Engineering-led · Vadodara, India
Dot Logic India designs, builds and operates database-driven business systems — multi-tenant ERP, backend and data engineering, reporting and workflow automation. One engineer accountable end to end, from schema design through production support.
Who we are
Clients work directly with the engineer who designs the schema, writes the queries, ships the release and answers the phone when production misbehaves. There is no account layer between the brief and the build.
The practice is built on roughly nine years spanning IT infrastructure support, database engineering, enterprise application development, security engineering and technology operations — including sustained work on production examination and digital-evaluation platforms serving multi-campus universities, where database architecture, high-volume ETL, enterprise reporting and application security had to hold up under live exam-cycle conditions.
That experience is the reason our work starts at the data layer rather than the interface. Most systems that fail in production do not fail because the screens were wrong; they fail because the model, the transaction boundaries or the reconciliation logic were never made explicit.
Dot Logic India applies that discipline to its own products and to client engagements: define the business rules precisely, model them in the database, put the tests around them, then build the interface as a wrapper over logic that is already correct.
Capabilities
Multi-tenant business platforms and bespoke line-of-business applications. Two-level tenant → organisation modelling so a single client can run multiple sites or legal entities under one account.
Schema design for high-volume transactional and reporting workloads, execution-plan-driven performance tuning, index strategy, and data-integrity assurance across schema migrations.
REST services, business-rule layers and integration work across modern and legacy stacks — including .NET estates that need to keep running while new capability is added around them.
Turning recurring manual work — reconciliation, result calculation, operational reporting, anomaly detection — into scheduled, auditable services with outputs your team already knows how to read.
Authentication and authorisation design, RBAC and claims-based models, JWT and refresh-token lifecycles, two-factor authentication, audit logging, and OWASP-based application review as an ongoing activity.
On-premise and hybrid deployment, server and database configuration, release coordination, and hands-on production troubleshooting under real operational deadlines.
Product · DOTERP
Ten modules — people, operations, finance and platform — on a shared multi-tenant schema. One client, many sites or legal entities, one set of books. Configure the dashboard the way your team actually works.
Quality & testing
We say "end-to-end tested" and then have to show our working. This is the working — a validation and release discipline drawn from production practice, not a marketing paragraph.
Queries and stored procedures are read through their execution plans before they ship. Implicit conversions, table scans and lock contention get found at design time rather than in the middle of a busy cycle.
Reporting and calculation changes are checked against stakeholder expectations — and against ground-truth data where it exists — before deployment, not after a discrepancy is reported.
Releases are planned around live operational cycles. Changes have gone into production during active examination periods without interrupting them; the same care applies to payroll runs, month-end and audit windows.
Migrations are dependency-mapped before they run: indexes, views, procedures and constraints identified, compatibility assessed, change planned, then validated against row counts and business totals.
Where a process produces numbers someone must trust, we build the check that flags the outlier automatically instead of relying on a person to notice it.
OWASP-based review, least-privilege design and audit logging are treated as continuing obligations across the life of the system.
When something breaks in a live system, the sequence is fixed. It is the pattern that resolved recurring reporting discrepancies during active evaluation cycles, and it is the pattern we hold ourselves to.
Establish the fault against real data, not a description of it.
Follow the request through interface, API, procedure and query to the source.
Correct joins, indexes and access paths where the cost is structural.
Fix the business logic itself, at the layer where the rule belongs.
Confirm the output with the stakeholders who depend on the number.
Ship without disrupting work already in progress. Keep the rollback path.
Evidence
Delivered by our principal engineer in prior enterprise roles. Presented as evidence of engineering capability, not as a guaranteed service level.
How we work
We use LLM tooling deliberately — for first drafts, debugging, architecture exploration, documentation, test-case generation and code review. Every engineering decision, every line that reaches production, and all testing and deployment remain a named human responsibility.
Selected work
First client: a mining and heavy-civil infrastructure contractor
A heavy-civil and mining contractor operating across multiple sites needed one system for people, procurement, stock and project accounting — with each site able to run its own operation without fragmenting the data.
Read the engagementHigher education · multi-campus
High-stakes examination processing at institutional scale, where a calculation error or an hour of downtime during a live cycle is not recoverable.
Read the engagementDescribe what it has to do and where it currently breaks. You will get a reply from the engineer who would do the work.