Data Engineering, Integration & AI

From Raw Data to
Intelligent Decisions

Curated Miami designs and delivers modern data infrastructure — event streaming, integration pipelines, analytics platforms, and AI agents — across every major cloud.

Real-time
Event streaming pipelines
360° View
Unified data consolidation
AI-Native
Analytics agents & LLM-ready data
4 Clouds
AWS • GCP • Azure • OCI

Now offering AI-powered analytics agents — autonomous systems that monitor your data, surface insights, and answer business questions in natural language.

Learn more →
Platform expertise
Amazon Web Services
Google Cloud Platform
Microsoft Azure
Oracle Cloud Infrastructure
Data Engineering

The foundation that everything runs on

We architect and deliver the full data stack — from ingestion and integration through transformation and analytics — whatever cloud you run on.

01

Event Streaming & Real-Time Pipelines

High-throughput, low-latency architectures that capture events from every system the moment they happen — feeding both operational systems and AI agents in real time.

  • Pub/sub and event-driven architectures
  • Change data capture (CDC) from operational databases
  • Stream enrichment, filtering, and routing
  • Real-time alerting and monitoring
  • Kafka, Kinesis, Pub/Sub, and Event Hubs
02
AI-enhanced

Data Consolidation & Integration

Unified, governed data from every source — the clean, structured foundation that makes AI and analytics reliable rather than risky.

  • ETL/ELT pipeline engineering
  • API, database, and flat-file integrations
  • Master data management (MDM)
  • Data quality validation and lineage tracking
  • Lakehouse and data warehouse design
03
AI-enhanced

Business Analytics Infrastructure

Curated, analysis-ready datasets that power your BI tools today — and serve as the context layer for AI agents and language models tomorrow.

  • Data warehouse and semantic layer design
  • Longitudinal and multilevel data modeling
  • Power BI, Looker, Tableau, and Metabase
  • Executive dashboards and operational reporting
  • KPI frameworks and metrics definitions
04

Integration Architecture & Strategy

The integration strategy that aligns your technology with long-term goals — designed to support both today's reporting needs and tomorrow's AI capabilities.

  • Current-state architecture assessment
  • Integration roadmap and platform selection
  • Data mesh and domain-oriented design
  • Version-controlled, reproducible pipelines
  • Cloud migration and modernization planning
AI & Intelligent Agents

Put your data to work — automatically

We build AI-powered systems on top of your data infrastructure — autonomous agents, predictive models, and natural language interfaces that turn your warehouse into an active intelligence layer.

AI-Powered Analytics Agents

Autonomous agents that continuously monitor your data pipelines, detect anomalies, and proactively surface insights — so your team is told what matters instead of having to find it.

  • Anomaly detection across KPIs and pipeline metrics
  • Natural language Q&A over your warehouse
  • Scheduled insight delivery to Slack, email, or Teams
  • Root-cause analysis on data deviations
FinanceRetailHealthcare

Predictive Analytics Pipelines

ML models embedded directly into your data infrastructure — predictions that flow into the same dashboards and systems your teams already use, automatically refreshed as new data arrives.

  • Churn prediction and customer lifetime value modeling
  • Fraud scoring and risk stratification
  • Demand forecasting and inventory optimization
  • Patient risk and clinical outcome modeling
HospitalityFinancialHealthcare

Natural Language to Data

Business users ask questions in plain English and get instant answers from your warehouse — no SQL, no ticket to the data team, no waiting. Built on your curated semantic layer.

  • Text-to-SQL query generation over your data models
  • BI copilots embedded in Power BI, Looker, and Tableau
  • Conversational dashboards for non-technical users
  • Powered by OpenAI, Anthropic, or open-source LLMs
All industries

Automated Data Quality & Observability Agents

AI agents that continuously validate your data — checking freshness, completeness, and consistency across pipelines — alerting before issues reach your dashboards or your stakeholders.

  • Automated schema drift and freshness monitoring
  • Statistical anomaly detection on row counts and values
  • Self-healing pipeline triggers on failure conditions
  • Data quality scoring and SLA reporting
EducationRetailFinance

LLM-Ready Data Infrastructure

We structure and serve your enterprise data as context for large language models — so AI products run on your proprietary knowledge, not just public training data.

  • Vector database design and embedding pipelines
  • Retrieval-augmented generation (RAG) architecture
  • Enterprise knowledge base construction
  • Fine-tuning data preparation and curation
All industries
How AI Fits In

AI runs on top of great data engineering

Every AI service we deliver is built on the same curated data foundation — which means your models are only as reliable as your pipelines.

