01 / 04
WEBSITES / LANDING PAGES
Fast, indexable marketing sites built to convert. Under two seconds to first paint on a mid-range Android phone, because that is what most of your traffic is using.
HTML · SSR · ANALYTICS · CMS · SEO
SHIP4U — DEVELOPMENT STUDIO — INDIA
FROM IDEATO SHIPPEDPRODUCT.
We design, build and deploy production-grade web, mobile and AI products. Two engineers, the full lifecycle, no handoffs between agencies.
SCROLL TO BUILD
01CAPABILITIES
READY02 / 04
WEB APPLICATIONS
Full-stack products with real authentication, real data and real integrations. Frontend, backend, database, APIs. Built to survive actual users rather than a demo.
AUTH · DATABASE · API · PAYMENTS · ADMIN
03 / 04
MOBILE APPLICATIONS
Cross-platform apps with the backend that makes them work. Built, signed, submitted, and shipped to both stores.
IOS · ANDROID · PUSH · OFFLINE · STORE RELEASE
04 / 04
AI APPLICATIONS
Agents, RAG pipelines and LLM features that do something specific and useful. Evaluated against a test set, not judged by how the demo felt.
AGENTS · RAG · EVALS · TOOL USE · INTEGRATIONS
DEPLOYMENT & CLOUD
CI/CD, infrastructure, domains, SSL, monitoring. Set up once, correctly, so it stops being your problem.
MAINTENANCE & SUPPORT
Ongoing development, fixes and new features. We stay on after launch.
02SELECTED WORK
READYHearU
THE PROBLEM
- Most wellness apps treat the journal as a text box and the model as a demo.
- There was no confidential write-and-speak loop that could actually ship on a cluster.
WHAT WE BUILT
- A FastAPI backend and React journal, with a Gemini voice assistant for people who would rather talk than type.
- CI on GitHub Actions and a Kubernetes deploy on GCP, so the thing you open is the thing that runs.
STACK
FASTAPI · REACT · GEMINI · GITHUB ACTIONS · KUBERNETES · GCP
- 1
- VOICE ASSISTANT
- 1
- KUBERNETES CLUSTER
- 2
- SURFACES WEB AND VOICE
W-02Eidos
A self-healing RAG system that evaluates its own answers and rewrites the weak ones.
NEXT.JS · FASTAPI · LANGGRAPH · QDRANT · POSTGRES · R2 · AWS
2025
W-03Exovision
Custom model detects comets, planets, and stars and determines their positions based on their movement.
PYTHON · CUSTOM ML MODEL · ASTRONOMY
2025
Every product is a machine. We draw it before we build it.
FIG. 01 — SYSTEM GEOMETRY / ORTHOGRAPHIC / DRAG TO ORBIT
04PROCESS
READY01
DISCOVER
We work out what you are actually building and what it has to do on day one.
02
ARCHITECT
Data model, services, integrations, hosting. Decided before a line is written.
03
DESIGN
Interface and flows, designed against the real data, not against a mood board.
04
BUILD
Weekly deployed builds you can open. No three-week silences.
05
TEST
Real devices, real edge cases, real load. Fixes before launch, not after.
06
DEPLOY
Infrastructure, CI/CD, domains, SSL, monitoring. Handed over documented.
07
SCALE
Ongoing development as the product and the traffic grow.
05STACK
READYChosen for the products we build, not for the logos. Hover a node to see why it is there.
Chosen for the products we build, not for the logos. Tap a technology to see why it is there.
CLIENT
Next.js
Next.js — report jobs queue from Next.js APIs, admin dashboards fetch live data, and the Eidos UI ships on it.
React
React — product surfaces and internal dashboards. The same components talk to FastAPI and to Next.
TypeScript
TypeScript — every line we ship is typed. Catches the bugs that would otherwise hit a client's phone.
Python
Python — FastAPI, LangGraph, workers, and the Astro Engine. The language the AI libraries actually live in.
