AI Services

Data& Analytics

We build governed, AI-ready data platforms, then add machine learning, predictive analytics and natural-language analytics so your teams can ask better questions and act faster.

One sourceof trusted, governed data
Predictiveforecasts and risk scores
Ask in plain Englishconversational analytics

What’s Included

Our capabilities

AI-ready data platforms, machine learning, predictive and conversational analytics and MLOps for organizations in the US, Canada, India, UAE and Australia.

Data engineering & pipelines

Reliable ingestion from applications, IoT devices and third parties into a central platform.

Lakehouse & warehouse

Modern data platforms on Databricks, Snowflake, BigQuery, Redshift or Fabric.

Data governance & quality

Catalogues, lineage, access controls and data-quality checks you can trust.

Machine learning & forecasting

Predictive models for demand, risk, churn, maintenance and outcomes.

Conversational analytics

Ask questions in plain language and get answers, charts and explanations from your data.

MLOps & monitoring

Deployment, retraining and monitoring so models stay accurate in production.

Use Cases

Where it delivers value

Proven patterns across the industries we serve.

Healthcare

Readmission risk, capacity forecasting and remote patient monitoring insights.

Insurance

Claims analytics, fraud detection and pricing models.

Manufacturing & IoT

Predictive maintenance and quality analytics from sensor data.

Retail

Demand forecasting, inventory optimization and customer analytics.

Finance

Cash-flow forecasting, anomaly detection and management reporting.

Leadership

Executive dashboards and self-service analytics across the business.

HealthcareInsuranceFinancial servicesManufacturingRetailAgricultureReal estate

How We Deliver

A clear, five-step approach

Every engagement follows the same proven path, shaped around your goals, risks and timelines.

  1. 01

    Discover

    Understand key decisions, data sources and business questions.

  2. 02

    Engineer

    Build pipelines, lakehouse platforms and governed data models.

  3. 03

    Model

    Develop machine learning, forecasting and predictive models.

  4. 04

    Visualize

    Deliver dashboards and conversational analytics.

  5. 05

    Operationalize

    Deploy with MLOps, monitoring and data-quality controls.

What you get

  • Data strategy and architecture
  • Governed data platform and pipelines
  • Machine learning models and APIs
  • Dashboards and conversational analytics
  • MLOps and data-quality monitoring

Technologies & frameworks

DatabricksSnowflakeMicrosoft FabricPower BITableauPythonApache SparkAWS & Azure ML

We are platform-neutral and work within your existing cloud, security and data standards.

Where We Work

Serving clients in 5 countries

Onshore, nearshore and offshore delivery from our teams in Canada and India, with the time-zone overlap and data-residency options each region needs.

USUnited States

Nearshore from Canada with full time-zone overlap, or cost-effective offshore delivery from India.

CACanada

Onshore team in Alberta for same-time-zone collaboration, on-site workshops and Canadian data residency.

INIndia

Local engineering centre in Secunderabad, Hyderabad, for direct engagement and scalable delivery.

AEUAE

Delivery from India with a strong working-day overlap with Gulf Standard Time.

AUAustralia

Delivery from India with morning overlap for Australian teams and follow-the-sun support.

FAQ

Common questions

Quick answers about Data & Analytics.

What is an AI-ready data platform?

It is a governed, well-organized data foundation, with clean pipelines, consistent definitions and access controls, that analytics and AI models can use reliably.

What is conversational analytics?

It lets people ask questions about business data in plain language and get answers, charts and explanations, without writing queries or building reports.

Can you use data from our IoT devices?

Yes. We ingest and process sensor and device telemetry alongside business data for monitoring, predictive maintenance and operational insight.

How do you keep machine learning models accurate?

Through MLOps: automated monitoring of data and prediction quality, alerts for drift, and scheduled retraining and validation.

Ready to get started?

Tell us about your goals and we’ll propose the right team, plan and engagement model.

Contact us