Software that goes into production and stays there.
Internal tools, integrations, reporting and analytics layers, web and mobile applications, and AI systems over private data.
Most of what we build sits around systems a company already runs: the integrations into them, the reporting out of them, and the tools between them and the people using them every day. We have built a cloud native ERP of our own, so we know what an ERP is and what it is not for.
01Selected work
02Before the paperwork
If you would rather see the work before the paperwork, give us a small piece of it on sample or invented data. You judge what comes back, and if it is not good enough that is the end of it.
Try us first
Sample or invented data. No access to your systems, no NDA, no cost.
Partners
Test us on a real task from a live project instead, with the deadline you'd give anyone else.
03Who leads the work
More than ten years building and running production software for US organisations. He scopes every engagement, owns the architecture and is the escalation point throughout. The day to day work is done by a named senior engineer, who stays on it.
- Healthcare under HIPAA and FHIR. Architected compliant microfrontends and embeddable widgets used across multiple healthcare organisations, and built a speech to text and generative AI pipeline that extracted structured patient data and persisted it in FHIR format. (WellSky, through Nitor Infotech)
- US platform at scale. Owned site wide performance, caching and rendering architecture, and led a Next.js App Router migration on a high traffic US financial media platform. (Benzinga)
- Production agentic AI. Multi agent orchestration with LangGraph and MCP, hybrid search with cross encoder re ranking, Self RAG and Corrective RAG, and GraphRAG, shipped end to end. (getodin.ai)
- Cloud and infrastructure. Serverless microservices on AWS Lambda, DynamoDB and ElasticSearch, GraphQL APIs, and CI and CD pipelines across teams.
04How we use AI in delivery
We use AI assisted development across the team, and we are specific about where it helps and where it does not.
- It carries the routine work. Scaffolding, test generation, refactors, framework migrations and documentation, so senior time goes to design, data modelling and the edge cases that actually decide whether something works.
- A named engineer owns every change. Nothing merges without a human who reviewed it and is accountable for it. AI writes drafts, it does not approve them.
- The gates stay the same. Pull request review, unit and end to end tests on every change, and dependency and vulnerability scanning before release.
- We also build this kind of system for clients, so the same evaluation discipline applies to our own use of it.
05Technology
06How we work
07Working with US and UK teams
With the UK we overlap on the normal working day. Ahmedabad is four and a half hours ahead of London in summer, five and a half in winter, so most of your day is our day. No shifting needed for standups, reviews or escalations.
With US Eastern we shift hours to hold a real overlap window every day, covering your morning for standups, reviews and escalations.
We work under your NDA and your access model. Named individuals, least access needed, no subcontracting.
08Company
If something here is close to what you need, write to pratik.soni@rankbit.tech.
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