looking to speak with a Full-Stack Product Engineer (AI SaaS) — Paid Consultation

This thread is a month old so if you are already sorted, ignore me.

If not: I ship full-stack AI SaaS solo, currently 24 production apps including image plus inference pipelines, and AI products live for regulated industries (law firms, lenders). Your ask is the exact shape of work I sell, with one difference from the replies above: I do not do consultation calls. I do a fixed-scope async discovery sprint instead. You get a written architecture sanity-check, a tight MVP scope cut, and a ranked technical-risk list with realistic cost modeling (image pipeline plus inference cost is where plant-science AI usually bleeds first). A document you can hand to any engineer you hire later, not an hour that evaporates.

A few days turnaround. If that beats another call, reply here or DM me. My company is No Human Nearby if you want to look me up first; this account is new so IH will not let me post links yet.

Hey,

Saw your post about the plant-science AI SaaS on Next.js + Supabase + Vercel. Fun lane to be building in. Plant science has way more room than most people realize.

You asked about architecture sanity-check, MVP scope, and risks. Here's where my head goes immediately, in case any of these are already top of mind:

1. The image pipeline. With image uploads + AI processing, the architectural question is usually where the processing runs (Vercel function, separate worker, or third-party API) and where you keep the originals vs. processed versions. Defaults look fine until your first 12MB phone photo.

2. AI cost shape. Per-image inference on a vision model adds up fast. Worth modeling that on day one for whatever your expected usage pattern is, since the unit economics can quietly flip before you notice.

3. Image rendering + layering. There are three flavors: client-side canvas overlay, server-side image composition, or going through a third-party API. Each has different cost and complexity tradeoffs depending on what you're showing the user.

Quick question: is this disease/pest identification, growth tracking, consumer plant ID, commercial growing, or something else? The specific use case changes which of the above matters most.

Happy to do the paid call you mentioned. No rush, whatever works for your schedule.

Mike

This is exactly the conversation worth having before writing a single line of code. Architecture decisions in week one of an AI SaaS, how you handle model calls, context management, fallback logic, have compounding costs if you get them wrong. We do a free architecture scoping call as part of our intake and have found that 80% of the time, founders can cut MVP scope by 30% just by getting clearer on the core loop. If a paid consultation doesn't materialise, feel free to reach out. I'm happy to give 30 minutes of honest feedback.

Before you book a full consultation is the blocker building features, or deploying the thing and keeping it running? Those are really different problems. If it's the deploy/infra side , hosting the database, not getting surprise-billed that's a much narrower job than a product-engineer engagement, and there are faster, cheaper ways through it. Happy to point you the right way either way. What exactly are you stuck on?

I'm a senior software engineer and looking for collaborators.
Please contact me via WhatsApp or telegram.
WhatsApp: +1 (513) 910-0712
Telegram: @montra21

Plant science domain + image-based AI tools is a specific combination most engineers would underestimate. The real architectural risk isn't the AI integration, it's designing the image pipeline (upload, processing, layering, rendering results) in a way that doesn't become a bottleneck once you add real users. Most MVPs get that wrong early and pay for it later.
I've shipped full-stack products on exactly your stack (Next.js, Supabase, Vercel, Postgres) including a HIPAA-compliant healthcare platform and an image-heavy 3D configurator with real-time rendering. Both required the same discipline you're describing: tight MVP scope, clean architecture from day one, no over-engineering.
The scoping session you're describing is actually the highest-leverage thing you can do right now. Happy to do a paid consultation focused specifically on your image pipeline architecture and AI integration path. That alone should surface the 2-3 decisions that will define whether your MVP is extensible or a rebuild waiting to happen.
DM me if you want to get into it.

Hey @greenstack . I can help you out with SAAS consultation. The initial 2 hours will be free and hopefully we will solve a good chunk of your problem in those 2 hours so that you feel the value of partnering with me. You can email me at goureshramrakhyani@gmail for detailed portfolio and past client history.

Sanity-checking architecture before building is the highest-leverage thing you can do at this stage - most founders skip it and end up rebuilding 3 months in.
I run a dev studio that works with non-technical founders on exactly this: paid scoping sessions, MVP scope definition, technical risk review. If you haven't found the right person yet, happy to chat.

Wow. Great work for me.
Let's work together.
Please check my portfolio - Mor, Treepixel on project section.
troy-barrett-portfolio[dot]vercel[dot]app
It's all developed and deployed successfully by NextJS, Supabase.
Hope to get your reply soon

The combination of deep domain expertise and a clear monetization focus is exactly the right starting point — most technical risk in AI SaaS isn't in the stack, it's in the gap between what the founder knows and what the system is built to do.

The architecture sanity-check and MVP scoping you're describing are really one problem: what does this system need to be true about your domain before it can do anything useful? Get that definition right and the technical decisions follow naturally.

Happy to have that conversation if you're still looking.

That's what Hiqbyte does best @greenstack . Why don't we have a quick discovery call and eventually decide for a long term collaboration. Drop a mail at [email protected] and let's discuss future.

I would be glad to explore the opportunity to work with you. We can connect via email at [email protected]
Additionally, could you please share your LinkedIn profile?
I look forward to discussing this further.

The "fastest path to a working product" piece is the part I'd actually enjoy digging into with you. Early SaaS ideas usually have one or two things that quietly become the whole project, and finding those before you build is half the battle.
DM me if you want to jump on a call.

This work aligns well with my skills and experience, and I would be glad to contribute to your organization. Can we connect to discuss further? Recently completed project including AI would love to give you demo

Hey! This is right in our lane at Notzero Software Studio. We're a full-stack software agency with experience building AI-powered SaaS products end-to-end from architecture all the way to deployed MVP. Happy to jump on that paid consultation call. DM me and let's connect.

My team and I built an AI Saas for a company that was recently acquired. That app and most of the ones we build use Laravel + PHP + MySQL, but I am very familiar with full stack web architecture, APIs AWS, and narrowing down what's needed for an MVP. Let me know if you're interested in talking more.