The AI Data Foundation

AI is only as strong as
the data behind it.

Most AI initiatives fail on the data underneath, not the model on top. We build the part it stands on — the foundation that gets your use cases into production and keeps them there.

01
Who We Are

A boutique specialist,
not a generalist.

Data Century builds the AI data foundation for regulated industries. Most AI initiatives fail on the data underneath, not the model on top. We build the part AI stands on — the foundation that gets use cases into production and keeps them there.

Regulated industries
Banks, insurers, and Crown corporations, where the data has to be right.
Senior specialists
Consulting, industry, and data and AI engineering — the people who scope the work deliver it.
Canada and the US
Established in Canada, building in the US market.
02
The Foundation

Your data foundation for AI.

Three layers, built in concert. Each one depends on the others, so we build them together — use case by use case — turning raw data into something AI can act on and the business can measure.

01
The Data Layer
Make the data available. ✓
The right data flowing reliably to where AI and the business need it.
02
The Trust Layer
Make the data dependable. ✓
Every number traceable, governed, and defensible.
03
The Value Layer
Make the data useful. ✓
Trusted data turned into measurable outcomes and AI use cases.
03
Data Layer
The Data Layer
Make the data available. ✓

Platforms, pipelines, and data products that get the right data flowing reliably to where AI and the business need it.

Without the foundation
With the foundation in place
Without the foundationA new data source takes months to reach production. Every use case starts from scratch.
With the foundation in placeNew sources are ready in days. Pilots launch and scale faster.
Without the foundationThe data team spends its time moving and preparing data by hand.
With the foundation in placeAI use cases reach production instead of waiting on manual data prep.
Without the foundationAn upstream change breaks a downstream report or model with no warning.
With the foundation in placeBreaks are caught early. If one slips through, you trace it in seconds.
04
Trust Layer
The Trust Layer
Make the data dependable. ✓

Governance, ownership, lineage, quality, and controls that make every number traceable and defensible.

Without the foundation
With the foundation in place
Without the foundationNo one owns the data. Quality issues get patched every cycle, never fixed.
With the foundation in placeClear ownership. Issues get fixed once, at the source.
Without the foundationThe business does not trust the numbers, so AI outputs get checked by hand.
With the foundation in placeThe numbers hold up, so AI outputs can be acted on directly.
Without the foundationA regulator asks where a number came from. Finding out takes days.
With the foundation in placeAny number traces to source in seconds.
05
Value Layer
The Value Layer
Make the data useful. ✓

Shared business definitions, semantic models, and priority AI use cases that turn trusted data into measurable outcomes.

Without the foundation
With the foundation in place
Without the foundationAsk how many clients you have. Five systems, five answers, all technically correct.
With the foundation in placeOne definition per metric. AI agents and people get the same right answer.
Without the foundationNo one can use the data without an analyst to interpret it.
With the foundation in placeA business user asks an AI chat and gets the answer, or the report builds itself.
Without the foundationEvery AI use case starts from zero. Nothing carries over.
With the foundation in placeProven patterns get reused. Each use case ships faster than the last.
06
The Payoff

Where this takes your business.

The measurable change once each layer is in place.

01 — Data Layer
10x
less manual data movement, once the pipelines run themselves
Days
from new source to usable data, not months
02 — Trust Layer
Seconds
to trace any number to its source, down from days
80%
less time chasing and reconciling bad data
03 — Value Layer
1
definition per metric, the same answer from every system
0
conflicting answers — ask twice, by anyone or any agent, get the same one
07
How We Work

Specialists in the AI data
foundation, not generalists.

01
We bring the use cases, not just the technology.
We bring the highest-value AI use cases for your business and work backward from there to the gaps standing in the way. A direct line from a business outcome to the work that unlocks it.
02
We build in the right sequence.
Available, then dependable, then useful. Each layer laid so the next one holds — the difference between an AI foundation and a pile of tools that never quite work together.
03
Senior specialists, start to finish.
The people who scope your work are the people who deliver it. Deep specialists in regulated data and AI foundations, not a pyramid of juniors learning on your programme.
08
What It Enables

What becomes possible
when the foundation holds.

AI use cases that survive contact with production.
AI-enabled workflows your team actually trusts.
New data sources in days, not months — the next use case starts faster than the last.
Agents that act on your business, with answers everyone agrees on.
Reporting that stops arguing about whose number is right.
09
In Practice

Running in financial
services today.

Compliance · Operations
AML false positive reduction
Compliance teams stop reviewing thousands of alerts that lead nowhere. Models fed by clean, consistently defined data flag real risk. People investigate it.
Client Onboarding
Automated KYC onboarding
New clients onboarded in hours with a defensible audit trail — not weeks of manual chasing across systems with five different definitions of the same client.
Regulatory · Reporting
Regulatory reporting, automated
Every number traced to source automatically. No manual adjustments before the cycle runs. A regulator asks where a figure came from — you answer in seconds.
Automation · AI
Agentic workflow automation
AI agents that act without a human resolving conflicting definitions first. The automation that was supposed to remove manual steps actually does.
10
Leadership

Led by people who've
done this at scale.

Senior specialists who scope your engagement and stay on it.

Yasser Nabavi
Yasser Nabavi
Founder, CEO & Managing Director

Founder of Data Century. More than fifteen years leading data governance, data management, and analytics delivery for regulated organisations across financial services, public sector, healthcare, and energy. Previously a data lead in Deloitte's Risk Advisory practice, serving major Canadian banks on regulatory, AML, and risk data aggregation programmes.

Salman Malik
Salman Malik
Managing Director, Canada

Managing Director for Data Century in Canada, leading semantic layer and value realisation work. Most recently Vice President of Canadian Banking Analytics at Scotiabank, leading a 140-plus person team and delivering $140MM+ in annual revenue benefits through personalisation, pricing optimisation, and automation. Formerly a Partner in EY's Strategic Transformation practice and a leader at Accenture and Deloitte.

Ben Harding
Ben Harding
Managing Director, US

Leads Data Century's US business. More than twenty years across markets and consulting, focused on turning AI investment into measurable value. Previously led the Finance, Risk, and Compliance practice at a global consultancy, delivering enterprise Basel III and RCSA programmes for global banking clients. A regularly published author on capital markets, risk, AI, and compliance.

11
Next Step

Assess your data foundation.

01We start with a use case you care about — one that matters to the business.
02We map your foundation against it — data, trust, and value layers.
03You get a clear read on what stands between your platform and production-ready AI.
Assess your data foundation