TransformingMini IdeasintoMega Innovation
AI automation agency · founder-led
MiniAI Labs designs, builds and runs AI systems for growing businesses: assistants that answer from your own documents, voice agents that pick up the phone and workflows that move data between your tools. A fixed price in writing, accounts in your name, a person in the loop.
Decorative animation: the MiniAI Labs "M" mark in polished graphite, ringed by fine particles of light. A loose cloud of ideas drifts around it; as you scroll the ideas gather into a lightbulb, then an agent graph, then resolve back into the "M".
From a mini idea to a shipped system
Technologies we build with
Named to show what we build with. These are not endorsements, partnerships or client logos.
OpenAI
Anthropic Claude
Google Gemini
Meta Llama
Mistral AI
Hugging Face
LangChain
n8nMakeZapierWhatsApp Business PlatformTwilio
Stripe
Supabase
Cloudflare
Vercel
Next.js
Python
TypeScript
Docker
GitHubHow we work
After a free scoping call you get a written proposal with the scope, a fixed price, the timeline and an estimate of running costs such as AI usage or telephony. There is no hourly billing, paid work starts only once you accept, and anything new is quoted before we build it.
Proposal and payment termsModels, telephony, WhatsApp and hosting run on accounts registered to your business wherever possible, so you pay providers directly and keep admin control. You can revoke our access yourself at any time, and once you have paid in full, the deliverables we created are yours.
Ownership termsEvery system knows when to stop. Low-confidence answers go to your team with the full conversation attached, and actions that move money, message people outside your company or change records wait for someone to approve them. You decide where those lines sit.
Security practicesWe are an early, founder-led studio, so we show the work instead of borrowed logos: concept builds with their architecture and typical targets, published prices, and the assistant on this site. A 14-day money-back guarantee on our fees backs the first working version.
See the concept buildsThe delivery architecture
Data layer
We ingest your documents, help pages, policies and product data, split them into passages and index them by meaning and by keyword, so answers come from your content rather than the model’s memory.
A source inventory and an indexed knowledge base your team can update
AI core
A router reads the request, picks a specialist prompt and a model sized for the job, and lets the model call only the tools on its allowlist. Long tasks run as explicit steps, so any run can be inspected and replayed.
A routing and tool map, plus the test set the system has to pass
Integration layer
The same engine answers on your website, WhatsApp, phone lines or email, and writes results back to the systems your team works in through their APIs and webhooks.
Channels set up on your accounts and a written data-flow map
Control layer
Guardrails set what the system may say and do, approval gates hold high-risk actions, and every conversation and run is logged, so your team can read transcripts and see why something happened.
Handoff rules, approval gates and a review routine your team owns
Services
Each loop shows Sample data, for illustration.
Assistants on your website and WhatsApp that answer from your own content, cite their sources and hand over to a person when they are unsure.
Pipelines that move leads, orders and documents between your tools, retry when a service fails and log every run.
Multi-step agents that research, draft and update records with scoped tools, and stop for approval before anything leaves your company.
Phone agents that say they are AI at the start of the call, handle routine calls and bookings, and transfer anything urgent to your team.
Retrieval and AI pipelines over your documents, databases and internal APIs, deployed where your data has to stay.
Short-form and explainer videos from brief to storyboard to final cut, with a review at every stage and the rights stated.
Find your AI solution
What we plan for
Typical target
5–14 days
Time to a first working version
Basis: Our published per-service delivery ranges, counted from your acceptance of the proposal; larger builds run in milestones, each with a demo
Typical target
40–70% of in-scope volume after tuning
Routine requests handled without a person
Basis: The share of repeatable questions or tasks in your own ticket, chat or call export, measured in discovery and confirmed in the pilot; everything else reaches your team by design
Typical target
None, by design
High-risk actions taken without approval
Basis: Payments, messages to people outside your company and deletions pass an approval gate enforced in code, and are tested with misuse scenarios before launch
Typical target
Estimated in every proposal
Running costs known before you commit
Basis: AI usage, telephony, messaging and hosting are estimated for your expected volume and billed by the providers on accounts in your name
Proof, built in the open
Each one walks through the brief, the architecture, a sample run and the typical targets we would plan for. Concept builds are worked examples, not client work.
Concept buildAI Chatbots
A concept build showing how we would build a support bot for an online electronics store whose helpdesk fills with the same few questions. The bot would answer order, delivery, returns and product-fit questions from the store’s catalogue, policies and live order data, on the website and WhatsApp, and pass everything else to the helpdesk with the conversation attached.
Concept buildWorkflow Automation
A concept build showing how we would automate the admin around each appointment at a multi-doctor clinic: booking, reminders, intake, follow-up and reporting. It would sit on top of the clinic management software the team already uses, carry appointment logistics only and leave every clinical decision with the clinic.
