MorningLabs AI · AI Infrastructure
Custom AI agents, audited before they ship.
We build AI agents that answer your customers when you can't. Then we attack them ourselves and fix what breaks, before you go live.
30 min · If AI isn't the answer, we'll say so
A human signs off before your customers see it
Everything you already run
reading from one dashboard
reading from one dashboard
- STOREFRONT
- CONVERSATION
- MONEY
- HIRING
- THE DESK
- THE MODELS
We connect to Shopify, Instagram, Meta, WhatsApp, Telegram, Slack, Razorpay, Stripe, LinkedIn, HubSpot, Gmail, Google Sheets, Google Analytics, Claude, OpenAI, Gemini and Perplexity.
What you can ask it
Who should I call first today?
Rohit Menon — three site visits, no quote sent — from HubSpot
Which orders won't survive delivery?
91 flagged before dispatch — from Shopify
Which candidate is worth a call?
Four of 312 cleared the take-home — from LinkedIn
Which ad should I put budget behind?
Set 3 — half the cost per order — from Meta
What changed since last week?
Returns up 3.1 points, all of it Tier-3 — from Google Analytics
What should I fix first?
The pincode field. It costs the most. — from Claude
What actually changes
- Your morning, already checkeda written brief waiting before 8am
- The repeat work stops costing hoursthe same forty answers, handled without you
- Every source read togetherone view across storefront, inbox and spreadsheet
Four businesses. Four bad afternoons.
Most people don't need an explanation of what an AI agent is. They need to see the afternoon it would have saved them.
Four calls came in after 6pm on Friday. Two left voicemails. By Monday, both had booked with someone else.
Now: Every call gets picked up, qualified, and booked into Monday's diary before anyone opens the laptop.
AI receptionistThe same six questions about sizing and delivery, forty times a day, answered by a founder who should be buying stock.
Now: The six questions answer themselves inside WhatsApp. The seventh, the weird one, reaches a human with the context attached.
WhatsApp ordering agentEvery client deliverable starts from a blank document at 9am.
Now: A voice note becomes a first draft in the client's voice. The strategist edits instead of starting. Nothing publishes without a human pressing publish.
Brand-voice content engineThey already switched something on. It works, mostly. Nobody can say what happens when it doesn't, and nobody wants to be the one who asks.
Now: They know exactly what it can see, what it can be talked into, and what happens when it's wrong. In writing.
AI Safety AuditComposite examples based on the kinds of systems we build.
Someone once tried to inject code through a chatbot we'd built. Live site. Real customer data behind it.
Nothing leaked. The attempt hit checks we'd designed before launch, back when the bot was still on paper.
That's the whole company in one moment. We plan for failure before we ship — so you hear about problems from us, never from your customers.
A call comes in at 6:47pm. Nobody's there.
This is a lead-qualification agent handling an inbound call on its own. Every line below is a step it takes, and the last one is the part most people skip.
The last line is the one that matters. A human still sees it.
What we build.
Every system is custom. No packages, no subscriptions you'll forget to cancel.
Built for teams of 1–30.
Small teams feel every hour they lose. These are the three shapes of company we build for.
Founders and early teams
You want systems you own — code, docs, and training included, no retainer required.
Marketing and sales leads
Your team burns hours on work an agent should draft first.
Teams mid-pilot
Something's running. The results are inconsistent. Nobody can tell you what's safe to scale, and everyone's too polite to say so. Start with the audit.
Four steps. No surprises.
A diagnosis session, 60–90 minutes. We look at what you're trying to do, what's breaking, and whether AI is actually the right solution.
Most of what goes wrong is decided before a line of code exists. That's the cheapest place to catch it. We define what agents do, what data they touch, and how the system fails gracefully.
Custom code, not configuration. Error handling from day one, logging at every critical step. Built like infrastructure — because that's what it is.
Deployment isn't the end. We monitor the first 2–4 weeks live, fix what breaks, and hand off only when the system is stable.
Find out what your AI would say on its worst day.
The message came in on a live chatbot — a working site, real customer data behind it. Someone was probing it with injection attempts, trying to make it execute code and cough up what it knew.
The bot refused, logged the attempt, and flagged it. Every check it hit had been designed months earlier — before launch, when the system was still a diagram.
We didn't get lucky. We'd already assumed someone would try. That assumption is what we sell.
- Prompt injection and jailbreak attempts
- What it does when it does not know
- What it must never say, and how that is enforced
- Who gets told when it fails
- Intent classifiedpassed
- Instruction override detectedblocked
- Data scope checkpassed
- Response withheldpassed
- Logged and escalatedpassed
- Human notifiedpassed
Nothing reached the customer.
This runs before anything ships. Every time.
"I spent a decade in marketing inside growing companies — the last stretch running a full marketing transformation for a global recruitment tech firm. Over and over I watched the same scene: AI shipped in a sprint, trusted by nobody, owned by nobody, quietly switched off by month three. MorningLabs is my answer to that. We build the slow way, on purpose."
Vishal Gupta
Founder · MorningLabs AI
Mornings are for clear thinking. Labs are where ideas get tested.
We'd rather not be your dependency.
Most agencies build something you can't touch, then charge you monthly to touch it for them. We hand over the code, the documentation, and the training to run it.
Team workshops for marketing, sales, and ops. AI literacy programmes for schools, because the next generation should understand this before it understands them.
If we've done the job properly, you need us less each month.
Repository, documentation, and deployment access handed to you.
Workshops until the people using it daily can change it themselves.
Then we step back. Longer only if you ask.
Client work funds the lab. The lab ships tools.
Meridian AI
Our first product, currently in the lab. Details when it's ready.
Bring the thing
that's stuck.
A 30-minute diagnosis call. Free. If the answer is "you don't need AI for this," you'll hear that too.