Technical capabilities

Production-quality AI — from pipelines to models in production.

We don't deliver just code; we craft outcomes. We build the custom secret sauce systems to automate and operationalize your workflows.

Data platforms & pipelines

ETL, data warehouses, and API integrations that consolidate scattered data into a single source of truth.

Machine learning & data science

Models, forecasting, and rigorous analysis that turn your data into reliable, measurable decisions.

Generative AI applications

LLM-powered tools built on your own data — with the evaluation, guardrails, and security enterprises require.

Cloud & MLOps

Secure, scalable infrastructure and the deployment pipelines that keep data and models running in production.

Core capabilities by domain

The tools and technologies we reach for, grouped by the problems they solve. We're deliberately technology-agnostic — we pick what fits the job.

Generative AI & LLMs

Open-source model optimzationInference optimizationToken optimizationOpenAIAnthropicLangChainLlamaIndexpgvectorPineconeRAG evaluationMCP Servers

Machine learning & data science

Frontier model integrationAWS BedrockPyTorchTensorFlowscikit-learnXGBoostpandasMLflow

Data engineering & pipelines

AirflowdbtSparkKafkaSnowflakeRedshiftPostgreSQLFivetran

Cloud & infrastructure

AWSGCPAzureKubernetesDockerTerraformGitHub Actions

Languages & interfaces

PythonSQLTypeScriptGoScalaRESTGraphQL

Governance & security

RBACSOC 2 practicesHIPAAPII handlingData lineageAudit logging

Reference architecture

How a platform we build fits together

A typical end-to-end data & AI platform — from raw sources to production applications, with governance and observability spanning every layer.

SourcesApps · APIs · Files · Events
IngestionBatch & streaming
Storage & warehouseLake · Warehouse
Transform & modeldbt · Features · ML
Serving & appsAPIs · GenAI · BI
Governance · Security · Observability — across every layer

Delivery lifecycle

01

Discover

We map your data, systems, and goals, and agree on what success looks like before writing code.

02

Architect

We design the platform — data models, infrastructure, and interfaces — for reliability and scale.

03

Build

The engineers who own your project implement in tight iterations, with tests and reviews from the first commit.

04

Validate

We verify correctness with automated tests, data validation, and evaluation against real cases.

05

Deploy

We ship to production on secure, reproducible infrastructure with CI/CD and rollback.

06

Operate

We monitor, maintain, and improve — owning outcomes once systems are live.

Engineering practices

The disciplines we bring to every engagement — the reason our systems hold up in production.

Automated testing

Unit, integration, and data tests so changes ship with confidence, not hope.

CI/CD

Every change is built, tested, and deployed through repeatable, reviewable pipelines.

Infrastructure as code

Environments defined in Terraform — reproducible, versioned, and auditable.

Observability

Metrics, logging, and alerting so problems are caught before your users are.

Security & compliance

Least-privilege access, encryption, and controls aligned to HIPAA and SOC 2.

Documentation & handoff

Clear docs and knowledge transfer so your team can own the system after us.