Concept buildAI Agents
A concept build showing how we would build an AI agent that qualifies property leads on WhatsApp and website chat at any hour. It would ask about budget, area and timing, score each lead against the agency’s own rubric and book viewings for qualified buyers, so agents spend their time with people who are ready to view.
Concept buildAI Chatbots
A concept build for a direct-to-consumer brand in India whose WhatsApp inbox fills with the same two questions: where is my order, and how do I return it. The assistant answers in English, Hindi or Hinglish from live order data and the brand’s own returns policy, and hands anything unusual to a person with the whole thread attached.
Concept buildAI Chatbots
A concept build for a B2B software company whose help centre is thorough but hard to search. The copilot answers product questions from the published documentation, shows the passages each answer came from, and opens a support ticket, carrying the question and the sources it tried, whenever it is not confident.
Concept buildAI Chatbots
A concept build for a boutique hotel in the UAE whose front desk answers the same guest questions in several languages, day and night. The concierge replies on WhatsApp and the hotel website in the guest’s language, answers from the hotel’s own guide, turns requests into housekeeping tickets with the room number, and puts complaints in front of the duty manager straight away.
Concept buildWorkflow Automation
A concept build for the finance team of a UK small or mid-sized business that keys supplier invoices into its cloud accounting system by hand. Invoices arriving by email are read into structured fields with a confidence score, matched to purchase orders, approved in team chat by the budget owner and posted to the accounting system, while anything that does not match lands in an exception queue with the reason attached.
Concept buildWorkflow Automation
A concept build for an Indian startup that hires every month and runs onboarding from one person’s memory and a long checklist. A signed offer starts a workflow that creates the email and team-chat accounts, raises the laptop ticket, shares a day-1 checklist and books the 30-day check-in. When a step fails, it retries and tells that step’s owner instead of failing silently.
Concept buildWorkflow Automation
A concept build for an independent insurance agency in the US, the broker between its policyholders and several carriers, that receives first notices of loss by email and web form with photos and documents attached. Intake reads each claim into a structured record, checks it against a completeness checklist for that line of business, asks the policyholder for anything missing right away, and queues complete files for an adjuster. The AI never decides coverage.
Concept buildAI Agents
A concept build for a US online marketplace where sellers upload products with thin titles and half-empty attributes. An agent reads each new listing and the supplier’s spec sheet, fills category attributes and a description from that data only, validates the result against the category schema and sends it to a merchandiser for approval. Nothing publishes without a person.
Concept buildAI Agents
A concept build for a research agent that prepares a cited company brief before a sales call, so reps start from checked facts, not a pile of browser tabs. It plans its own research, works only through allow-listed tools, links every line to a source, and drafts a CRM note that a rep approves before anything is saved.
Concept buildAI Voice Agents
A concept build for a voice agent that answers a dental clinic’s phone after hours in Arabic and English and books routine visits into the clinic calendar. It sends an SMS confirmation, moves callers who describe urgent symptoms straight to the on-call dentist, and never gives clinical advice.
Concept buildAI Voice Agents
A concept build for an outbound voice agent that makes routine ETA check-in calls to truck drivers and logs each answer in the fleet’s TMS. It calls only when the truck is parked or at a check-in window the driver chose, and it alerts a dispatcher straight away when a driver reports a breakdown or a delay.
Concept buildAI Video
A concept build for a pipeline that turns a listing’s own data and licensed photos into short vertical and widescreen videos on one brand template. A model writes scene captions only from the listing fields, every number on screen is checked against the record, and nothing is published until a reviewer at the portal approves it.
Concept buildAI Video
A concept build for a pipeline that turns a teacher’s lesson outline into a captioned explainer video, with the teacher’s review at the centre of every step. A model drafts the script, the teacher edits and approves it, and slides, captions and the render follow automatically before the video is uploaded to the LMS.
Concept buildCustom AI
A concept build for a camera inspection step that sorts machined parts into pass, flagged or unsure with a detector trained on the plant’s own images. Unsure parts always go to a person, and the quality team keeps the final say on scrap and rework.
Concept buildCustom AI
A concept build for an internal assistant that answers staff questions from a firm’s own documents, inside the firm’s cloud account. Every answer cites its sources, and retrieval is filtered by each person’s existing document permissions, so nobody gets an answer built from a file they could not open.
Concept buildAI Agents
A concept build for the purchasing team of a UAE trading and distribution company that chases overseas suppliers by hand for order confirmations, ship dates and shipping documents. Four agents split the work: a planner picks the orders that need chasing, a researcher gathers the facts, a writer drafts one email per supplier and a reviewer checks every figure against the sources. A buyer approves each email before it goes, so nothing reaches a supplier on its own.