01 — Foundation

Consolidated data

Clean, integrated, governed data from all your source systems — the non-negotiable starting point.

02 — Context

Semantic & vector layers

Business logic, definitions, and embeddings that let AI models understand what your data actually means.

03 — Intelligence

Models & agents

Predictive models, LLMs, and autonomous agents running continuously against your curated data.

04 — Action

Insights & automation

Answers, alerts, predictions, and automated decisions delivered to the people and systems that need them.

Cloud Platforms

Platform-agnostic, deeply experienced

We work with the platform that's right for your environment — and deploy AI services natively within whichever cloud you already run on.

AWS
Amazon Web Services
Streaming, storage & AI/ML
Kinesis Data StreamsMSK (Kafka)AWS GlueS3 Data LakeRedshiftSageMakerBedrockQuickSight
GCP
Google Cloud Platform
Big data & AI analytics
Pub/SubDataflowBigQueryVertex AICloud ComposerDataprocLookerGemini
AZR
Microsoft Azure
Enterprise integration & AI
Event HubsData FactoryMicrosoft FabricSynapse AnalyticsAzure OpenAIDatabricksPower BICopilot Studio
OCI
Oracle Cloud Infrastructure
Enterprise data & AI
OCI StreamingData IntegrationAutonomous DWOCI AI ServicesData FlowGoldenGateAnalytics Cloud
Industries We Serve

Domain expertise across key sectors

Data and AI challenges are industry-specific. We bring both technical depth and domain context to deliver solutions that fit your business — not just your tech stack.

Financial Services

Real-time fraud detection, regulatory reporting, AI-driven risk scoring, and unified client data.

Healthcare

HIPAA-compliant pipelines, patient data consolidation, clinical AI models, and outcomes analytics.

Education

Longitudinal student data, program analytics, AI-powered learning insights, and outcomes measurement.

Retail

Demand forecasting, AI-driven inventory optimization, customer analytics, and omnichannel integration.

Hospitality

Guest experience analytics, revenue management AI, loyalty program data, and operational reporting.

Our Approach

Structured delivery, lasting results

We move from discovery to production quickly — leaving behind systems your team can own, extend with AI, and build on.

01

Discover

Map your data landscape, sources, and AI readiness to define what needs to be built.

02

Design

Blueprint integration patterns, data models, and AI architecture for your context.

03

Build

Deliver production-grade pipelines, models, and agents — tested and version-controlled.

04

Validate

End-to-end testing and stakeholder review before anything goes into production.

05

Enable

Documentation, training, and managed services so your team owns it long-term.

Our Work

See what we build

Live examples of the dashboards, architecture, and outcomes we deliver — across industries and cloud platforms.

Interactive Demo

Miami-Dade County Public Schools — Microsoft Fabric Analytics

A live example of the Power BI analytics platform we built on Microsoft Fabric — ingesting M-DCPS data through Data Factory pipelines into OneLake, transformed with Fabric Notebooks, and exposed through Power BI Services. Data reflects real Miami-Dade County Public Schools figures.

