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Kanav Chauhan, AI full-stack developer
AI that survives production.
I build retrieval systems, AI agents and the products around them, with the evals and guardrails that make them safe to ship.
In a hurry? The 60-second version →Five AI products: three live products built at Toshi Consulting, and two platforms I built on my own, from the AI logic to the interface. Each case study shows how it works.
01
Sep 2026 · AI full-stack developer at Toshi Consulting
A sales CRM built for Indian B2B teams: leads from IndiaMART, JustDial and Meta Ads in one queue, an AI sales assistant, WhatsApp follow-ups and GST-correct quotes.
Built with
02
Jul 2026 · AI full-stack developer at Toshi Consulting
AI-checked grain intake for agricultural warehouses: a vision model checks every truckload, every bag gets a QR code, and certificates are signed so nobody can fake them.
Built with
03
May 2026 · AI full-stack developer at Toshi Consulting
An exam preparation platform for classes 1 to 12: adaptive practice, mock tests, an AI doubt-solving tutor and a study plan that rebuilds itself after every test.
Built with
04
Mar 2026 · Solo build: AI pipeline, backend, web app
A multi-tenant support platform: AI classifies tickets from email and WhatsApp, finds the right help articles and drafts cited replies, and a human approves anything risky.
Built with
05
Sep 2025 · Solo build: backend, retrieval, evals, web app
Company knowledge search that answers employees' questions with citations, using only the documents each person is allowed to see.
Built with
35 core skills · 6 areas · full index below
Every skill here was used in real work. Point at a project to see what it was built with, or at a skill to see where it was used.
The toolkit
From skills to shipped work.
Scroll and each category wires itself up to the products it went into.
The index · every skill, wired to where it shipped
58 skills · 7 groups · 46 shipped
Try it
How a model reads your text
Models don't read words. They read tokens: small chunks of text.
Retrieval-augmented generation isn't magic. It's careful plumbing.
17 tokens, 66 characters. A rough estimate, not a real tokenizer.
Keep scrolling to fly through it, one layer at a time.
The same four stages whether I join your team or come in for a project.
Week 1
Sit with the people who will use it. Collect 50 real questions or tasks, and agree on what 'good' means before writing code.
Weeks 2-3
The thinnest version that runs end to end on real data. Ugly is fine; fake is not.
Weeks 3-4
Measure what the model gets wrong, fix the biggest failure, measure again. Repeat until the numbers move.
Ongoing
Production rollout with monitoring, alerts and evals in CI, so the next prompt change can't quietly break things.
Full-time
AI full-stack developer
Product teams putting LLM features in front of real users. Remote, or on-site in Chandigarh.
Freelance
RAG audit
Two weeks. I measure your current system, find why it fails, and hand over a ranked fix list.
Freelance
Prototype to production
Six to eight weeks to take a promising demo and make it something customers can rely on.
Most AI projects die somewhere between the demo and the first real user. I work in that gap: measuring what the model gets wrong, designing the retrieval and the guardrails, and building the product around it so people actually come back.
Experience
Certifications
Education
Out of the dark, into the open.
or hover the city behind this section: every tower is a day, and it plays a note.
159
public contributions on GitHub from 05 Oct 2025 to 08 Oct 2026. Every dot below is one of them, set down on the day it was made. Quiet months included, nothing rounded up.
resume_analyser_llm
ATS-style resume screening: match score, matching skills and suggestions, with Groq and LangChain.
Loan-Prediction-in-Industry-Level-Prototype
Predicts how likely a loan applicant is to be approved, from data cleaning to model.
Machine-Learning-Projeccts
Machine-learning projects and notebooks: regression, classification and evaluation.
recent commits
Set default theme to dark for first-time visitors
portfolio26 · Oct 2026
Fix Netlify build: exclude Next.js cache from secret scanner
portfolio26 · Oct 2026
Ignore browser-extension attributes on <body> (ColorZilla hydration error)
portfolio26 · Oct 2026
PROGRESS: backups moved to 'portfolio backup/', stale lines cleaned
portfolio26 · Oct 2026
new changes to learn and practice
interview-prep · Sep 2026
first commit
interview-prep · Sep 2026
Sep 2025Case study
Keeping forbidden text away from the model: permission-aware RAG
Mar 2026Case study
Why "ticket in, GPT answer out" isn't enough for a support team
Jul 2026Case study
Certificates nobody can forge: signed grain intake at the warehouse gate
Now building
A live AI chat on this site: gpt-oss-120b on Groq, answering only from my own work.
Now learning
MCP: servers and clients that let agents use real tools safely. Atlas already serves search over it.
Now exploring
Open-weight models on Groq: fast, cheap inference for real-time agents and voice.
Now practising
System design for scale: queues, caching, rate limits and multi-tenant data, the way production SaaS is built.
Now deploying
My two platforms, live on one VPS: Docker Compose behind Caddy, CI on GitHub Actions, AI through a self-hosted LiteLLM gateway.
Now reading
Designing Data-Intensive Applications: how real databases and distributed systems hold up under load.
Your idea. My expertise. Ready?
Get in touch
Open to full-time roles and a few freelance projects.
Your turn
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Level 1 of 3 · Naive bot
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