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Business Intelligence

Turn scattered data into clear answers

Custom BI platforms and automated reporting pipelines for organizations with complex data, senior BI engineers who model your warehouse, wire the pipelines, and ship dashboards teams genuinely trust.

~2wks
to project kickoff
100%
code & IP ownership
ISO 27001
aligned, not certified
6–10yrs
average engineering experience

We start with your problem, not the dashboard, the numbers nobody trusts, the reports that take days, the decisions made blind, and tell you honestly what it takes to fix it.

Business intelligence development services

From data architecture and warehouse design to dashboards and optimization. Pick a service to see how we approach it.

Packaged BI tools box you into rigid reporting that rarely matches how the business actually runs. When metrics, roles, and decisions differ by department, generic platforms breed workarounds rather than answers.

How we help

We build BI platforms around your business logic, data sources, and user roles, so reporting mirrors how you really operate. That can mean extending what you have, adding new capabilities, and shaping the platform to absorb shifting data volumes, users, and reporting needs over time.

Data scattered across systems produces inconsistent reporting and blocks any full picture. Weak warehouse design adds slow queries and climbing maintenance costs on top.

How we help

Our engineers design and build warehouses around your reporting patterns, data models, and performance targets, dimensional modeling, partitioning, and platform tuning in Snowflake, Redshift, or Azure Synapse. Your warehouse ends up stronger at reporting, historical analysis, and shared use across teams.

Manual extraction and transformation create bottlenecks, introduce errors, and stall reporting cycles. As source systems multiply, the mess grows faster than any manual process can track.

How we help

We build automated pipelines on modern orchestration frameworks that handle incremental loads, dependency chains, and quality checks at every stage. They cover batch and streaming data, keep audit trails, and recover from failures automatically, so data flows dependably from source to analytics on a schedule you can trust.

Historical reporting tells you what happened, but most teams lack the setup to forecast what comes next. Without prediction, planning rests on gut feel or stale trend lines.

How we help

Our data scientists build forecasting systems with data mining, machine learning, and statistical modeling. The models plug directly into your BI platform so predictions sit next to historical data in the dashboards teams already use, a quantitative base for forward-looking calls, not a separate tool nobody opens.

Batch processing delays insight by hours or days, so you can’t respond to shifting conditions in time. For operations that live on current data, stale dashboards are effectively useless.

How we help

We architect real-time BI on streaming platforms such as Kafka, incremental refresh, and low-latency query tuning. The systems ingest high-velocity data from IoT devices, transactions, and operational databases, letting operations teams watch conditions unfold and act on patterns before they turn into problems.

Static reports emailed around drive no engagement and leave no room to explore follow-up questions. When every new request runs through an analyst queue, backlogs grow and decisions slow.

How we help

We build the full range of visualisations, from the everyday (bar, line, and pie charts, tables) to the analytical (heat maps, scatter and bubble charts, box plots) to the complex (Sankey and network diagrams, choropleth and geospatial maps, treemaps, Gantt and radial charts, 3D). The skill isn't drawing the chart, it's choosing the right one for the question, and building the harder ones well when a standard tool can't. Tools: Power BI, Tableau, Looker, and custom visualisation (React, D3) for anything a standard tool can't render.

Teams running several BI and data systems end up with duplicated work, clashing metric definitions, and disconnected views of the business. As tools and sources accumulate, reporting gets harder to standardize and trust.

How we help

We connect BI platforms with CRM, ERP, marketing automation, and data lakes through APIs, database connections, and middleware. We also standardize data definitions and reduce reporting fragmentation, so your teams work from a more consistent view of the business.

Legacy BI gets harder to maintain as data grows, expectations change, and old tech falls behind. Many teams stay stuck because modernization feels risky next to live reporting.

How we help

We modernize legacy BI by updating reports, pipelines, data models, and platform pieces while preserving critical reporting continuity, cloud migration, report conversion, and incremental modernization of existing assets. The environment becomes easier to maintain without losing the reporting knowledge baked into current systems.

BI we've shipped

View all case studies

The stack we build with

We pick visualisation tools by your requirements, ecosystem fit, and licensing, standing up role-based access, embedded analytics, and governed self-service reporting at enterprise scale.

