We do not have a product catalogue. We have a point of view — that intelligence, and the capability it creates, should not be rationed by the size of an organisation's budget or the accident of geography. Everything we build is an expression of that point of view. The form changes. The purpose does not.

01 — Enterprises

Accelerating the journey to AI-enabled.

For the institutions that move capital and manage risk at scale — banks, insurers, NBFCs — we build the intelligence infrastructure that makes AI-enabled decisioning real, not aspirational. Sherlock, our model risk platform, and Lumina, our AI analytics layer, sit at the core of this work.

The rigour is regulatory-grade. The timelines are honest. The results are in production.

Sherlock Model risk management and validation platform. Built for financial institutions operating under regulatory scrutiny.
Lumina AI-native analytics layer. Connects raw data pipelines to decision-ready intelligence across enterprise operations.
See enterprise case studies →

02 — SMEs

Making you AI-native, not AI-aspirant.

The mid-sized company — manufacturer, platform operator, regional lender — has always been told that enterprise-grade AI is not for them yet. We disagree. We build bespoke platforms that make the SME AI-native before their larger competitor realises what has happened.

The engagement that delivered autonomous operations for a global chemical manufacturer in the USA began with a single question: what would it mean if the plant could decide for itself? That question is the right starting point.

Our SME engagements are not software licences. They are built-to-purpose intelligence systems, integrated into existing operations, owned by the client from day one.

IoT analytics, digital twins, credit decisioning, fraud detection — the domain varies. The standard of work does not.

03 — MSME & Vriddhi

Vriddhi

The trust graph of neighbourhood commerce has never been made visible. The merchant knows her customers — their preferences, their cadence, their loyalties — in a way no algorithm has been asked to understand. Vriddhi is built to change that.

The central player in Vriddhi is the merchant. Not the platform, not the aggregator, not the algorithm. The merchant. Her customers belong to her — their data, their preferences, their buying patterns — protected by design and owned by right.

Enterprise-grade capability now belongs to the corner shop. A trust graph that learns. A mini-ERP that does not require a training budget. DPDP-compliant from the first line of code. Built in Bangalore. Ready for every market where the same gap exists — which is to say, everywhere.

Why we built Vriddhi →

04 — Governments

Policy grounded in intelligence, not assumption.

Governments make decisions at a scale where the cost of assumption is measured in millions of lives. Capability research, policy analytics, and capability inclusion at national scale — these are not vendor engagements. They are partnerships in building what did not exist before.

We work with governments to ensure that policy is built on intelligence — rigorous, independent, and designed to hold up under scrutiny.

Ckuens is not a vendor to governments. It is a partner in building national capability. That distinction shapes how we engage — from the quality of our analysis to how we structure the conversation at the beginning.

The most valuable intelligence is the kind that tells you what you did not know you did not know.