Production AI & Engineering Consultant
I help teams ship AI that actually works in production, not just in the demo.
I'm Preksha, an engineer with 7+ years building production software, most recently on high-stakes production systems. The work underneath is production architecture: systems, data, APIs, and cloud, with AI as the sharpest, highest-stakes case. Most AI looks great in a demo and gets expensive the moment real users, cost, and risk show up. I turn it into something that holds, and I'll build it with you instead of advising from the sidelines.
Preksha Shah
Production AI & engineering
Where the real risk lives
The gap between a good demo and a system you can trust.
It almost always comes down to three things. This is the lens I bring to every engagement.
Security & data
The model is the easy part. What breaks is data exposure, access, and decisions you can't explain or audit later. That is what I check first, in any high-stakes system, AI or not.
Reliability in production
A demo answers the easy, expected case. Production has retries, rate limits, bad inputs, and 3 a.m. incidents. AI systems hit all of these, just less predictably. I design for the failure modes before they cost you a customer.
Cost at scale
Infrastructure costs quietly scale faster than revenue, and LLM bills are the fastest-moving version of that. I keep cost, speed, and infrastructure honest against the outcome, so growth doesn't destroy the margin.
Why me
The experience behind the work.
Years of building production systems, writing I publish openly, and open-source work. You're welcome to look through any of it before we talk.
7+ years building real systems
I've spent 7+ years building and leading engineering across web, API, and cloud systems, most recently on high-stakes production systems, where an outage or a wrong decision has real consequences.
Hands-on, not just advisory
Architecture, AI systems, cloud, and API integrations across Laravel, React, Node, and Python. I've made these trade-offs with my own hands, not from a slide deck.
Published writing
I write two newsletters, and my perspective on why AI stalls in production was published by AI Data Press. You can read how I think before you ever book a call.
Real builds, not just talk
Case studies that walk through an actual system: the problem, the approach, and the decisions behind it, not a highlight reel.
See the case studiesHow we can work together
Clear scope, senior judgment, no drawn-out engagements.
Each of these is designed to give a founder or engineering lead faster clarity and fewer expensive mistakes. Start small; go deeper only if it's worth it.
Start here · lowest risk
Architecture Health Check
A tight, written review of one system or one decision. Where the real risk is, what I'd fix first, and whether a deeper engagement is even worth it. The lowest-risk way to see how I work before committing to anything larger.
Advisory & Strategy
Architecture & AI Review
For a team with a working AI demo that needs to know whether it survives real users, security, cost, and scale before betting a roadmap on it.
You get: A written production-readiness review and a prioritized next-90-days plan.
More on advisory & strategyBuild & Delivery
Most hands-onBuild Sprint
For teams that want it built, not just advised. I design and ship a production-ready AI feature, agent, system, API, or architecture build with your team. Scoped tightly, handed over clean.
You get: A working, production-grade AI feature, agent, system, API, or architecture build, shipped and documented. Not another prototype.
More on build & deliveryOngoing
Fractional AI & Engineering Partner
For founders who want senior technical judgment in the room for the hard calls, without hiring a full-time lead yet.
You get: A steady hand on architecture, AI direction, and the decisions that are expensive to get wrong.
How it works
What working together actually looks like.
No long sales cycle and no black box. Four steps from the first call to a clear result.
A short call
Thirty minutes to understand the problem and see if I'm the right fit. No pitch, and if I'm not right for it, I'll say so.
A clear plan
Within a day, a one-page plan: what I'll do, what you'll get, the timeline, and the price. No surprises.
The work
I run the review or build with you in the loop the whole way, so you see real progress as it happens.
Handover
A clear deliverable, a walkthrough, and honest next steps, even when that is you not needing me yet.
In the open
Writing and work you can look through.
Featured in AI Data Press
“A published perspective on why enterprise AI initiatives stall, and what a solution-first approach looks like.”
Featured writing
All writingStraight answers
The questions people actually ask.
How does a working engagement start?
With a short call to confirm the problem, the scope, and whether a paid review is genuinely the right next step. If it isn't, I'll tell you.
Are you taking on new clients right now?
I work with a small number of teams at a time so each one gets real attention rather than a template. If the fit is right, I'll make room.
What kind of teams do you work with?
Any team putting AI into a real product and needing it to actually hold up, from startups to scale-ups. My focus is high-stakes production systems, where reliability, cost, and security stop being optional.
Why should I trust the judgment without a client list?
Read the writing, read the AI Data Press feature, look at the open-source work, and talk to me. I'd rather you judge the thinking directly than take a testimonial's word for it.
If the stakes are high, start with clarity.
One short call to see whether a focused review is the right next step for your team. If it isn't, I'll say so.