Tableau
Power BI
Looker
Superset

We choose warehouse platforms by query workload, existing cloud footprint, and total cost of ownership, weighing the trade-offs in concurrency, storage pricing, and ecosystem fit.

Snowflake
Redshift
BigQuery
Azure Synapse

We work across the major orchestration and integration tools, handling scheduling, dependency management, and error recovery across batch and streaming workloads.

Airflow
dbt
Fivetran
AWS Glue

We build semantic layers and modelling frameworks that give business users consistent definitions without needing to know the underlying schemas.

dbt
LookML
Cube
AtScale

Our data scientists span statistical environments from exploratory analysis to production, integrating with your existing analytics infrastructure.

Python
R
Spark MLlib
scikit-learn

Our engineers build and run streaming pipelines across major platforms, handling high-throughput ingestion, event-driven processing, and continuous dashboard refresh.

Kafka
Flink
Kinesis
Pub/Sub

We implement validation, lineage tracking, and access policies on the governance tools already in your environment, enforcing standards without new overhead.

Great Expectations
Collibra
Monte Carlo
Soda

Our architects work across the major clouds and lakehouse formats, operating within your standards and extending infrastructure as workloads grow.

AWS
Azure
Google Cloud
Delta Lake

Our business intelligence development process

Eleven steps, run in order, step through the sequence from requirements and metrics to adoption and ongoing support.

01

Requirements & metrics

We work with stakeholders to pin down reporting needs, key metrics, and data sources, turning business objectives into the BI specs that steer architecture and build.

02

Source audit & mapping

Our architects audit existing sources, gauge data quality, find integration points, and document lineage, surfacing gaps, redundancies, and openings to consolidate reporting.

03

Architecture & platform pick

We design scalable BI architecture that balances performance, cost, and maintainability, choosing platforms against your infrastructure, licensing, and scaling needs.

04

Warehouse modeling

We build dimensional models, define fact and dimension tables, and set strategies tuned for query performance, solid modelling that heads off rework and keeps reporting consistent.

05

Pipeline build

Our engineers build automated pipelines that extract from source systems, transform with business rules, and load into the warehouse, each with error handling, logging, and quality checks.

06

Data quality controls

We set validation rules, cleansing processes, quality dashboards, and anomaly alerts, so the analytics teams lean on stay trustworthy enough for confident decisions.

07

Dashboards & reports

We design clear dashboards with the right chart types and interactive filters, balancing polish against analytical depth so users can explore the data on their own.

08

Semantic layer

We build semantic layers that simplify complex models and set consistent business definitions, letting users work in familiar terms without knowing the schemas underneath.

09

Security & access

We apply role-based permissions, row-level security, and data masking, so users see only what their role allows while governance holds.

10

Performance tuning

We profile queries, add aggregations and caching, refine models, and tune database configs, keeping dashboards responsive enough that people actually use them.

11

Adoption & ongoing support

We train report creators and business users, then watch usage, resolve issues, add sources, and evolve the platform as priorities shift after launch.

BI experts, AI-augmented

These are the AI coding tools our engineers use to ship faster and keep code clean, distinct from the AI systems we design and build for you.

Claude CodeGitHub CopilotCodexCursorReplitGeminiOllamaWindsurf

We use these tools inside strict guardrails, every line is reviewed by a person. See how we build →

1

Senior BI engineers

Engineers with real, hands-on bi experience who take ownership of the work, not juniors learning on your budget.

2

Production-grade delivery

We take work from prototype to production, with testing, monitoring, and clean handover, not demos that stall after the pitch.

3

Security & compliance

Safeguards from day one. We build to and align with the standards regulated industries expect, including HIPAA, SOC 2, and ISO 27001.

We've delivered BI across healthcare, fintech, proptech, logistics, and more.

See how we approach your industry
Engagement

How you'd work with us on BI

Pick the level of ownership that suits you. We shape the engagement around your goals.

1

Staff augmentation

Add senior BI engineers to a team you already have.

2

Dedicated team

A committed BI team that runs like your own.

3

Full delivery

Hand over the build and we deliver it end to end.

Explore engagement models

BI FAQ

Buried in reports nobody trusts?

Bring us the fragmented data, the manual reporting, the dashboard nobody opens. We’ll tell you honestly what it takes to fix it.

Book a discovery call