Modernizing a legacy system without stopping the business
Software engineering from New Delhi, for teams in India and abroad
Most reporting problems are data problems: the same number calculated three ways, reports assembled by hand, dashboards nobody trusts. We build the pipelines, models and dashboards that turn operational data into consistent reporting — and fix the source systems when that's where the problem really is.
Role-specific dashboards embedded in the systems people already use.
Agreed definitions for key figures, implemented once.
Scheduled extraction and transformation from operational systems.
A reporting database separate from production workloads.
CSV, PDF and email reports on a schedule.
Validation and reconciliation checks that flag inconsistencies.
One reliable source for the numbers your team decides on.
01
Business intelligence dashboards built on agreed metric definitions.
02
A single view of sales, operations and finance for leadership.
03
Live status for teams who act on data during the day.
04
Scheduled extraction and transformation from your systems.
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A reporting database separate from production workloads.
06
PDF, Excel and email reports delivered on schedule.
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Charts and reports inside your own product or portal.
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Validation that flags missing or inconsistent records.
Reports rebuilt by hand every week.
Different teams reporting different figures.
Heavy queries running against the live database.
Each location reports separately.
Recognise your situation here?
Talk to an engineerEach key figure defined and agreed before a chart is built.
Data problems fixed at the source where possible.
New reports checked against known figures before rollout.
A data dictionary your team can maintain.
Reporting runs on replicas or a warehouse, not on production.
Pipelines process changes rather than full reloads.
Sensitive figures restricted by role.
Every figure traceable to its source.
01 · Discover
Workshops with the people who run the process today. We map how work actually moves, where it stalls and what the system must never get wrong.
02 · Define
A written scope: users and roles, core workflows, integrations, non-functional requirements and a release plan you can hold us to.
03 · Architect
Data model, service boundaries, hosting, security model and the trade-offs behind each choice — reviewed with your team before code starts.
04 · Build
Short sprints with a working demo every week. Code review on every change, automated tests on the paths that carry money or data.
05 · Validate
Functional QA, role-by-role acceptance, performance checks and a security pass before anything reaches production users.
06 · Scale
Staged rollout, monitoring and a support window. Then the backlog of improvements that only real usage reveals.
Sales and inventory CRM for a stone distributor
Membership, billing and check-in platform
School ERP with web and mobile apps
Not always. Many businesses start with a read replica and well-designed reports. A warehouse makes sense when data comes from several systems or volumes grow.
Yes. We often begin by importing spreadsheet data and then move collection into proper systems.
We build dashboards into your applications with React, or connect established BI tools, depending on who uses them.
By defining each metric once in the data model and building every report on that definition.
They cover collecting data from your systems, cleaning and modelling it, and presenting it as dashboards and reports people can act on.
BI tools suit internal analysts exploring data. Custom dashboards suit fixed operational views inside your own applications or for customers. We recommend based on who will use them.
Yes. Pipelines can pull from spreadsheets, accounting exports and application databases into one reporting model.
From near real time to daily refreshes, depending on the source systems and what decisions the data supports.
Tell us what the system needs to do. We'll reply within 24 hours with questions, not a sales script.
