RAG and AI agent platforms
Retrieval systems that answer from your documents, built to run multi-tenant in production.
More on this RAG and AI agent platformsAvailable for new engagements
We build the backend and AI systems your product runs on
Twenty years of industry experience building distributed systems in Java, Python, Go and Node.js: payment infrastructure sustaining 10,000 transactions per second, and multi-tenant RAG platforms running in production for regulated industries. You work directly with the engineers writing the code.
Services
What we build
Five things we have shipped repeatedly and can defend in a technical conversation. If your problem is outside this list we will say so.
High-throughput payment and transaction systems
Payment and order infrastructure that stays correct under concurrency and load.
More on this High-throughput payment and transaction systemsEvent-driven backends and microservices
APIs and services in Java, Python, Go or Node.js, designed to be handed over, not held hostage.
More on this Event-driven backends and microservicesData and analytics engineering
Pipelines, time-series stores and the query layer that makes them useful.
More on this Data and analytics engineeringCloud infrastructure and delivery
AWS and GCP infrastructure as code, with the CI/CD and monitoring to run it.
More on this Cloud infrastructure and deliveryWork
Selected work
Retrieval and AI platforms, and systems built to hold up under load: payment infrastructure at 10,000 transactions per second, ecommerce serving two million requests a day. Most of this was delivered for product companies in the US, UK, Europe and Asia, and we do not publish client names. Workout360 is our own product.
Atlas — Your company’s evergrowing knowledge, mapped
Atlas turns scattered documents, meeting notes, and transcripts into a connected map of the people, projects, and facts inside them. Ask a question in plain language and Atlas…
Read the case study Atlas — Your company’s evergrowing knowledge, mappedA multi-tenant RAG platform for document-heavy enterprise workflows
Four microservices powering retrieval, generation, configuration and memory as a knowledge agent inside a larger agentic system.
- 4 microservices in the platform
- 4 reranking strategies supported
A payment and order platform sustaining 10,000 transactions per second
Event-driven payment infrastructure on Java and Kafka, holding sub-50ms p99 latency under sustained load.
- 10,000/s transactions sustained
- <50ms p99 latency
How we work
No black box, no surprises
The same four steps on every engagement, whether you are two timezones away or twelve.
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01
Technical call
Forty-five minutes with the engineer who would lead the build. If we are the wrong fit we tell you on this call rather than after a proposal.
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02
Written scope
Fixed deliverables, a delivery date and a price. Agreed before any code is written.
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03
Build in your repo
Work happens on your infrastructure, in your repository, with a weekly demo. You can read every commit as it lands.
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04
Handover
Documentation, runbooks and a walkthrough. The system is yours to run without us.
Working together
What it is like to hire us from abroad
The practical questions, answered before you have to ask them.
Timezone overlap
Bengaluru and Udaipur, India (IST, UTC+5:30). We have worked with US and UK product teams for years: full overlap with UK and EU hours, morning overlap with US time zones.
Team
The engineers you will work with
You work directly with the engineers below, the same people who scope the work, write the code and hand it over.
Dilraj Vyas
Founder and Principal Engineer, Java and distributed systems
Twelve years building distributed backend systems in Java and Spring Boot, most recently payment and order infrastructure running at 10,000 transactions per second. Has led the engineering behind an ecommerce logistics and payments platform delivered across four countries, and works in event-driven architecture with Kafka, AWS and Kubernetes.
Bengaluru, India
Khushal Chouhan
Co-founder and Principal Engineer, Python, Go and AI systems
Twelve years across Node.js, Python, Go and Rust. Builds retrieval and agentic AI platforms with LangGraph, OpenSearch and vector search, and the data pipelines underneath them. Has delivered regulatory, legal, healthcare and IoT analytics platforms for product companies in the US and UK.
Udaipur, India
Writing
Notes from the build
What we learned shipping these systems, written for the engineers who have to maintain them.
What breaks when you put RAG into production
Nine things we changed taking a retrieval platform from a working demo to something real users depend on, starting with the evaluation set almost everyone skips.
Read What breaks when you put RAG into productionTell us what you are trying to build
Describe the system and the constraint you have hit. You will get a technical reply, not a sales sequence.