Process
The problem, the tools you use and what a good result looks like. If AI is not the right fix, we say so.
Scope, price, timeline, payment schedule and a running-cost estimate.
On accounts in your name, so you can steer early instead of waiting for a reveal.
Something you can try yourself. The 14-day money-back window starts here.
Live in production, a walkthrough for your team and the documentation.
Support included in your plan, then run it yourselves or move to monthly optimisation.
Security-first
Each connection gets only the scopes its task needs, with keys kept out of the code and revocable by you.
It is used only for your project and never to train systems we build for anyone else, and we pick provider settings that keep it out of model training wherever they exist.
The AI sees only what each task needs, health data stays in systems you control, and testing can run on de-identified data.
NDAs, DPAs and BAAs are reviewed case by case before work starts. We only sign commitments we can meet.
Engagement
$497one-time
For one clearly defined process, delivered once at a fixed price.
Custom
For larger organisations, quoted per project after a scoping call.
AI usage, telephony, messaging and hosting are paid to the providers on accounts in your name, or passed on at cost with no mark-up. Enterprise builds can include a custom SLA.
Compare plans on the pricing pageFAQ
Six kinds of systems: AI chatbots that answer from your own content, AI voice agents that answer and route calls, AI agents that carry out multi-step tasks with approvals, workflow automations that move data between your tools, custom AI and retrieval (RAG) systems on your own data, and AI video production. Every build runs on our delivery architecture rather than a self-serve product you sign up for, and is set up around your channels, data and rules.
Start with one process that repeats every day, follows rules someone could write down and already has an owner, such as answering the same customer questions or copying form leads into a CRM. Bring an export or a handful of real examples to the free scoping call. We tell you whether AI is the right fix, what a first version would cover and what it would cost before anything is built.
The written proposal follows the scoping call, and we confirm when you will have it before the call ends. Once you accept it, a first working version typically takes 5 to 14 days: chatbots 5 to 7 days, voice agents about 5, video 3 to 5 days from script approval, a custom integration with one system 7 to 14, and workflow automation or agents 10 to 14. Larger builds are split into milestones, each with its own demo.
We are model-agnostic. Builds use models from OpenAI, Anthropic (Claude) and Google (Gemini), or open-weight models such as Meta Llama and Mistral when data has to stay inside your environment. We shortlist per task and test the candidates on your own questions for answer quality, speed, cost per conversation and the provider’s data terms. The model sits behind one routing layer, so it can be changed later without a rebuild.
Usually, yes. Anything with an API or webhooks can be connected, and for older systems we look for an export, a database view or an email feed instead. Tools in our build stack include n8n, Make, Zapier, the WhatsApp Business Platform, Twilio, Stripe, Supabase and Cloudflare. Your specific CRM, helpdesk or calendar is confirmed on the scoping call, together with the narrowest access each connection needs.
No AI system is right every time, so every build is designed for the moments it is unsure or out of scope. Answers come from your own documents and show their source, a low-confidence answer becomes a clarifying question or a handoff to a person, and anything that moves money, sends a message outside your company or deletes data waits for approval. Before launch and after every change, we rerun a test set built from your real questions.
Yes — if you are not satisfied, you can claim a full refund of the fees you paid us for a project within 14 days of receiving its first working version (on a monthly plan, the plan fees paid up to your claim). Third-party costs such as AI usage or hosting are not refundable. To claim, email hello@miniailabs.in; we send the refund within 14 days of your claim, to your original payment method. The full conditions are in our Terms of Service (miniailabs.in/terms/).
Yes, through our Agency Partner programme, on any plan. Agencies and consultancies can resell our work under their own brand with an NDA in place: you are our client, our proposal to you sets the scope and price, and you set your own price for your client. Partners who refer clients to us earn a 5-10% recurring commission on our fees from those clients, for 12 months unless the partner agreement says otherwise, paid monthly once the client's money-back window has closed; it is not paid on white-label work unless the agreement says so. The details are in our Terms of Service (miniailabs.in/terms/).
Monthly maintenance on the Growth plan includes performance monitoring, knowledge-base updates, prompt and evaluation tuning, bug fixes and optimisation based on usage data. Priority support adds a dedicated chat channel for your team, with response times set out in your proposal. A custom SLA is available for Enterprise builds.
We have dedicated pages for SaaS and startups, e-commerce, real estate, healthcare, where builds are HIPAA-aware, and hospitality. Our concept builds also work through insurance intake, finance operations, logistics and education examples; they are worked examples, not client work. For any other sector, the scoping call is where we check honestly whether the workflow suits AI before you spend anything.
Next step
Book a free 30-minute strategy call. We look at one workflow you want to automate, tell you honestly whether AI fits, and outline the scope, the integrations and a sensible first version.
Free 30-minute call · no commitment
