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About Insight Centric

A technology-led advisory practice for AI enablement in financial services.

We rebuild operating models around AI as a native capability. Workflows redesigned from first principles. Data layers re-architected for action. Decision rights, governance, and roles redrawn for the new production function. Audit-ready in regulated environments.

FTSE 100
The institutions we are built for
15+
Years senior practitioner experience
5
Enablement pillars in every engagement
24-36 mo
Realistic transformation arc
What We Do

We are built for the structural work most firms avoid.

Most enterprise AI work today is augmentation — copilots, chatbots, pilots layered onto workflows that were designed for humans. The gains are real and they don't compound. The institutions that will lead financial services in 2030 are the ones rebuilding their operating models around AI now.

Insight Centric exists to do exactly that work. We are a technology-led advisory practice — not a generalist consultancy, not a process improvement firm, not an AI vendor — focused on the structural redesign that makes AI compound: the production function, the data layer, the decision systems, the operating model, and the governance machinery that holds it all up under regulatory scrutiny.

Our practitioners have led operating-model redesigns, regulated AI deployments, and enterprise data programmes inside FTSE 100 banks, large insurers, and asset managers. We have built data layers from scratch, designed three-lines-of-defence governance for AI under PRA SS1/23, redrawn decision rights matrices for credit and KYC workflows, and embedded model risk operations into the cadence of production deployments. We know where the trapdoors are.

The work is hard, the timelines are long (24–36 months for serious enablement), and the compounding advantage takes years to build. That is exactly why we do it — and why the firms that start now will be impossible to catch by 2030.

Practice Areas

Five interlocking pillars. One operating system.

Every AI Enablement engagement is built around the same five pillars. We sequence them based on where your binding constraint sits — but the pillars do not work in isolation. The whole point of compounding is that they reinforce each other.

Production Function Redesign

We rebuild operational workflows around AI as a native capability. Not augmentation. Not bolt-on. The unit of change is the workflow itself, mapped in BPMN 2.0 and re-architected from first principles for continuous information processing.

Data Layer Architecture

We design action-data layers that automated systems can reason about: captured at the point of action, standardised at capture time, structured around the workflow rather than the report, observable in production with column-level lineage.

Decision Systems & Feedback Loops

We instrument the data flywheel — override capture, structured feedback curation, continuous retraining, decision logs queryable on demand. The compounding mechanism that turns operational data into a moat.

Operating Model & Talent

We redraw decision rights, redesign roles for system supervision and exception handling, and rebuild performance metrics for the new manager archetype. The work most consultancies skip — and where the value actually lands.

Governance & Model Risk

We embed governance into the workflow rather than bolt it on at gates. Three-lines-of-defence design for AI, decision logs as evidence, and continuous alignment to EU AI Act, PRA SS1/23, FCA SYSC, and DORA expectations.

Technology Stack

The tools we actually use

We are vendor-agnostic on principle but technically opinionated in practice. The stacks we work in across data, ML, workflow, and observability:

Python · PyTorch · scikit-learn
OpenAI · Anthropic · Mistral
BPMN 2.0 · Camunda · bpmn.io
Snowflake · Databricks · BigQuery
dbt · Airflow · Dagster · Prefect
OpenLineage · DataHub · OpenMetadata
Monte Carlo · Bigeye · Great Expectations
MLflow · Weights & Biases · Vertex AI
Streamlit · Retool · Hex

We recommend whatever tooling fits the redesign. We have no commercial alignment with any vendor and no licences to sell.

Who We Serve

Regulated industries, end-to-end

Our practice is concentrated in regulated industries where the structural opportunity is largest and the governance bar is highest. Financial services is our deepest expertise, but the same structural framework applies in healthcare, life sciences, energy and utilities, and the public sector — and the regulatory frame, the value streams, and the failure modes are tailored to your sector in every engagement.

Financial Services

Banking, insurance, asset management, wealth & private banking, capital markets, and payments. Operating under PRA SS1/23, FCA Consumer Duty, MiFID II, AIFMD, Solvency II, PSD2, and the EU AI Act. Six dedicated sector pages cover each value-stream pattern.

Healthcare & Life Sciences

Hospital systems, integrated health networks, payers, pharmaceutical and biotech companies, and medical device manufacturers. Operating under MHRA, FDA, EMA, ICH GxP, HIPAA / GDPR, CQC, EU AI Act, and EU MDR / IVDR. Validation and clinical governance treated as engineering constraints, not downstream checks.

Energy & Utilities

Grid and system operators, transmission and distribution networks, generators, retail energy suppliers, and water utilities. Operating under Ofgem, FERC, NERC, ACER, and the relevant safety-case frameworks. Reliability of supply and physical safety treated as first-class constraints.

Public Sector

Government departments, regulators, executive agencies, and large public service providers. Operating under the UK Government AI Playbook, the Algorithmic Transparency Recording Standard, the EU AI Act high-risk obligations, GDPR / UK DPA, and the equality duty. Accountability and public-law defensibility built into the design from day one.

How We Are Different

Six things that set us apart

We do not look like a traditional consultancy because we are not one. Here is what changes when you engage us.

Technology-Led, Not Slide-Led

Our practitioners build, instrument, and operate AI systems — we are not slide-builders. We work in BPMN modellers, dbt projects, model registries, and observability stacks because that is where the work actually lives.

Senior Practitioners on Every Engagement

No off-shored deck-builders. The people in the room are the people doing the work. Every engagement is led by practitioners with 15+ years of operating-model and technology delivery experience in regulated environments.

Regulatory Fluency Built In

EU AI Act, PRA SS1/23, FCA SYSC, Consumer Duty, DORA, BCBS 239, three-lines-of-defence, and model risk management are not addenda to our work — they shape the workflow design from day one.

Embedded Delivery Model

We embed alongside your operations, technology, and risk teams as practice partners — not external reviewers. Knowledge transfer is built into the engagement structure so the capability stays after we leave.

Workflow-Native, Vendor-Agnostic

We do not sell licences and we have no commercial alignment with any AI vendor or platform. The unit of change is the workflow, not the technology — we recommend whatever tooling fits the redesign.

Compounding by Design

Every engagement is structured to produce a reusable foundation — data layer, governance machinery, role design — that the next workflow inherits. The first project is the proof. The second project starts halfway built.

Monthly newsletter

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If our positioning resonates and you want to see the ideas applied in practice, subscribe to the monthly essay. One long-form piece per month on AI enablement, embedded governance, and operating-model redesign in regulated industries.

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Ready for a senior conversation about AI Enablement?

Start with an executive working session — 90 minutes, no deck, no pitch. We use the time to understand your operating model, your AI ambition, the binding constraints, and whether AI Enablement is the right conversation now, or whether something more focused is the right next step.

Or read the pillar essay: What AI Enablement Actually Means