Six practices that we run as one delivery team. Bring us a whole product or the single piece that is stuck — both are normal.
01 / 06
AI & Automation
AI features that answer from your own data, with evaluation and guardrails attached from day one.
The ".AI" in our name is not decoration. We build retrieval pipelines, assistants, document extraction and workflow automation grounded in your systems rather than a generic model. We scope the narrow, high-value use case first, measure it against a real evaluation set, then widen it.
Retrieval-augmented assistants over your own data
Document parsing and extraction pipelines
n8n workflow automation across your existing tools
WhatsApp and conversational assistants that hand off cleanly
Model evaluation harnesses and guardrails
Vector search and embedding infrastructure
02 / 06
Cloud & DevOps
Infrastructure that is written down, repeatable and cheap to run — not clicked together in a console and forgotten.
We design and operate cloud platforms on AWS and Azure: network topology, container orchestration, delivery pipelines, observability and the cost discipline that keeps the bill honest. Everything ships as infrastructure-as-code, so what runs in production is exactly what is in the repository.
AWS / Azure architecture and migration
Terraform & CloudFormation infrastructure-as-code
ECS, EKS and Kubernetes container platforms
CI/CD pipelines with real rollback paths
Monitoring, alerting and incident runbooks
Cloud cost audits and right-sizing
03 / 06
Software Engineering
Backends and APIs built to survive the second year — typed, tested, instrumented and documented.
Distributed services, real-time systems, domain models, integrations and the unglamorous plumbing that decides whether a product scales. We work in .NET, Node.js, Python and Go, and we leave behind a codebase your own engineers can pick up without a handover call.
REST, GraphQL and WebSocket API design
Real-time and event-driven systems at scale
Third-party and payment integrations
Legacy modernisation and monolith splits
Automated test suites and CI gates
Performance profiling and query tuning
04 / 06
Web & Mobile
Interfaces that load fast on a mid-range phone on a weak connection — because that is where your users are.
Marketing sites, dashboards, admin panels, portals and cross-platform mobile apps. We build with React, TypeScript and React Native on top of a real design system, and we treat Core Web Vitals and accessibility as build requirements rather than a later clean-up.
React and TypeScript web applications
React Native iOS and Android apps
Design systems and component libraries
Core Web Vitals and bundle budgets
WCAG-minded accessible interfaces
Headless CMS and content pipelines
05 / 06
Data & Analytics
One version of the numbers, refreshed on a schedule, that the whole company can point at.
Ingestion, warehousing, modelling and reporting. We wire your product, billing and operational sources into a warehouse, model them into metrics people actually agree on, and put dashboards in front of the teams who need them.
ETL and streaming ingestion pipelines
Warehouse design and dimensional modelling
Executive and operational dashboards
Event tracking and product analytics
Data quality checks and alerting
Reporting automation and scheduled exports
06 / 06
Product Design
Design that begins with the workflow and the constraints, not with a colour palette.
Research, information architecture, interaction design and a component library that engineering can build against directly. We work in Figma and hand over files your developers can actually read — every screen with its empty, loading and error states.
Brand identity and visual systems
Figma UI design and interactive prototypes
Information architecture and user flows
Design tokens and component libraries
Design-to-code handover with engineering
Usability testing and iteration rounds
Tooling
The stack we reach for by default.
We are not religious about any of it. If your team already runs something well, we work in that instead of rewriting it to suit us.
AWS
Azure
Kubernetes
Terraform
Docker
React
TypeScript
.NET
Node.js
Python
PostgreSQL
MongoDB
Redis
WebSockets
GitHub Actions
Grafana
OpenAI
LangChain
n8n
WhatsApp Business API
React Native
Figma
Engagement
Three ways to work with us.
Project
Best for: a defined thing that has to exist by a date.
Fixed scope, fixed price, a written plan and a delivery date agreed up front. Changes are priced as they come rather than absorbed silently.
From 4 weeks
Embedded team
Best for: an in-house team that needs more hands or a missing skill.
Our engineers join your stand-ups, your board and your repository, and work to your process. You get senior people without a hiring cycle.
Monthly, rolling
Managed platform
Best for: something already live that needs to stay that way.
We take on the infrastructure, the pipelines, the monitoring and the on-call, with an agreed response time and a monthly report you can read.
Retainer, 24/7
Delivery
What the first month looks like.
01
Discover
We start with your constraints, not our template. Existing systems, the team, the deadline, the budget and the thing that actually hurts. You get a written scope with a fixed price before anyone writes code.
Week 1
02
Architect
Data model, service boundaries, infrastructure diagram and delivery plan — reviewed with you and your engineers. Decisions get written down with their trade-offs so they can be revisited later on purpose.
Week 1–2
03
Build
Two-week increments, each ending on a real deployed environment you can click through. Nothing is demoed from a laptop. You see progress weekly and can change direction at any increment boundary.
Week 2 onward
04
Operate
Monitoring, alerting, runbooks and a documented handover — or we keep running it for you. Either way you own the code, the accounts and the keys from the first commit.
Ongoing
Questions
What people ask before they sign.
The same answers we give on a first call. If yours is not here, ask it directly — a person reads every enquiry and replies within one business day.
What does an AI automation company actually do?
It finds the work in your business that is repetitive, rule-shaped and expensive in staff hours, and moves it onto systems that run it — reading documents, triaging requests, drafting replies, reconciling records, scoring events. The engineering is the easy half. The valuable half is picking the one workflow where automation pays for itself first, and building the evaluation that proves it did.
How much does custom AI automation cost?
We do not quote before discovery, because a number given before anyone has seen your systems is a guess. Week one produces a written scope with a fixed price attached, and you are free to walk away with it. As a frame: the budget bands most engagements fall into run from under Rs 5L for a single scoped automation to Rs 40L+ for a full platform build.
How long before we see something working?
The first deployed increment lands inside four weeks on a typical engagement. We work in two-week increments, and each one ends on a real environment you can click through — nothing is demoed from a laptop. You can change direction at any increment boundary.
Should we use RAG or fine-tune a model?
For most business use cases, retrieval. RAG grounds answers in your own documents and data, updates the moment the source does, and lets you cite where an answer came from. Fine-tuning earns its cost when you need a consistent format or tone at volume, or a narrow classification task — not when you need the model to know your facts. We will tell you which one your problem is, including when the answer is neither.
What happens when the AI gets something wrong?
It is designed to. Every system we build has a confidence threshold, an escalation path to a person, and a log of what it did that can be reversed. We build an evaluation set from your real cases before rollout, run it in CI on every prompt change, and measure the system against your existing manual baseline rather than against a demo.
Will our data be used to train a model?
No. We work inside your cloud accounts and your data stays in them. Where a third-party model provider is involved we use the enterprise endpoints that contractually exclude your inputs from training, and we tell you exactly which provider sees what before anything is wired up.
Do we own the code and the accounts?
Yes, from the first commit. Your repositories, your cloud accounts, your domains, your keys — we work inside your organisation rather than ours. There is no lock-in to unwind if you take the work in-house or hand it to another team.
Do you work with companies outside India?
Yes. We are based in Jodhpur, Rajasthan and most of our work is remote, with teams across India, the Gulf, Europe and North America. We keep a real overlap window with your working day rather than leaving replies overnight, and we reply to every enquiry within one business day.
Not sure which of these you need?
Describe the problem in plain language. We will tell you which practice it belongs to — and if it is not one of ours, we will say so.