Kaushal Khodifad is the founder of CLOZOM, the professional network for India's healthcare professionals. He has spent eight years putting product into production, the last four of it AI, where compliance, audit trails, latency budgets and real users decide what actually ships. PGDABA, IIM Ahmedabad. CORe with High Honors, Harvard Business School Online. The record is at /work, the products at /products, and contact at /contact.
Kaushal Khodifad, Founder of CLOZOM
The model isthe easy part.Shipping it inside compliance, audit trails, latency budgets and real users is the hard part.
Eight years of exactly that. The industry changes; the hard part does not.
LinkedIn · 10K+ followersProduction outcomes by Kaushal Khodifad: at Infosys (Oct 2018 - Oct 2021) a credit-decisioning platform that cut loan defaults 70% and compressed loan processing from seven days to under 24 hours across three regulated Fortune 500 verticals under SOX and GDPR; at Dukaan (2022) ML carrier optimization saving $1.5M+ annualized across 5M+ merchants with a 10% RTO reduction; at OTPless (2023) a 60% lift in authentication success in eight weeks for a platform serving 30M+ end users; for a $200M+ manufacturer, an independent 90-day production AI project using ARIMA, GARCH and neural-network ensembles that improved forecast accuracy 40% and cut inventory carrying costs 25%; for a US commercial lending AI platform (Jul - Sep 2026), a founding product role as its only product person, building the product from zero across all six stages of the loan lifecycle; and CLOZOM, the professional network for India's healthcare professionals - built for professionals, not patients - which he founded in 2023 and has grown to 50,000+ registered healthcare professionals and 26,000+ healthcare jobs across India. Full record at /work.
- 50,000+Registered healthcare prosCLOZOM
- +60%Authentication successEnterprise SaaS platform
- $1.5M+Annualized savingsVenture-backed e-commerce
- 70%Fewer loan defaultsFortune 500 banking clients
- 25%Lower inventory carrying costs$200M+ manufacturer
Selected work by Kaushal Khodifad: JPMorgan Chase card data platform (Analytics & Data), Arbiter commercial lending adjudication (Fintech & Payments), Praxis agentic enterprise OS (Workflow & Automation), Arintra medical coding (Healthcare AI), Intuit FP&A agent (Fintech & Payments) and Finkraft GST recon (GRC & Compliance). These are independent concept studies built on public data: not client work, and not an engagement with or endorsement by any company named. Full set of 35 at /products.
What it looks like shipped.
35 products8 industriesevery one opens
Independent concept studies on public data. The company name anchors the domain, nothing more.
Teardowns, not takes.
Long-form on how AI actually gets shipped inside regulated industries. Every claim carries a primary source.
- Grounding is the easy half of autonomous medical coding - an Arintra teardownValidating every code against the actual CMS tables stops a model inventing codes, and that fight is largely won. It does not stop a real row from being the wrong answer, which is the failure mode nobody demos.12 Sep 2026 · 20 min
- How card-data entitlements actually work - an Atlas teardownAn entitlement that lives in application code is a claim about every code path that will ever exist. An entitlement that lives in the database is an artifact somebody else can read.12 Sep 2026 · 19 min
- Compliance evidence: automating the part auditors actually check - DPDP Rules 2025 teardownA regulator has already said it plainly: pointing at a correctly configured system is not proof that it was configured correctly on the day it mattered. Compliance tooling automates the configuring, and the proving is still a person with a folder of screenshots.12 Sep 2026 · 20 min
- How a lending decision gets warranted, not just made - a credit memo automation teardownMaking the number is the easy half. Warranting it, with reason codes a regulator accepts and a trace nobody can quietly edit, is the half that decides whether the system ships.12 Sep 2026 · 19 min
- What actually stops an agent is code it cannot reach - tearing down two agent prototypesEvery governance feature that lives inside the model's context window is advisory. The test for any agent control is one question: can the model change this outcome by saying something?12 Sep 2026 · 19 min
Contact Kaushal Khodifad by email at kaushal@kaushalkhodifad.com or via LinkedIn. Based in Bengaluru. Builds production AI inside regulated industries.
Building something hard?
Email goes to me, not a form. Answered within 24 hours, including a no.