Built by operators
We're an AI studio focused on Autonomous Operations.
Enterprise operations are made of hundreds of small decisions every day — which vendor to use, when to run a discount, which route to dispatch, which account to chase first, which shift to fill, which price to set. These decisions are rarely made well. Most teams default to gut feel or to a process written eighteen months ago, and the cost compounds quietly into the P&L.
AI agents are good at decisions like these — often better than the humans who make them today. But agents only work when you've understood the operation first. The hard part isn't the model or the prompt. It's calibration: knowing which decisions should be fully delegated to the agent, which should be surfaced for human approval, and which should stay entirely human. Most AI vendors skip that work. We don't.
We're operators. We've run these processes. We start with the business — the workflow, the people, the data, the constraints — before we build anything. Then we build the agents, calibrated to the right level of autonomy for each decision they touch.
- Factory floor
- Supply chain
- Fleet
- Customer success
- Back-office
Trusted by industry leaders
Most vendors start with the agent. We start with the operation.
AI is a tool. Not the product.
- 01
Process
What does the work actually look like, step by step.
- 02
Team
Who does what, what they’re measured on, what makes them act.
- 03
System
Design what should run the operation, end to end.
- 04
AI
Apply it where it earns its place. Not before.
Most shops start at 04 and work backward — they've built a model and need a problem to fit it. We build around the work, and let AI earn its way in.
Our Work
Production AI deployments with measurable business impact
FreightTiger
Customer success engagement with one of India’s largest road logistics platforms.
Swiggy
Supply-chain operations work with a Swiggy company.
Zapkey
Building best-in-class AI infrastructure for real estate.
We practice what we preach.
A 5-person team operating like a 100-person company. The rest is AI we built and run every day.
Company AI OS
The internal stack that runs the whole company — automations, glue, and the connective tissue between every system below.
Mitra
Plans our content every week — pulls analytics, audits the site, decides what to write next.
Adam
Writes our content every day — researches, drafts, validates, generates visuals, and ships to production.
Ken
Runs our finance ops — invoicing, reconciliation, expense tracking, GST.
This website
Built and shipped by AI. Every section, every blog post, every deck.
Our sales decks
Drafted, refreshed, and tailored to prospects by AI. Including the one we just sent you.
If you want to see what production AI actually looks like, you're reading it.
Built in operator networks
Partnerships and communities we work with.
How we work
Three things that separate production deployments from POCs that collect dust.
Understand before we automate
We start with a diagnostic — process, tooling, data, team — before recommending what to build. If AI isn't the right answer, we say so.
Own it end to end
We don't hand off a deck. We write the code, train the models, and stay close to the deployment until it's running in production.
Stay long enough to scale
Most AI work fails between pilot and rollout. We stay through scale-up — instrumentation, evals, edge cases — so the system actually compounds.
Deploying Reliable AI Agents at Scale
80% of enterprise AI projects fail to reach production. Learn the framework used by organizations achieving 40-82% efficiency gains.
Deploying Reliable AI Agents at Scale
A Production Framework
Building AI that ships.
I'm Bala, founder of Applied AI Studio.
I've spent 17+ years building products for growth-stage startups and enterprises. Previously co-founded a SaaS supply chain platform used by large enterprises like Zomato, Zepto, and Porter.
I also run Applied AI Club—a community of 2,500+ operators learning to work with AI through weekly sessions and practical workshops.
Applied AI Studio exists because too many AI projects are built without a measurable outcome. Our small team takes technical ownership of hard problems and delivers measurable outcomes.
We don't do strategy decks. We write code, train models, and ship production systems.
Let's Talk
Have a challenge that needs AI? We'd love to hear about it.