⚡ 0 → 1 · Production-Grade · 30 Days

Your MVP.
Built like it already
has a million users.

I'm Kushal — 13+ years building and scaling production AI systems, including a platform processing 2M+ events a day for a 500K-device global IoT fleet and a HIPAA-compliant AI system serving 5,000+ daily clinical sessions. I bring that same architecture, discipline, and speed to your MVP — live in 30 days, with real integrations, real infrastructure, and zero rebuild waiting for you at scale.

Figma-to-code template Mock data & "demo-only" auth Throwaway prototype → Real, scalable, shippable in 30 days
13+
Years shipping production systems
2M+
Events/images processed per day, in production
500K
Devices on one IoT fleet architected end-to-end
€2M/yr
Infrastructure savings delivered (3x throughput)
5K+
Daily clinical sessions on a HIPAA-compliant AI system
50K+
Concurrent users served on a platform I architected

Tell me about
your idea.

No page hop, no ten-field form — just the basics. I'll reply personally within a day.

Thanks — I'll get back to you within a day. Meanwhile, feel free to check pricing or see case studies.

Most MVPs get
rebuilt. Yours won't.

Agencies and freelancers ship demos — mock auth, dummy data, a "coming soon" API, no path past 100 users. I've spent 13+ years on the other side: owning production systems after the demo, when they meet real traffic, real regulators, and real incidents. I build your MVP the way I'd want to have inherited it.

🏗️

Enterprise architecture, startup speed

The same patterns that carried a 2M+ image/day platform to production — applied to your MVP from day one, not bolted on after you raise a round.

🔌

Real integrations, not stubs

Payments, auth, LLM providers, third-party APIs — wired up and working on launch day, because "we'll connect it later" is how MVPs die in review.

📈

Built to scale without a rewrite

Stateless services, queues, caching, and autoscaling from commit one — the architecture that took a platform from 0 to 500K devices, sized down to your MVP.

🔒

Security & compliance from day one

STRIDE threat modeling, secrets management, and privacy-by-design — the same discipline used to ship HIPAA-compliant and NIS2-aligned systems.

🧠

Diagnose before you build

Every build starts with root-cause thinking, not a backlog. I've publicly broken down why entire industries fail to digitize — that same rigor gets applied to your scope first.

🔑

You own everything

Your cloud account, your repo, your keys. No vendor lock-in, no dependency on me to keep the lights on after handover.

30 days.
Four phases.
One shippable product.

A fixed-scope sprint, not an open-ended engagement. Scope locks after week one so there's no drift — and no surprise invoice at the end.

Days 1–5
Architecture & Scope
Lock the core user journey, data model, integration list, and success metrics. No scope creep after this.
Days 6–20
Build & Integrate
Real backend, real frontend, real integrations — built in parallel, demoed weekly, tested continuously.
Days 21–27
Scale-Test & Harden
Load testing, caching tuned, monitoring wired in, security review, edge cases closed out.
Days 28–30
Ship & Handover
Live on real cloud infrastructure, in your accounts, with documentation — you own the keys, not me.

Two kinds of proof.
Both before I
write a line for you.

What I've shipped at scale for employers, and how I think before any code gets written — a habit I apply to every client engagement, starting with yours.

// Track Record

Professional Experience

Before KushalBuilds, I was the engineer these companies trusted to take their AI platforms from first architecture diagram to production — and to keep them running under real load.

📷
AI Platform · IoT · Vision
2M+ images/day
500K device fleet
€2M/yr saved

Confidential · Global Optics & Imaging Enterprise

AI Vision Platform

Engineering Manager / AI Platform Lead

Built the engineering function from zero and architected the end-to-end AI pipeline — ingestion, preprocessing, deep-learning inference, metadata, API — processing 2M+ images/day from a 500K-device global IoT fleet on Azure ML and Kubernetes. Shipped a GenAI capability (Azure OpenAI, GPT-4) for natural-language image search and AI-generated observation summaries.

