Services

Four practice areas. End-to-end data & AI delivery.

From data ingestion to production-ready intelligence, we provide the expertise required to design, build and scale modern data and AI platforms.

Data Engineering

Build the foundation that makes everything else possible

We design and build scalable, reliable and governed data systems that power analytics, AI and business transformation.

SourcesERP, CRM, SaaS, IoT and event streams
IngestBatch and real-time integration
LakehouseUnified, open and scalable storage
GovernQuality, lineage and controls
ServeTrusted data for analytics and AI

Business Outcomes

Unified operational visibility
Trusted enterprise data
Real-time data availability
Reduced reporting latency
Improved governance & compliance

Our Capabilities

Lakehouse ArchitectureData Platform ModernizationETL / ELT EngineeringReal-time Streaming PipelinesData Quality & ObservabilityGovernance & LineageDataOps Enablement
Technologies
SnowflakeSnowflake
DatabricksDatabricks
Apache SparkApache Spark
KafkaKafka
AirflowAirflow
dbtdbt
Analytics & Business Intelligence

Turning data into decisions leaders trust

Governed, self-service analytics that give every team a single trusted view, so the business decides from the number instead of arguing about it.

Executive visibility
Faster operational decision-making
CollectModelVisualizeShareDecide
Self-service analytics
Reduced reporting dependency
Improved KPI accountability
Capabilities
Executive dashboardsKPI reporting frameworksSelf-service analytics platformsEmbedded analyticsReporting modernizationData literacy enablement
Technologies
Power BIPower BI
TableauTableau
PostgreSQLPostgreSQL
MongoDBMongoDB
PythonPython
GrafanaGrafana

Machine Learning &
MLOps

From AI pilots to enterprise impact.

Business outcomes
  • Forecasting and optimization
  • Intelligent automation
  • Recommendation systems
  • Operational efficiency gains
  • Improved business planning
Capabilities
  • Predictive Modeling
  • Forecasting
  • Recommendation Systems
  • Classification
  • Anomaly Detection
  • MLOps Lifecycle Management
  • Model Monitoring
Technologies
PythonPython
Apache SparkApache Spark
MLflowMLflow
KubernetesKubernetes
AWS SageMakerAWS SageMaker
Vertex AIVertex AI
Generative AI

Enterprise AI, beyond the chatbot

A simple journey from your enterprise data, through the right technology ecosystem, into AI capabilities that deliver measurable business outcomes, tailored to each client rather than a fixed stack.

Enterprise Data
  • Documents
  • Databases
  • Applications
  • APIs
  • Web
Technology Ecosystem
  • Azure OpenAI
  • AWS Bedrock
  • Claude
  • Gemini
  • LangChain
  • LlamaIndex
AI Capabilities
  • Enterprise LLM integration
  • Retrieval-Augmented Generation
  • AI agent development
  • Document intelligence
  • Copilots and conversational AI
  • AI governance and strategy
Business Outcomes
  • Knowledge retrieval systems
  • AI-powered copilots
  • Workflow automation
  • Faster decision cycles
  • Improved employee productivity

Reference Architecture

A proven architecture for modern data & AI

Source Systems
ERP
CRM
SaaS Applications
IoT Devices
Event Streams
Ingestion & Integration
FivetranFivetran
KafkaKafka
CDC
APIs
Custom Connectors
Storage & Processing
Data Lakes(S3, ADLS, GCS)
SnowflakeSnowflake
DatabricksDatabricks
Delta LakeDelta Lake
Apache IcebergApache Iceberg
Transformation & Governance
dbtdbt
Apache SparkApache Spark
Data Quality Monitoring
Metadata Management
Lineage
Governance Controls
Analytics & AI
Dashboards
Machine Learning Models
LLM Applications
APIs
AI Agents
Every layer is designed for scalability, extensibility, cost transparency, security, and compliance.
ScalabilityBuilt to scale with business growth
ExtensibilityModular design with flexible integrations
Cost TransparencyOptimized resource usage and clear visibility
SecurityEnd-to-end security by design
ComplianceBuilt for regulatory and industry compliance

How We Engage

From strategy to scale. Real impact, together.

A collaborative, iterative approach that turns data and AI potential into measurable business outcomes.

Discover & Assess
2 to 3 weeks
  • Data maturity assessment
  • Stakeholder interviews
  • Use-case prioritization
  • Value opportunity roadmap
Foundation Build
4 to 8 weeks
  • Platform setup
  • Pipeline development
  • Governance implementation
  • Data quality & security
Value Delivery
4 to 6 weeks
  • First use case in production
  • Business outcomes validated
  • User adoption & feedback
  • Iterate and optimize
Scale & Evolve
Ongoing
  • Expand use cases
  • Automate processes
  • Embed AI across functions
  • Drive continuous value
Delivery Models
Fixed-Price Projects

Clearly scoped outcomes and timelines for a defined deliverable.

Dedicated Data & AI Teams

An embedded engineering pod that scales with your roadmap.

Staff Augmentation

Senior specialists who slot into your existing teams.

Request a Free Data Maturity Assessment →