the deepest ones, where BlueMetrics has certification, production cases, and a mature process. Adjacent stacks (Snowflake, Azure OpenAI, open-source models via Bedrock) come in through custom projects.