Enterprise integration · AI first delivery
We integrate the platforms, data and channels an enterprise already runs, then build real-time search, reporting, customer interaction, promotions and pricing on top. We deliver AI first, and the engineers who build it run it 24x7.
Engineering team in Ahmedabad, India, working across Asian, Australian and European business hours. We do not have an office in Australia or New Zealand.
Each of these is work we have delivered. The tools listed are named in the linked write-up.
Customers and staff cannot find what they need across products, accounts and history held in different systems.
One search index fed by change events from every source, so results are current and scoped to who is asking.
Reports are assembled overnight from several systems, so every decision runs on yesterday.
Events streamed from each system into a real-time analytics store, combined into one live view of money, exposure and activity.
Something changes for a customer and nobody acts until the customer complains.
Triggers that fire on live events and drive the next step: a message, a ticket with the customer attached, or a change in what the customer sees.
Feedback arrives through forms, calls, complaints and social channels, and nobody can see the trend until it is a headline.
Text from every channel classified for sentiment and topic, mapped to where it came from, with alerts on sudden shifts.
Promotions run on timers and batch jobs, so offers land late, overlap or quietly build liability.
Offers issued and withdrawn on live events, with eligibility, limits and liability checked at the moment of the offer.
Revenue, cost and risk sit in different systems, so the true margin of a product or customer is a spreadsheet exercise.
Systems consolidated onto one platform with one console, so cost and live position are read in one place instead of reconciled.
Prices and offers are set by habit while input costs and demand move every week.
Forecasting and mathematical optimisation that recommend the price or offer with the best margin, with the reasoning shown.
Every new brand, region or customer means another stack to build, patch and watch.
Containerised platforms on Kubernetes, new tenants onboarded from a template in minutes, and monitoring the on-call engineers actually use.
Our engineers use AI at every stage of delivery: reading and mapping an existing system, writing and reviewing code, generating tests, checking releases and watching production. That is how a senior team takes on a large amount of integration work and gets it into production quickly.
What it does not mean: unreviewed code in your systems, or a model making decisions nobody can explain. An engineer owns every change that ships, and every automated action leaves a record.
Why AI output needs an approval pathEverything we integrate publishes events, keeps versioned data and exposes clean APIs. That is what lets you add forecasting, classification, optimisation or AI agents later without rebuilding the integration underneath.
Models we put into production are trained on point in time data, promoted only when they beat the current one, and monitored for drift.
How we keep production models rightLedgers, billing and finance systems, connected through their published APIs and file interfaces.
Customer records, consent and history, matched into one view of each customer.
Payment gateways and wallets, with idempotent requests and reconciliation.
Identity verification (KYC), single sign on and audit trails.
Exchange APIs, data vendors and partner feeds, normalised into one model.
Databases, file drops and batch jobs that everything depends on and nobody wants to touch.
We work from each system's published interfaces and your constraints, and we design every integration for timeouts, duplicates and replays, not just the good day. We do not claim a partnership or certification with any software vendor.
Typical stack: Core Java and Spring Boot, Node.js, Python, Kafka, Kubernetes, MySQL, MongoDB, Cassandra and Elasticsearch, with Prometheus and Grafana for monitoring.
01
We map your systems, where data and decisions get stuck, and which capability above pays back first. You get a written plan with the first piece to build.
02
One workflow end to end, on your data, with monitoring from day one. The systems you run today keep running alongside it.
03
The same team runs it 24x7 and adds the next capability. Modernisation happens one piece at a time, without a rip and replace.
Which systems you run, what has to happen in real time, and where decisions or data get stuck today. A list is plenty; a specification is optional.
Your enquiry goes directly to Kartik Modi, our Managing Director, and an engineer replies by email.
