Connect your CRM, ERP, storefront and internal tools with reliable, event-driven integrations, so data stops moving by hand.
The problem
Orders, customers and invoices are re-keyed between systems. Data drifts, errors multiply, and AI projects stall because nothing is connected.
How it works
Systems kept in sync automatically, with retries and an audit trail.
- MapWe map which system owns which data and how it should flow.
- DesignWe design event-driven flows with clear ownership and error handling.
- BuildWe build integrations with retries, idempotency and logging.
- MonitorFailures alert the right person with the context to fix them.
Where people stay in control
- Each record has one system of truth
- Failed syncs are visible, not silent
- Changes are versioned
What it connects to
How we deliver crm and erp integration
The same method as every Software Engineering engagement: each stage ends with a decision you sign off. We work with teams in Bengaluru, across India and abroad.
We study the problem with the people who live it: workflow, customers, constraints.
Problem brief agreedWe agree what success means, what is in scope and the hypothesis we are testing.
Scope signed offFlows, interfaces and architecture, tested as a prototype before engineering starts.
Prototype approvedWorking software and artefacts, demonstrated every week.
Features acceptedRelease to real users with documentation, monitoring and a runbook.
Release acceptedWe measure what happened and turn it into the next roadmap.
Roadmap reviewedRelated insights
- Forward deployed engineering, explainedWhat a forward deployed engineer does, why the role matters for AI implementation, and how it differs from consulting, outsourced development and on-site support.
- Build or buy? Deciding on a custom AI agentWhen an off-the-shelf AI tool is enough, when a custom AI agent is worth building, the questions that decide it, and the middle path most good systems end up taking.
Why integrate systems before adding AI?+
AI needs reliable access to current data. Integration is often the highest-value first step, and it makes every later AI feature safer and simpler.
Related use cases
Legacy software modernization
Replace ageing systems step by step while the business keeps running.