AI Product & Consulting Studio
YGL is an AI product and consulting studio helping businesses discover, build and deploy practical AI solutions — from intelligent automation and internal tools to production-ready applications.
Products by YGL
Consultancies describe AI systems. We ship them. These are products we designed, engineered and deployed ourselves — the same practices we bring to client work, applied where we carry the consequences.
An AI-native wellness platform built by YGL.
Photograph a meal, get an honest macro breakdown. An AI nutrition, fitness and wellness platform with a vision pipeline that refuses to guess.
AI-powered short-form content intelligence.
Turns saved reels into a searchable library of structured, actionable notes — including Hindi and Hinglish audio that most tools drop.
How we think about systems
Not client screenshots — we don't have those to show yet. These are the concepts that actually show up in the work: a data layer that holds, a retrieval pipeline, guardrails, an evaluation harness, a fallback path, monitoring that catches failure before a user does.
Staged delivery
Idea → prototype → production
Consulting
Most AI programmes stall between the strategy deck and production. We work across the whole distance — finding the opportunity, proving it's real, and building the system that runs it.
Find the AI work that's actually worth doing.
Most AI initiatives fail at selection, not execution. We map your workflows, find where a model genuinely beats the current process, and rank the options by value against effort — including the ones we'd advise you not to build.
Take the repetitive work off your team.
The highest-return AI work is rarely a chatbot. It's the operations nobody wants to do: triage, extraction, routing, summarising, reconciling. We design and build automations that run reliably in production and fail loudly when they should.
From idea to a product people can actually use.
We design and build AI-powered products end to end — the model work, the application around it, the data layer underneath and the interface that makes it feel obvious. The same way we build our own.
Make the software you already have significantly smarter.
You don't need a rewrite to get value from AI. We work inside existing applications — adding intelligence to the flows where it changes the experience, without destabilising what already works.
App Rescue
Don't start over. We help founders and teams rescue half-built applications, solve technical bottlenecks and take products from “almost working” to production.
The prototype runs locally and falls over the moment it meets real users, real data or a real network.
Impressive on three hand-picked examples, unreliable on the fourth. No evaluation, no guardrails, no idea what the failure rate actually is.
You inherited a codebase nobody can explain, with no documentation and no way to judge what's safe to touch.
Every fix creates two new problems. The remaining 20% keeps growing because the foundation can't carry the features on top of it.
Vibe-coded fast, but nobody checked auth, data modelling or what happens at real load — the classic gap between an AI-generated prototype and something that scales.
The build works but submission keeps failing — signing, permissions, privacy declarations, review rejections.
Case Studies
Two products we built, and two worked scenarios showing how an engagement runs. The scenarios are labelled as such — we don't have client logos to show you, so we're not going to invent any.
FitRas · built by YGL
Nutrition tracking fails because logging a meal costs more effort than the insight returns. FitRas replaces manual entry with a photo — and gates the answer when the model isn't sure.
InstaBrain · built by YGL
Short-form video holds real information in a format you cannot search. InstaBrain turns it into structured notes and makes the whole library answerable in plain language.
Illustrative engagement
A worked example of how an AI automation engagement runs, from discovery through to a deployed classifier with a human in the loop.
Illustrative engagement
A worked example of an App Rescue: what the assessment looks at, what usually turns out to be wrong, and the order the repairs happen in.
Method
Six stages. The early ones exist to make sure the later ones are worth paying for.
Understand the business before the technology. What the work costs today, where it breaks, who it frustrates, and what a good outcome would actually look like in numbers.
YGL Build Lab
Most AI education stops at the tutorial. The Build Lab is for people who want something live — mentoring, workshops and guided sprints that end with a deployed product rather than a certificate.
You bring a product you're actually trying to ship. We work through it together — architecture, AI design, the parts where you're stuck — until it's live. The curriculum is your codebase.
For: Founders and developers mid-build
Focused sessions for a team on one topic: AI-assisted development workflows, agent design, RAG systems, or getting an AI feature from prototype to production safely.
For: Product and engineering teams
A structured run from idea to a deployed application, with checkpoints. You write the code; we make sure the architecture and AI decisions hold up before they become expensive.
For: Developers who keep starting and not finishing
Why YGL
Small enough to move without a process tax. Serious enough to build things that survive their second year.
Small team, no layers, no handoffs between agency departments. The person who designs the system is the person who builds it, so the decision and the implementation don't drift apart.
Features are easy and systems are hard. We design for the second year — the data model, the failure modes, the cost curve, the person who inherits the codebase.
Strategy decks don't run in production. Every engagement is measured by whether something real went live and kept working.
YGL is early. Rather than dress that up with invented logos and testimonials, we'd rather show you the systems we've built and let the engineering make the argument. More about the studio
Final call
Let's figure out what should actually be built.