AI Initiative logoAI Initiative

AI InitiativeThe architect

Research · Architecture · Building

Kulbir Minhas.

From data and decisions
to intelligence that grows.

My work has moved through data, research, products and systems for intelligence working together. AI Initiative is where I pursue what comes next.

The evolution of humans and AI

From tools to peers,
growing together.

AI is changing what it can be for people. The question I care about is how that evolution can stay a partnership, with each side making the other more capable.

  1. Before

    Tools

    AI waited for instructions and did one task.

  2. Today

    Assistants

    AI responds, drafts and suggests, then forgets.

  3. Next

    Peers

    AI that remembers, learns from outcomes and grows with the people it works with.

How the partnership works

  • People bring purpose, values and judgement.
  • AI brings memory, reach and tireless checking.
  • Every outcome teaches both: people decide better; AI learns what matters.
  • Over time the partnership becomes more capable than either alone.

This is co-evolution: human and machine capability rising together. I measure success by what people can now do.

Explore the full vision ↗

Experience that connects

A journey with
more than one thread.

From client work and visualising risk to R&D, product leadership and AI architecture. Some roles ran alongside one another; the timeline keeps those connections visible.

Career at a glanceAs of October 2026 · select a track to explore

AI Initiative began in January 2024 and the Fifth9 role in May 2024; the Insight Delivered CTO role continued until June 2024. Client BI projects for Context BI, RSA and Canopius were part of the Insight Delivered roles.

2001–2013 · Data and decisions

Make information
useful to people.

Early work spans TCS client work for NSE, client and contract work for Morgan Stanley, BI and ETL roles, and advanced visualisation at Credit Suisse.

These are the data and decision-making foundations of the journey: integrating information, making complex subjects understandable and supporting people working with it.

Data integration · Business intelligence · Risk visualisation

2013–2024 · Research and product leadership

Bring research
into working systems.

I co-founded Insight Delivered and progressed from Director R&D to CTO. The work included technical direction, global teams and the development of AI and machine-learning products such as AutoML, DeX and Strategic Finance.

Client projects within those roles included Qlik work through Context BI and BI strategy, architecture and Centre of Excellence programmes for RSA and Canopius, connecting product work with client settings.

R&D · Product development · Technical leadership
The complete career recordRoles, settings and dates—including the overlapping work
  1. 2001–2003

    Client work for NSE

    TCS

    Client work for the National Stock Exchange.

  2. 2003–2008

    Client and contract work

    Morgan Stanley

    Financial-services client and contract work.

  3. 2009–2012

    BI and ETL roles

    Project Brokers · Zensar Technologies · Unipro

    Business intelligence and data integration roles.

  4. 2012–2013

    AVP, Advanced Visualisation

    Credit Suisse

    Basel III risk visualisation.

  5. Apr 2013–Jun 2024

    Co-Founder · R&D Director → Chief Technology Officer

    Insight Delivered

    Co-founder. Director R&D: Apr 2013–Sep 2021. CTO: Sep 2021–Jun 2024. Technical direction, global teams and AI/ML product development, including AutoML, DeX and Strategic Finance. Client projects: Qlik work through Context BI for Nationwide/Kofax, Morgan Stanley and HSBC (2013–2017); BI strategy, architecture and Centre of Excellence for RSA (2017–2019) and Canopius Group (2020–2023).

  6. Jan 2024–present

    Founder & AI Scientist

    AI Initiative Ltd

    Independent learning research, poker and Matiz, games and writing.

  7. May 2024–present

    Principal Data Scientist

    Fifth9

    Based at HSBC, in Developer Experience. I architect Conduir, an agentic, multi-agent AI architecture in which people and AI agents work together. It composes models and tools for each task, keeps memory that outlasts any single model (Cortex), maps how complex systems fit together (GraFOSa), explores ideas through many perspectives (Manthan), and turns each reviewed outcome into experience for the next piece of work. It grows out of my earlier Maestro work and points towards AI as a continuing peer that grows with people.

Education

MTech, Hydraulics EngineeringIIT Roorkee · 2001

B.Tech, Civil EngineeringNIT Calicut · 1997

Two current settings

The vision finds
different forms of work.

AI Initiative is my independent lab. At Fifth9, I architect systems for intelligence working together. Both inform my perspective, with each organisation’s work clearly attributed.

JANUARY 2024–PRESENT

AI Initiative

Founder & AI Scientist

An independent home for a larger vision: intelligence that grows with people. The work includes modular learning, poker and Matiz, games and writing.

Games are the current route to market. The wider direction remains open to other ways evolving intelligence could help people learn, create and act.

MAY 2024–PRESENT

Fifth9

Principal Data Scientist

Based at HSBC · Developer Experience

I architect Conduir, an agentic, multi-agent AI architecture in which people and AI agents work together. It composes models and tools for each task, keeps memory that outlasts any single model (Cortex), maps how complex systems fit together (GraFOSa), explores ideas through many perspectives (Manthan), and turns each reviewed outcome into experience for the next piece of work. It grows out of my earlier Maestro work and points towards AI as a continuing peer that grows with people.

Conduir Spatial adds shared environments. The scope and development of each contribution are described in the work map.

The habit running through the journey

Stay ambitious.
Keep questioning.

I care about ambitious questions and the patient work of testing them. Progress becomes useful when another person can understand the reasoning, question the result and carry the learning forward.

How the work is approached ↗
  1. 01

    What did we expect?

    Make the purpose and the question clear enough to examine.

  2. 02

    What actually happened?

    Look at the work, invite another perspective and take unexpected results seriously.

  3. 03

    What should change?

    Keep the useful lesson and give the next attempt a better starting point.

The path ahead

From AI that answers
to AI that grows with people.

The path I’m taking: from AI that answers to AI that grows with people, and from building systems to shaping how humans and AI evolve together.