SERVER
Node.js
Node.js — Next.js API routes and Express services. One language with the client, so two people can own the request path.
Golang
Golang — services that have to stay small and concurrent. Chi when the API is Go; Python stays where the AI libraries are.
GraphQL
GraphQL — the in-house Astro Engine over FastAPI. Typed queries, no paid astrology provider in the loop.
FastAPI
FastAPI — Astro Engine, RAG backends, Eidos. We moved Flask here for async throughput and kept it.
DATA
PostgreSQL
PostgreSQL — relational because Eidos and most products have relationships. We will regret JSON columns in month four.
Redis
Redis — time-decayed affinity, short-term agent memory, job locks around the edges. Used for what it is good at.
MongoDB
MongoDB — report-job locking, structured user memory, CRM lead stores. Documents when the shape actually is a document.
AI
Gemini
Gemini — chat intent and the Eidos critic loop. Default when we need a fast, cheap generation pass.
OpenAI
OpenAI — ranking and chat intent alongside Gemini. Used where the evals say it wins, not by habit.
pgvector
pgvector — embeddings in the same database as the rows they describe. One backup, one query, no sync job.
LangGraph
LangGraph — orchestrator, workers, judge, retries. The TrustAstrology agents and the Eidos critic are graphs, not prompts.
INFRA
GCP
GCP — Pub/Sub into BigQuery, Cloud Run, GCE workers, GCS for 35+ report PDFs. Where the heavy async work runs.
AWS
AWS — VPC, ALB, ECS Fargate, EventBridge, Lambda, S3. Chosen when the job needs a box, a queue, or a cron.
Docker
Docker — the same container on a laptop, on ECS, and on the Eidos box behind Nginx. It ends 'works on my machine'.
Azure
Azure — when the client's estate is already there. Same boxes, queues and crons as AWS, different console.
Jenkins
Jenkins — Eidos deploys to a raw AWS host, Elastic IP, Nginx. GitHub Actions for the repos that do not need a box.
06PRICING
READYWHAT ARE YOUBUILDING?
STARTING PRICES. FINAL QUOTE DEPENDS ON SCOPE, INTEGRATIONSAND TIMELINE, AND IS FIXED IN WRITING BEFORE WORK BEGINS.ALL PRICES ARE ONWARDS.
07STUDIO
READYAt Ship4u, you work directly with seasoned engineers who design and ship your product end-to-end. You get clear communication, decisions in hours instead of weeks, and nothing is handed off without your knowledge. We take on a limited number of projects to ensure focus, and if a project is not the right fit, we will tell you honestly.
Laksh Krishna Sharma
AI ENGINEER · DEVOPS
I design the AI pipelines and the cloud they run on, and I keep them cheap enough to stay in production.
- OWNS
- Architecture, LLM pipelines, APIs, cloud infrastructure
- BACKGROUND
- AI Engineer at TrustAstrology.ai. Previously AI at Ant Creatives and full-stack at Venumonk. CS at MAIT, Data Science at IIT Madras.
- WRITES
- Python, TypeScript, FastAPI, LangGraph, PostgreSQL, Redis, AWS, GCP, Docker
Rupesh Singh Karki
AI ENGINEER · FULL STACK
I build the product end to end — agents, backends, and the interfaces people actually use.
- OWNS
- Multi-agent systems, full-stack product, data workflows
- BACKGROUND
- AI Engineer at TrustAstrology.ai. Previously full-stack at SociolinQ. CS at MAIT.
- WRITES
- Python, TypeScript, FastAPI, React, LangGraph, PostgreSQL, MongoDB, Redis, AWS
CURRENT AVAILABILITY — AVAILABLE NOW
08SHIP
READYLET'S SHIP IT.
Tell us what you are building. We will tell you honestly whether we are the right people to build it.
RECEIVED
WE READ EVERY ENQUIRY OURSELVES AND REPLY WITHIN TWO WORKING DAYS.