3x throughput and €2M/year infrastructure savings via TensorRT acceleration and dynamic batching
60% MTTR reduction — stood up observability (OpenTelemetry, Grafana SLOs) from zero
Zero message loss at 2M+ events/day via an idempotent, backpressure-aware event backbone
🩺
Healthcare AI · RAG · HIPAA
5K+ daily sessions
~€5M ARR impact
30+ microservices

Confidential · US Healthcare Product

Clinical AI Platform

Technical Lead, AI & Backend Platform

Owned architecture and delivery of a real-time clinical AI pipeline — audio → Whisper transcription → NER enrichment → structured clinical notes — serving 5,000+ daily sessions for a US healthcare product. Built a HIPAA-compliant RAG system (LangChain + pgvector + Azure OpenAI) for natural-language querying of patient history.

30+ FastAPI microservices behind an API gateway with rate limiting, circuit breakers, distributed tracing
LLM evaluation harness + shadow-mode A/B testing to catch regressions before rollout
Fine-tuned domain medical NER (LoRA/PEFT) for an 18% F1 improvement; ~22% YoY ARR growth
📄
B2C SaaS · Acquisition · Scale
50K+ concurrent users
18% YoY revenue
15-person team

Confidential · B2C Career-Tools SaaS

Acquisition Integration & AI Resume Scoring

Lead Full-Stack & AI Engineer

Led an acquired brand's integration — migrating users and systems onto the parent platform and delivering end-to-end white-labelling across a high-ambiguity, multi-system cutover. Architected an AI resume-scoring engine (spaCy, BERT embeddings) for semantic matching and ATS scoring.

Platform served 50K+ concurrent EU users via Redis caching, CDN optimization, K8s autoscaling
Led a 15-person engineering team; introduced CI/CD and code-review standards driving ~18% YoY growth

// Diagnosis Before Code

Industry Systems Diagnoses

Before I write a line of code for any client, I diagnose the actual failure mode in the industry — not just the symptom. This is a growing series of public breakdowns of why entire industries lose money to fragmented, non-digitized systems. Construction is first; law and other regulated industries are next.

🧩
Construction Tech · Preconstruction
13% of global GDP
5 missing capabilities found

Why Preconstruction Fails — a diagnosis, not a pitch

Published systems analysis · Construction Tech

Before writing a line of code for any client, I diagnose the actual failure mode — not the symptom. In this piece, I broke down why construction (13% of global GDP, the least digitized major industry) keeps losing money in preconstruction: architects and contractors use the same documents in entirely different systems, and the intelligence one side discovers never travels back to the other. This is the same discovery process that opens every 30-day build.

Identified 5 capabilities missing across every vendor in a global, regulated market
Mapped regional strategies (Germany, USA, UK, China, Switzerland, India) to find the highest-value gap
Read the full breakdown on LinkedIn →

Transparent pricing.
No surprise invoices.

Fixed-scope, fixed-price builds — priced upfront on a free scoping call, not billed hourly. Ranges below are typical starting points; every engagement is scoped to your actual product before a number is finalized.

💱 Prices shown in EUR — auto-detected from your region.

Entry Point
Architecture Audit
Starting from
2,000

A fast technical due-diligence pass before you commit budget to a build.

Architecture & build-vs-buy review
Security & scalability risk assessment
Written report + prioritized roadmap
1 walkthrough call
Request an audit
After Launch
Scale & Harden
Starting from
3,000

For an MVP (mine or someone else's) that needs to survive real traffic and real regulators.

Load testing & performance tuning
Observability, SLO/SLI dashboards, incident playbooks
Autoscaling & caching tuned for real traffic
Compliance readiness (GDPR, HIPAA, NIS2)
Scope a hardening pass
Entry Point
Security & Reliability
Starting from
2,000

A focused pass on the part of your product that can't fail quietly — auth, secrets, and uptime. See the full security & compliance menu ↓ for deeper engagements.

STRIDE threat modeling & OWASP review
Secrets management & auth hardening
Observability & incident-response playbooks
Written findings + fix priority list
Book a security pass
Ongoing
Fractional AI Architect / CTO
Starting from
1,500/mo

Part-time, embedded technical leadership — for teams that need a Head of AI Engineering, not another contractor.

