01Find the leverage
Start with the operation, not the model.
We trace one workflow, find the delay or rework worth solving, and agree how to measure a useful improvement before we build.
RESEARCH + APPLIED AI / GULF, INDIA AND NEW MARKETS
We build AI.
Your team owns it.
We learn from operators, publish what the market is telling us and build practical AI systems around work that matters.
Start a research conversationOne workflow. A measurable change.Built with your people.Capability over dependency.One workflow. A measurable change.Built with your people.Capability over dependency.
/ What makes dotSuper different
From zero to one.
Then built to last.
02Build the system
Built for the way your people work.
Real data, existing tools, permissions and exceptions shape the system. We test it with the people who will use it, with clear boundaries for human judgement.
03Make it last
Ownership is a deliverable.
A named owner, practical training and a usable runbook belong in the handover. Your team should understand how the system works and what to do when it needs attention.
/ Market research
Before we build,
we listen.
Across the globe, we are speaking with businesses in manufacturing, retail, logistics, construction, healthcare and other industries to understand how they see AI and technology today.
What excites them? What concerns them? Where do they see real potential, and where does AI still feel disconnected from the way their businesses actually work?
These conversations help us understand the people, priorities and perspectives behind AI adoption across markets.
We believe the best technology starts with understanding the people it is built for.
- 01Listen
We talk to founders, operators and industry teams about their experiences, expectations and views on AI and technology.
- 02Learn
We look for the perspectives, questions and challenges that emerge across industries and businesses.
- 03Build
What we learn shapes what we build: practical AI systems designed around real businesses, not assumptions.
/ How we engage
Three entry points.
One operating thesis.
We start with evidence and one real constraint, not a catalogue of tools. These offers provide different ways to research the problem, build the first useful system or keep a proven improvement moving.
GEO Inbound Engine
Make your expertise easier to find and understand across search and AI answers. Build useful content around verified facts and connect observable demand to qualified enquiries.
Explore the engine
AI Readiness Sprint
Fifteen working days to examine one workflow and choose a practical first move: build a pilot, improve the foundations or pause with a clear reason.
Explore the sprint
Optimisation Subscription
Keep improving the systems your team runs. Small AI, development and operational projects, with one active priority and a clear finish line.
Explore the subscription
/ What the full 0 → 1 programme delivers
What you leave with
01
A use case worth backing
↗02
Workflow + data readiness map
↗03
A working first system
↗04
Human-in-the-loop guardrails
↗05
Team enablement + documentation
↗06
Clear ownership after launch
↗/ Stage check
Are we built
for each other?
You make or move real things.
Manufacturing, industrial, and operational businesses are where we do our best work.
A workflow is costing you.
It is slow, repetitive, inconsistent, hard to see or dependent on one person.
You can name a useful change.
Faster quoting, fewer review errors, clearer records or a decision made on time. We agree the measure together.
You want your team to own it.
We build with your people so the capability stays after the engagement ends.
You can act on an honest diagnosis.
If better records or a simpler process would solve the problem, we recommend that first. A build needs a useful purpose and someone inside the business ready to own it.
/ Capability over dependency
The capability
stays with you.
A useful system comes with the knowledge to run it. We make the owner, access, documentation and support responsibilities explicit, so your team can make informed decisions after handover.
Read our principles/ The 0 → 1 programme
One constraint.
Five deliberate moves.
A focused path from an expensive workflow problem to a useful system your team can run. Every stage has a decision, an output, and a clear owner.
- 01
Find the constraint
Trace the workflow from trigger to hand-off. Identify the delay, rework, information gap, or decision bottleneck worth solving.
OUTPUT · Opportunity brief + baseline - 02
Define the first win
Choose one use case valuable enough to matter and narrow enough to test. Record the baseline, success measure and conditions that would make us change course.
OUTPUT · Prioritised use case + success metric - 03
Build in context
Build the smallest useful version around representative data, existing tools, permissions and real exceptions. Keep the people doing the work involved.
OUTPUT · Working prototype - 04
Prove it safely
Test accuracy, hand-offs, permissions, fallback paths and where human judgement must remain, using real users and real work.
OUTPUT · Validated pilot + operating guardrails - 05
Transfer ownership
Give the named owner a runbook, training and a clear support path. Review access, ongoing costs and maintenance responsibilities before handover.
