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Cloud data and AI

Design, migrate and run modern data platforms, then put analytics, machine learning and generative AI to work on them in production.

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ERP and financeCRM and salesApps and IoTFiles and docsLakehouseRawCleanedBusiness-readyDashboardsBIML modelsforecastsAI assistantsRAG and agentsGovernance, quality and security across every layer

Data platform modernization

Move from aging on-premises warehouses to a cloud lakehouse that scales with the business and costs less to run. We plan the target architecture, migrate in phases and prove every number matches before anything is switched off.

  • Current-state assessment and target architecture
  • Snowflake, Databricks, BigQuery, Redshift and Fabric builds
  • Code conversion and pipeline re-platforming
  • Parallel runs with automated reconciliation

Data engineering and pipelines

Reliable batch and real-time pipelines that bring data from every application into one governed platform, with monitoring that catches problems before your reports do.

  • Batch, streaming and change data capture
  • Spark, dbt, Airflow, Glue and Data Factory
  • Kafka, Kinesis and Event Hubs
  • Pipeline observability and alerting

Database engineering

Deep database expertise is where our team started. We design, tune and stabilize the databases your operations depend on, on-premises or in the cloud.

  • SQL Server, Oracle, PostgreSQL, MySQL and MongoDB
  • Query and index performance tuning
  • High availability, backup and disaster recovery
  • Database migration to managed cloud services

Generative and agentic AI

AI assistants and agents that work on your private data, answer with sources, and take action in your systems with people in control of the decisions that matter.

  • Retrieval-augmented generation on company data
  • AI agents for document-heavy operations
  • Azure OpenAI, Amazon Bedrock and Vertex AI
  • Guardrails, access control and evaluation

Machine learning and MLOps

Forecasting, classification and anomaly detection models that retrain on fresh data and stay accurate after launch.

  • Demand, revenue and cash-flow forecasting
  • Churn, risk and anomaly models
  • Automated training and deployment pipelines
  • Drift monitoring and retraining

Analytics and business intelligence

Dashboards and self-service reporting built on governed data, so every team works from the same numbers.

  • Semantic models and metric definitions
  • Power BI, Tableau and Looker
  • Executive and operational dashboards
  • Embedded analytics in your products

Data governance and security

Know where your data comes from, who can see it and whether it can be trusted, without slowing teams down.

  • Data catalog and lineage
  • Data quality rules and monitoring
  • Masking and protection of personal data
  • Role-based access and activity logging

Platforms and tools we work with

Cloud
AWS, Microsoft Azure, Google Cloud
Data platforms
Snowflake, Databricks, BigQuery, Redshift, Azure Synapse, Microsoft Fabric
Databases
SQL Server, Oracle, PostgreSQL, MySQL, MongoDB, Cosmos DB, DynamoDB
Data engineering
Python, SQL, Spark, Airflow, dbt, Kafka, Azure Data Factory, AWS Glue
AI and ML
Azure OpenAI, Amazon Bedrock, Vertex AI, LangChain, vector databases, MLflow
Engineering and analytics
Kubernetes, Docker, Terraform, GitHub Actions, Azure DevOps, Power BI, Tableau

Related solutions

Programs we deliver end to end. See all solutions.

Data modernization

Legacy warehouse to cloud lakehouse

Move Oracle, Teradata or SQL Server warehouses to Snowflake, Databricks or BigQuery without disrupting reporting.

  • Pipeline re-platforming and code conversion
  • Parallel runs with automated reconciliation
  • Phased cutover and decommissioning
See the solution blueprint
Generative AI

Enterprise knowledge assistant

A secure AI assistant that answers from your contracts, policies, tickets and databases, with sources cited.

  • Retrieval-augmented generation on private data
  • Role-based access and guardrails
  • Evaluation harness to measure accuracy
See the solution blueprint
Agentic AI

AI agents for back-office operations

Agents that read requests, classify them, take action in your systems and hand exceptions to people.

  • Document intake, extraction and validation
  • Integration with ERP, CRM and ticketing
  • Human-in-the-loop review and full activity logs
See the solution blueprint
Real-time data

Streaming analytics platform

Event-driven pipelines that turn operational changes into live dashboards and alerts in seconds.

  • Change data capture from transactional databases
  • Kafka, Kinesis or Event Hubs processing
  • Anomaly and fraud alerting
See the solution blueprint
Machine learning

Forecasting with MLOps

Demand, revenue and cash-flow models that retrain on fresh data and stay accurate in production.

  • Feature engineering and model selection
  • Automated training and deployment pipelines
  • Drift monitoring and retraining triggers
See the solution blueprint

Solution blueprints

Reference architectures for how we design and deliver this work.

Blueprint · Data modernization

Medallion lakehouse on Databricks or Snowflake

A bronze, silver and gold lakehouse that turns raw data from every system into trusted, analytics-ready and AI-ready data products.

View the architectureBlueprint · Real-time data

Real-time analytics with Lambda and Kappa architectures

Two proven patterns for combining historical and real-time data, and how we choose between them.

View the architectureBlueprint · Data modernization

Cloud data warehouse with modern ELT

A Snowflake, BigQuery, Redshift or Synapse warehouse with dbt-modeled marts for finance, sales and operations.

View the architectureBlueprint · Generative AI

Secure generative AI with retrieval-augmented generation

An AI assistant that answers from your own documents and data, respects permissions, cites sources and is measured for accuracy.

View the architecture

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