Microsoft Fabric Power BI Report
Workspace: M-DCPS Analytics OneLake Connected
District Overview School Performance Attendance & Outcomes Educator Analytics
Total Enrollment
335,474
▼ 3.9% vs prior year
Graduation Rate
93.1%
▲ 1.3pts — Record high
Avg Daily Attendance
92.4%
▲ 0.8pts vs prior year
Total Schools
530
PK–12 · District A-Rating
Monthly enrollment trend — 2024-25Source: M-DCPS SIS via OneLake
Monthly enrollment from August 2024 to May 2025.
Proficiency rates by subjectFlorida State Assessments
Math 55%, Reading 56%, Science 52%, Writing 61%.
Graduation rate by subgroup — M-DCPS vs Florida State
Graduation rates for all major student subgroups.
Attendance by school type
Magnet Schools
95.2%
North Region
93.8%
Central Region
92.1%
District Avg
92.4%
South Region
91.4%
Charter Schools
90.6%
Top performing schools — M-DCPS 2024-25Fabric Notebook curated dataset · Gold layer
SchoolTypeRegionEnrollmentAttendanceGrad RateFL GradeAI Status
José Martí MAST 6–12 AcademyMagnetCentral1,84296.1%99.2%A✦ On track
Design & Architecture Senior HighMagnetCentral1,61495.8%98.7%A✦ On track
Marine Academy of Science (MAST@FIU)MagnetSouth1,29095.2%98.1%A✦ On track
Coral Gables Senior HighTraditionalCentral3,81293.4%96.8%A✦ On track
Hialeah Senior HighTraditionalNorth2,94091.2%91.4%A⚠ Monitor
Miami Norland Senior HighTraditionalNorth2,11889.6%88.3%B⚑ At risk
South Miami Senior HighTraditionalSouth1,87692.8%94.1%A✦ On track
Rolando Espinosa K–8 CenterK-8Central1,10294.3%A✦ On track
Fabric AI Agent Insight — Enrollment decline of 13,059 students (-3.9%) is concentrated in North Region traditional schools. Predictive model flags 3 schools at elevated chronic absenteeism risk entering Q3. Miami Norland Senior High shows a 4.2pt attendance drop correlating with a 2.1pt graduation rate decline — recommend early intervention review. Magnet school attendance (95.2%) outperforms district average by 2.8pts. Next automated report: Monday 7:00 AM.
Live · Refreshed 7:02 AM today Data source: M-DCPS SIS · OneLake Gold layer · Curated Miami Data Engineering
Microsoft Fabric · Power BI · Lakehouse: mdcps-analytics-prod

Architecture

How we structure your data

Every solution we build follows this layered approach — from raw source systems through governed transformation to analytics-ready outputs.

Source Systems
Student databases · SIS · LMS · Assessment platforms · Attendance · HR/Payroll
Layer 1
Ingestion
Data Factory · Kafka streams · CDC · API connectors · Batch + real-time pipelines
Layer 2
Transformation
Python · SQL · dbt · Entity linking · Longitudinal structuring · Data quality rules
Layer 3
Curated Storage — Lakehouse / OneLake
Bronze · Silver · Gold zones · Delta tables · Version-controlled · Governed datasets
Layer 4
Analytics & AI
Power BI · Looker · Tableau · AI agents · Natural language to data · Predictive models
Layer 5

Case Studies

Representative client outcomes

Examples of the challenges we solve and the results we deliver — across education, financial services, healthcare, retail, and hospitality.

Education

Unified longitudinal student data platform for a multi-site early childhood program

Challenge

Student records fragmented across 6 source systems with no consistent identifiers, making longitudinal analysis and grant reporting manual and error-prone.

Solution

Microsoft Fabric lakehouse with Data Factory pipelines linking children, classrooms, educators, and programs using consistent IDs and longitudinal data structuring.

83%
Less manual reporting
6
Systems unified
Financial Services

Real-time fraud detection pipeline for a regional bank processing 2M+ daily transactions

Challenge

Batch fraud detection running 4-hour cycles meant fraudulent transactions weren't flagged until significant losses had occurred.

Solution

AWS Kinesis event streaming pipeline feeding an ML scoring model with sub-second transaction flagging and automated compliance case creation.

$4.2M
Annual fraud reduction
<800ms
Scoring latency
Healthcare

Patient outcomes analytics platform across a network of 12 community health centers

Challenge

12 clinics running different EHR systems with no shared data model, making population health analysis impossible at the network level.

Solution

HIPAA-compliant GCP BigQuery lakehouse with a unified patient data model and Looker dashboards for care team decision support.

62%
Faster reporting
18%
Fewer missed follow-ups
Retail

Omnichannel inventory and demand forecasting for a 200-location retail chain

Challenge

In-store, e-commerce, and warehouse inventory siloed across 4 systems with no real-time visibility, causing chronic overstock and stockout situations.

Solution

Azure Synapse omnichannel integration with real-time inventory streaming and ML demand forecasting feeding automated replenishment triggers.

31%
Fewer stockouts
$2.8M
Inventory savings
Hospitality

Guest experience and revenue analytics platform for a boutique hotel group

Challenge

Guest data scattered across PMS, loyalty, F&B, and spa systems with no unified profile, making personalization and revenue decisions data-blind.

Solution

OCI-based guest 360 platform consolidating all touchpoints with AI-driven revenue management dashboards and real-time occupancy analytics.

14%
RevPAR increase
360°
Unified guest profile

Let’s talk about your data and AI goals

Whether you’re modernizing your data stack or ready to deploy AI agents, we can help design the right solution.

Message sent!

Thanks for reaching out. Our team will be in touch within one business day.

Or email us directly at [email protected]