OUTPUT · Runbook + ownership + support plan
/ How value compounds
The first win
changes the curve.
Scroll to move from a visible constraint to capability the business can keep building on.
01DAY 0 · BASELINE
The line starts with what is true.
We establish the operational baseline and name the one constraint worth changing. No growth claim comes before this evidence.
100+businesses impacted through founder-led applied-AI initiatives
/ Built from the field
Practical experience with business and manufacturing teams.
Founder-led applied-AI initiatives have helped more than 100 businesses identify and act on practical opportunities. Those conversations with founders, operators and industry leaders shape how dotSuper approaches the work.
100+ measures the reach of these initiatives, rather than the number of paying dotSuper clients./ The first useful move
One stuck workflow is enough to start.
Bring one market signal, operational constraint or AI question. In a 30-minute research conversation, we separate what is known from what still needs evidence and identify the next useful question. Any deeper diagnosis or build is scoped separately.
Choose a working session↓/ Live calendar · Research conversation
Choose a time. Bring one constraint.
A 30-minute research conversation about one market question, workflow or idea. We identify the next question and evidence worth examining. A detailed diagnosis or build is scoped separately.
Live availability from ceo@dotsuper.net Automatically converted · your local time
- 01Bring the operationOne real workflow is enough.
- 02Explore the fitIdentify what needs a closer look.
- 03Name the next questionAgree what evidence would help you decide.
Live availability
- Date
- Time
- Booked
Syncing live times
/ Applied AI research library
Case studies by dotSuper and its founders.
These founder-led case studies document how AI was applied in real business workflows. Each analysis preserves the reported outcome, operating context, human control and limits of the available evidence.
Explore the research libraryExplore the map
Shared operational challenges. Hover to pause. Drag to explore.
The globe revolves automatically. Hover or use keyboard focus to pause it, and leave to resume. Drag horizontally to rotate, or use the arrow keys. Home restores the overview. Plus and minus change the zoom. Location buttons focus the map on hover or keyboard focus. A tap provides a brief close-up.
FOUNDER-LED · PUBLISHED BY DOTSUPER · OUTCOMES NOT INDEPENDENTLY AUDITED
Forecasting and procurement
Mayur Farms
Four years of operating data turned into planning signals
₹6–6.5Lestimated annual labour saving
Read the evidence Website and lead generation
Infigo Research Laboratories
A discoverability and lead-qualification system for specialist expertise
~1 → 22website leads per day
Read the evidence Procurement
Defender Technologies
Supplier enquiries consolidated into a faster procurement view
2 days → hoursprocurement and supplier evaluation
Read the evidence / Got any questions?
Good. Ask the useful ones.
01Who is dotSuper for?+
Manufacturers and operating businesses with a workflow that should work better. We work with founders, functional leaders and the people closest to the process, including micro, small and medium enterprises.
02What can you build?+
Internal assistants, knowledge systems, document and review workflows, decision-support tools, customer and supplier workflows, and focused AI-enabled products. The exact form follows the work.
03How do we start?+
Book a 30-minute research conversation. Bring one market signal, workflow, recurring decision or early idea. We identify the question and evidence worth examining next. A detailed diagnosis or build is scoped separately.
04How is a research conversation different from the AI Readiness Sprint?+
The conversation is a no-fee first exchange about the market or the work. The paid 15-working-day sprint examines the workflow, people and available data, compares possible interventions and produces a documented recommendation, success measure and named owner.
05Do we need perfect data?+
No. We assess what exists, what is usable, what is missing and what a responsible first version can do. Data readiness is part of the work, not a prerequisite you must solve alone.
06Who owns the result?+
Ownership is part of the scope from the start. We agree what transfers to your team, where the system runs, who controls access and which third-party licences or services remain. Documentation and training are included in the agreed handover.
07What happens after handover?+
We agree the maintenance owner, recurring costs and support arrangements for the system. Further improvements can be scoped separately or through the Optimisation Subscription. Independence includes knowing when specialist support is needed.
08What if AI is not the right answer?+
The recommendation may be better records, a simpler workflow or a decision to pause. We explain the reason and the evidence needed to revisit it. A build is only useful when it solves the right problem.