AI & Automation · Data & Analytics

Turn raw data into decisions that compound.

AI data analytics services delivering custom data engineering services, BI dashboards, data governance, and generative AI for data insights — an enterprise data analytics company building from data engineering foundations to executive-facing analytics.

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AI data analytics services

Custom data engineering services

Predictive analytics solutions

Generative AI for data insights

Business intelligence (BI) solutions provider

Self-service analytics platforms

50TB+

Data processed monthly

Scalable pipelines handling enterprise-grade volumes.

4×

Faster time-to-insight

Automated reporting that replaces weeks of manual work.

70%

Fewer ad-hoc data requests

Self-service analytics empower teams to query directly.

18%

Avg stockout reduction

Demand forecasting that optimises inventory decisions.

Trusted by enterprises worldwideCMMi Level 3ISO 27001SOC 220+ Years

Why MetaDesign

Hire data analytics developers for pipelines that run themselves.

Enterprise data analytics company delivering ETL, warehousing, BI dashboards — built by engineers who understand your business, not just SQL.

Full-Stack Data Engineering

Our custom data engineering services build the entire pipeline — ingestion, transformation, storage, and serving — not just the visualisation layer on top.

Insight-Driven Design

Custom dashboard development (PowerBI, Tableau, Looker) designed for decisions, not decoration. Every metric ties to a business outcome with clear drill-down paths.

Governance-First

As an enterprise data analytics company, we bake data catalogues, lineage tracking, access controls, and compliance into the architecture — not bolted on later.

Executive Dashboards

Hire data analytics developers for real-time KPI dashboards — revenue, pipeline, churn, and operational metrics in one view for C-suite.

Revenue Analytics

Predictive analytics solutions powering cohort analysis, LTV prediction, and pricing optimisation from your transaction data.

Supply Chain Analytics

Generative AI for data insights driving demand forecasting, inventory optimisation, and supplier performance tracking.

Customer 360

AI data analytics services unifying customer profiles from CRM, support, billing, and behaviour data for personalisation.

Compliance Reporting

Automated regulatory reports — SOX, GDPR, HIPAA — with audit trails and data lineage.

Real-Time Streaming

Hire machine learning experts for data mining on Kafka and Kinesis — fraud detection, clickstream analysis, and IoT telemetry.

Our approach

Five stages, paired end-to-end.

Predictable delivery. No black-box sprints.

Discover

Audit your data sources, quality, and current analytics maturity. Map stakeholder needs to data requirements.

Architect

Design the data platform — warehouse, lakehouse, or hybrid — with governance, lineage, and access controls.

Build

Develop ETL/ELT pipelines, data models, and transformation logic with version control and testing.

Visualise

Create dashboards and self-service analytics tools aligned to business KPIs and decision workflows.

Operate

Ongoing monitoring, pipeline maintenance, data quality checks, and continuous analytics improvement.

Customer value

Why enterprises trust us with their AI.

Real outcomes our clients report within the first engagement cycle.

Higher automation rates

Eliminate repetitive tasks and free your team to focus on strategic work.

Measurable accuracy

AI models with tracked precision, recall, and F1 scores — not guesswork.

Faster decision-making

Real-time insights and predictions that accelerate business decisions.

Reduced operational cost

Automation that pays for itself within the first quarter.

Production-grade reliability

Guardrails, monitoring, and fallback logic built into every AI system.

Knowledge transfer

Your team learns to maintain and extend AI systems independently.

Technology

Tools our data & analytics developers ship with.

We use what works. No vendor lock-in.

SnowflakeBigQueryRedshiftDatabricksDelta LakedbtAirflowDagsterFivetranAirbyteTableauPower BILookerMetabaseSupersetKafkaKinesisSparkPythonSQL

By the numbers

400+

Engineers worldwide

200+

Active clients

20yr

Pure-play software

94%

Client retention

Engagement models

Three ways to work with our Data & Analytics team.

Scale up, scale down — zero procurement headaches.

Fixed-scope project

Start-to-finish delivery with total cost, timeline, and scope agreed upfront. Best for well-defined builds and launches.

BEST FORNew product launches

Dedicated team

A ring-fenced squad — PM, tech lead, engineers, QA — fully managed by us, embedded in your workflow.

BEST FORLong-running platforms

Staff augmentation

Plug senior engineers into your existing team and tools. You manage priorities, we deliver results.

BEST FORCapacity gaps & sprints

From the Blog

Asked first, every time.

Don't see yours here? Send us the question — a principal engineer will reply within 24 hours.

Which BI tool is best for our organisation — Power BI, Tableau, or Looker?

As a business intelligence (BI) solutions provider, we evaluate based on your ecosystem. Power BI integrates natively with Microsoft 365 and Azure. Looker is ideal for Google Cloud teams. Tableau offers the most flexibility. We assess your data stack, team skills, and budget for custom dashboard development (PowerBI, Tableau, Looker).

Can you build data pipelines on top of our existing data warehouse?

Yes. Our custom data engineering services integrate with Snowflake, BigQuery, Redshift, Databricks, and custom warehouses — building ETL/ELT pipelines, transformation layers, and dashboards on top of your existing infrastructure without migration.

How do you ensure data quality across our analytics pipelines?

Our AI data analytics services include automated quality checks at every stage — schema validation, freshness monitoring, anomaly detection, and row-count reconciliation using Great Expectations and dbt tests with Slack/email alerting on failures.

Do you build real-time analytics dashboards with live data?

Yes. Hire data analytics developers who build streaming pipelines on Kafka, Kinesis, or Spark Streaming for sub-second analytics — fraud detection, clickstream analysis, operational monitoring, and IoT telemetry dashboards.

Can you help us become GDPR and HIPAA compliant with our data?

Yes. As an enterprise data analytics company, we implement comprehensive data governance frameworks with data classification, column-level access controls, PII anonymisation, audit trails, and retention policies aligned to your specific regulatory requirements.

How long does it take to build an enterprise data platform from scratch?

Foundation (warehouse + core pipelines + initial dashboards): 6–8 weeks. Full platform with governance, predictive analytics solutions, and streaming: 12–16 weeks. We deliver incremental value every sprint.

What is the difference between a data warehouse and a data lakehouse?

A data warehouse stores structured, pre-modelled data optimised for fast queries (Snowflake, BigQuery). A lakehouse combines warehouse performance with data lake flexibility — storing raw and structured data together (Databricks, Delta Lake). Our predictive analytics solutions work on both architectures.

Can your analytics platform support self-service queries by non-technical teams?

Yes. We build semantic layers with generative AI for data insights that business users explore through drag-and-drop interfaces in Looker, Metabase, or Power BI — no SQL knowledge required. Hire data analytics developers who set guardrails so business users explore freely.

How do your predictive analytics solutions integrate with existing enterprise ERP systems?

We integrate predictive analytics solutions by building secure, automated ETL pipelines that extract historical data from your ERP, process it through custom ML models, and push actionable insights back into the ERP dashboard.

Can your custom data engineering services handle petabyte-scale unstructured data lakes?

Yes, our custom data engineering services specialize in petabyte-scale big data architectures. We utilize Apache Spark, Hadoop, and cloud-native solutions like AWS S3 or Azure Data Lake to efficiently process massive unstructured datasets.

Build your data platform with engineers who get data.

Tell us about your project. We'll come back with a plan, a timeline, and the right team — no obligations.

Book a Call

Turn raw data into decisions that compound.