What we do

Data engineering for every part of your data team.

We work with data platform, governance, analytics and data operations teams. We start with your top priority and build from there.

1Modernize

Data platform modernization

For data platform leaders moving off legacy systems

  • Older warehouses and Hadoop moved to a modern platform, with code converted and results checked
  • Batch and real-time data pipelines
  • ERP and CRM data brought into one platform, including SAP
2Govern

Data governance and quality

For governance, risk and compliance teams

  • Data lineage, access control and a searchable catalog
  • Quality rules and a named owner for each data area
  • One master record for each customer, product and asset
  • Controls for HIPAA, SOC 2, GDPR and financial regulations
3Analyze

Analytics and BI

For analytics leaders and business teams

  • Moves from older reporting tools to modern BI
  • One shared set of metrics, so every team reports the same numbers
  • Forecasting and planning models built on trusted data
  • Data ready for AI work
4Operate

Data operations

For the teams that keep data running

  • Pipeline monitoring for freshness, quality and failed runs
  • Platform cost and capacity managed over time
  • Audit evidence and access reviews kept current
  • A named owner when something breaks

Data and AI

We build your data foundation and put AI to work across your workflows.

AI needs trusted data. We plan each data program around your AI use cases. The data is ready when the AI work starts.

Build

Data ready for AI

  • Data prepared for search, analytics and agents
  • Documents and data your agents can reach safely
  • Pipelines monitored in production

AI on your workflows

  • AI agents that work inside your business workflows
  • Enterprise search across your documents and data
  • The right model for each task
  • A person approves key decisions
AI Engineering
Go-live

In production

Data and AI working together

  • Use cases chosen by business value and data readiness
  • One set of rules for data and AI
  • Access control and audit, from the source data to each agent
  • Support as your use grows

Data foundations by industry: Healthcare data foundation · Manufacturing data foundation · Customer and loan data foundation

Platforms

We work on the platform you run.

Our engineers work on every major cloud and data platform. We build on open standards, so you can change platforms later.

We also modernize on-premises platforms, including Oracle, Teradata and Hadoop.

Data, governance and analytics platforms

How we work

Our delivery model.

Our teams work inside yours, from the first assessment to running what we build. Most engagements start with a two- to three-week Data Readiness Assessment.

Data engineering teams

Dedicated teams build your data foundation, on-premises or in your cloud.

AI pods

A forward deployed engineer and an AI pod put AI to work on your workflows. A person approves key decisions.

Run and operate

We run and support what we build, and improve it as your use grows.

Parkar is SOC 2 Type II and ISO 27001 certified. AI Engineering ›

Client results

Data foundations in production.

A clinician and a colleague reviewing information together
Healthcare, data foundation

15+ data sources in one governed foundation

A health system brought clinical, operational and outside data together. Its core systems stayed in place.

15+data sources in one model on Microsoft Fabric
Read the case study ›
An analyst reviewing customer and loan reports on two screens
Financial services, credit card servicer

One customer profile across every product line

A US credit card servicer moved five warehouses onto one platform.

2new product lines launched
Read the case study ›

Get started

Start with where your data stands.

A two- to three-week Data Readiness Assessment scores your data and ends with a ranked plan.

Data Readiness Assessment2 to 3 weeks

Ends with a ranked list of work and clear next steps.

In the first phase
  • One business area on a modern data platform
  • One trusted data set in daily use
  • Governance in place on your first data set

From there we build in stages, starting where the payback is fastest.

4 minutes

AI Readiness Diagnostic

Ten questions about your data, systems and teams. You get a score and a clear place to start.

Take the AI Readiness DiagnosticDownload a sample report ›
2 to 3 weeks

Data Readiness Assessment

Our data engineers score your data and give you a ranked plan for the first projects.

Book a Data Readiness AssessmentDownload a sample report ›
5 days

AI Use Case Prioritization

Your AI ideas scored and ranked, with the right agent, model and size for each.

Book AI Use Case PrioritizationDownload a sample report ›