Engineering Services — Petrabytes
Engineering Services

We show up. We build it. You own it.

Scoped projects. Lean engineering teams. Production-ready deliverables. Petrabytes engineers design, build, and hand over enterprise data and AI platforms — on time, on budget, with your team trained to run them.

Scope a project → Talk to an engineering lead ↗
12
Practice areas
5
Phase delivery model
100%
Knowledge transfer
How a Project Works

Every engagement follows the same five phases. No surprises.

PHASE 1 · WEEK 1–2

Assess

We audit your current data landscape, identify gaps, and define what "done" looks like. You get a written assessment with architecture recommendations and a scoped delivery plan.

Data landscape auditArchitecture blueprintDelivery plan
PHASE 2 · WEEK 2–4

Design

Platform architecture, data models, integration patterns, governance policies. Everything documented before a single line of code is written.

Platform designData modelIntegration specGovernance framework
PHASE 3 · WEEK 4–12

Build

This is where the work happens. Pipelines built. Connectors configured. Quality rules enforced. AI integrations wired. Your team is in every sprint review.

Data pipelinesPlatform configAI integrationsTest coverage
PHASE 4 · WEEK 12–14

Deploy & Validate

Production rollout with governance checks, performance validation, security review, and user acceptance testing. Nothing goes live until it's proven.

Production deploymentUAT sign-offSecurity review
PHASE 5 · WEEK 14–16

Transfer & Optimize

Runbooks. Training sessions. Optimization recommendations. Your team takes full ownership. We stay available for questions — but you don't need us anymore.

RunbooksTeam trainingOptimization reportHandover complete
Engagement Types

Pick the project. We'll scope the team, timeline, and deliverables.

ENTRY POINT

AI Readiness Assessment

The fastest way to understand where you stand — and what it will take to operationalize AI on your data.
You get
  • Data landscape audit
  • AI readiness scorecard
  • Gap analysis & prioritization
  • Actionable roadmap
⏱ Typical: 2–3 weeks
MOST COMMON

Platform Implementation

Deploy PIEScale or build a custom enterprise data platform from architecture through production.
You get
  • Platform architecture & deployment
  • Cloud infrastructure
  • Enterprise integration
  • Production readiness review
⏱ Typical: 8–16 weeks

Enterprise AI Deployment

Move beyond pilots. Deploy production AI assistants, agents, domain models, and MCP integrations on governed data.
You get
  • AI application architecture
  • MCP server configuration
  • Enterprise search setup
  • Agent & workflow automation
⏱ Typical: 6–12 weeks
Full Project Menu

Twelve practice areas. Each with a defined scope and timeline.

Platform Implementation

Architecture, deployment, integration, production readiness.

8–16 weeks

Data Modernization

Legacy migration, quality, metadata, OSDU enablement.

10–20 weeks

Data Engineering

Pipelines, APIs, transformation, enterprise data models.

6–14 weeks

Enterprise AI

AI apps, agents, search, MCP, workflow automation.

6–12 weeks

Platform Optimization

Health checks, performance, cost, security, governance.

2–4 weeks

Data Strategy

Roadmap, architecture assessment, AI readiness, business case.

2–4 weeks

Analytics & BI

Dashboards, KPI frameworks, self-service reporting.

4–8 weeks

Real-Time & Streaming

IoT ingestion, SCADA, edge computing, event architecture.

6–12 weeks

AI Lifecycle (MLOps)

Model monitoring, retraining, drift detection, governance.

4–8 weeks

Knowledge Management

Capture, govern, and activate enterprise knowledge — reducing tribal knowledge loss and improving GenAI accuracy.

4–8 weeks

AI Readiness Assessment

Structured evaluation of your data, infrastructure, and organizational readiness to operationalize enterprise AI.

2–3 weeks

Predictive Maintenance

Energy-specific ML models for equipment reliability, pipeline integrity, and production uptime — from sensor to insight.

6–10 weeks
The Difference

What you get from Petrabytes vs. a traditional consulting firm.

✕ Traditional Consulting

  • 10-person team, 3 of them useful
  • Custom-build everything from scratch
  • 6 months of "discovery"
  • 200-page PowerPoint, no working code
  • Knowledge stays with the consultants
  • Success = project closed

✓ Petrabytes Engineering

  • Lean team of 3–5 specialist engineers
  • Platform-first — build on PIEScale, not from zero
  • 2-week assessment, then we're building
  • Working platform in production
  • Runbooks, training, your team owns it
  • Success = your team runs it without us
We Work on Your Stack

Our engineers are certified across modern enterprise platforms.

Cloud

AWSMicrosoft AzureGoogle CloudHybrid & On-Prem

Data & AI

DatabricksSnowflakeLakehousesStreaming & CDCOSDU

Enterprise

REST APIsEvent StreamingSAP / Historian / SCADAIdentity & Access

Need engineers for longer than a project?

If your transformation needs embedded engineers working inside your team for months — not a scoped project with a handover — that's Forward Deployed Engineering. Different model, different page.

Explore FDE →
Start a Project

Tell us what you need built. We'll scope it in a week.

A 30-minute discovery call. A written proposal within 5 business days. No 6-month "assessment phase" — just engineering.

Scope a project → Talk to an engineering lead ↗