Architecture ownership & roadmap partnership
LLM/RAG platform design & MLOps
Code review, mentoring, hiring support
Scoped to hours/week, cancel anytime after month one
Start a conversation

Final price depends on scope — integration count, AI/LLM complexity, compliance requirements, and expected launch scale all move the number. You'll get an exact, fixed quote before any work starts, not an estimate that grows.

# of integrations AI/LLM complexity Compliance (GDPR/HIPAA/NIS2) Blockchain / Web3 Expected scale at launch Mobile vs. web

Security &
compliance,
menu-priced.

From urgent regulatory deadlines to AI governance to classic security engineering — priced individually so you know exactly what you're buying. Rates below are introductory, first-engagement pricing.

A
Compliance Readiness
Regulation-driven · Urgent
NIS2 scoping + gap assessment from 4,000
NIS2 implementation (policies, incident-reporting flow, supply-chain docs) from 10,000
ISO 27001 readiness (ISMS, SoA, policy pack, internal audit) from 15,000
GDPR gap assessment / DPIA / RoPA from 3,000
DORA readiness (fintech) from 10,000
SOC 2 readiness (US-facing SaaS) from 8,000
B
India Compliance
DPDP · CERT-In · RBI
DPDP Act 2023 readiness (India's data protection law) from 2,000
CERT-In incident-reporting compliance (6-hr reporting rule) from 1,500
RBI IT & cybersecurity framework readiness (NBFC / fintech) from 3,000
IT Act 2000 & SPDI Rules compliance review from 1,500
C
AI / LLM Security
Rare skill combo · Premium
AI system inventory + AI Act risk classification from 8,000
LLM app threat model (STRIDE + OWASP LLM Top 10) from 6,000
Prompt-injection / jailbreak red-team from 8,000
RAG / data-pipeline security review from 5,000
AI guardrail implementation from 10,000
AI governance framework (board-ready, AI Act-aligned) from 12,000
D
Classic Security Engineering
Bread & butter · Easy to scope
Threat modeling per system / feature from 3,000
Cloud security review (Azure / AWS) from 4,000
Secure SDLC / DevSecOps setup from 8,000
Security architecture review from 5,000
E
Recurring Engagements
Where trust compounds
vCISO retainer from 3,000/mo
Fractional DPO from 1,500/mo
Compliance monitoring + reporting subscription from 1,000/mo

These are introductory rates for a first engagement together — scope, timeline, and a fixed quote are confirmed on a discovery call. Bundle any of the above with an MVP build or Scale & Harden pass for a combined-engagement discount.

Questions,
answered.

Why 30 days — is that realistic for a "real" product?
Yes, because scope is locked in the first week and I'm not building generic infrastructure from scratch each time — I'm applying architecture patterns I've already run in production at far larger scale (2M+ events/day). The constraint is what keeps it real: one core user journey, done properly, beats five half-built features.
What tech stack do you use?
Typically Next.js/React or NestJS/FastAPI on the backend, Postgres or CosmosDB with Redis caching, deployed on Azure or AWS with Kubernetes and CI/CD. For AI features: LangChain/LangGraph, RAG with pgvector, and vLLM/TensorRT for inference — the same stack behind the case studies above. Stack is adapted to your team's existing skills if you're taking over post-launch.
Do I own the code, infrastructure, and IP?
100%. The build happens in your cloud accounts and your repository from day one — not mine. At handover you get full documentation and I walk your team (or you) through everything. No vendor lock-in.
What if my scope grows mid-build?
Scope locks after the Architecture & Scope phase (days 1–5). New requests get logged for a fast-follow phase after launch rather than derailing the 30-day timeline — this is exactly the discipline that keeps the price fixed.
I don't need a full MVP — can I just get an architecture review?
Yes — the Architecture Audit package exists for exactly that: a fast, independent technical read on what you're about to build or already have, before you commit real budget.

// Let's Build

Stop shipping demos.
Ship a product.

Book a free 30-minute scoping call. You'll leave with a scoped plan and a fixed price — whether or not you decide to build with me.

🚀 Book your free scoping call ← Back to KushalBuilds