We do not build for demos.
We build for results.
CAPABILITIES
What we build.
AI-powered internal tools and dashboards.
We build internal applications and dashboards that replace the spreadsheet-and-tabs problem most teams accept as normal. Live data from the tools you already use, pulled into one screen, with the layers of automation and AI on top that turn raw numbers into decisions. We connect Shopify, Meta, payment processors, fulfillment systems, and internal databases into operational dashboards the founding team opens every morning instead of switching between four tabs.
stack: Next.js . Supabase . Vercel . React Query . the modern data stack
Meta ad intelligence and performance systems.
We build the layer on top of Meta Ads Manager that most teams wish came built in. Live dashboards pulling from every connected ad account, AI-generated morning briefings that summarize yesterday's performance, alert engines that catch ROAS drops and spend spikes before they cost real money, and festival-aware budget planning grounded in your own historical data. Built for brands running serious ad spend across multiple accounts, where the difference between catching a problem at 9am and catching it at 6pm is measured in lakhs. Same approach extends to Google Ads, TikTok Ads, and any paid channel with a real API.
stack: Meta Graph API . Anthropic Claude . OpenAI . n8n . Supabase . custom alert engines
Full-stack AI application development.
We build complete AI products, not demos. Database, authentication, interface, AI integration, deployment, and the unglamorous infrastructure that makes everything else possible. The systems we build are designed to be used by real people on real days, with the production discipline that means uptime, error monitoring, row-level security, and clean handoffs to your team when we hand them over. From consumer apps to internal platforms, end-to-end.
stack: Next.js . TypeScript . Supabase . Vercel . Anthropic Claude . OpenAI
Custom ATS and hiring infrastructure.
We build the hiring stack a serious operation actually needs. Branded application portals, AI candidate scoring trained against the specific role you're hiring for, automated email pipelines for rejection and assignment and interview workflows, tokenized assignment submission, full status tracking from applied through hired. Replaces the Google-Form-to-spreadsheet-to-WhatsApp pattern most growing teams default to, with something that scales without adding a recruiter for every ten applicants.
stack: Next.js . Supabase . Anthropic Claude . n8n . Gmail API
Voice and messaging agents.
We build AI agents that do real operational work inside the channels your customers and team already use. Voice receptionists that take calls, identify intent, book appointments against a live calendar, and log every conversation. Telegram and WhatsApp assistants that send emails, manage schedules, route tasks, and parse documents on command. Internal Slack and Gmail automations that classify, triage, and respond without manual handling. Each agent is built for a specific operational job, not as a generic chatbot.
stack: ElevenLabs . n8n . Telegram Bot API . WhatsApp Business API . Gmail API . Slack API
AI agents and workflow automation.
The systems that quietly do the work no one wants to do twice. Resume parsers that turn any uploaded file into structured candidate data. Knowledge retrieval systems that answer from your own documents instead of from a base model's guess. Content generation pipelines that produce on-brand visuals and copy at scale. Multi-source research agents that pull from APIs, news, and internal data to produce actual decisions. Built across n8n, custom code, and the modern AI stack, with the architectural discipline to keep them running unattended.
stack: n8n . Anthropic Claude . OpenAI . VectorShift . custom Python . the RAG toolchain
Mostofthesystemswebuildstartedasconversationsaboutproblemsthatdidnotfitastandardservice.Ifwhatyouneedisnotonthislist,tellusaboutit.Theinterestingproblemsusuallyarenotonlists.
APPROACH
How we work.
Business first, always.
Every decision starts with what is right for the business, not with what is technically interesting.
Built to work, not to impress.
If it does not work inside the operation, it does not leave our hands.
End to end.
First conversation to final deployment. One team, one accountability.
Honest by default.
We tell you what your business needs, even when it is not what you expected to hear.
Speed with substance.
Fast, but never at the cost of building something that actually works.
No size limit.
Individuals, growing businesses, established companies. Good work does not discriminate.
STACK
The layers underneath.
We are deliberately tool-agnostic. The stack is chosen to fit the problem, not the other way around.
Language models & reasoning
Frontier and open models, retrieval, and evaluation pipelines, chosen per problem rather than per trend.
Web & application layer
Modern typed front ends and server frameworks built for speed, accessibility, and long-term maintenance.
Data & warehousing
Pipelines, transformations, and stores that keep numbers trustworthy from source to dashboard.
Automation & orchestration
Event-driven workflows and schedulers that run the repetitive work without a person in the loop.
Integrations & APIs
Ad platforms, messaging, payments, and internal systems wired together so the data moves on its own.
Infrastructure & delivery
Cloud hosting, observability, and deployment set up so what we ship stays up and stays fast.
WHO WE WORK WITH
Size is not the filter. What they share is that the cost of getting the system wrong is now higher than the cost of building it right.
Founders shipping their first real systems
Early teams who need a senior builder, not a junior hire or another no-code patch.
Operators whose manual work has outgrown the team
The spreadsheets, the copy-paste, the 11pm reconciliations. Work that should have been automated a year ago.
Teams whose existing tools have stopped scaling
Systems that worked at ten people and quietly broke at fifty. Rebuilt to hold.
ABOUT
Most automation projects fail because they were built by people who never had to live with the result.
Shreyansh Kanoongo, founder
Before Automiq Labs, I spent time inside a fast-growing D2C brand leading the AI work — building the dashboards, the alert engines, and the ad intelligence systems the founding team opened every morning. Those systems are still in production. That is the reason I will not ship a system that breaks the moment the team I built it for tries to use it on a Monday morning.
CONTACT
Let’s build somethingthat actually works.
Tell us what you are trying to build. We will tell you whether we can help.