From spending on AI
to earning from it

We build the AI product engine for insurers and financial institutions — turning market signals into launched products in days, with revenue from week one.

The market has changed.
AI hasn't paid off yet

Shrinking margins

Markets are slowing, and clients demand more — more personal, faster, cheaper. Growth no longer comes on its own. It has to be earned, through new products and sharper operations.

Built without the business

The platform gets built by IT, in isolation from the people who are supposed to earn from it. Tools, agents, dashboards — delivered to a business that was never in the room. Two years later the gap is still there, and the revenue impact is still zero.

The double bind

The market wants results faster than ever. AI promised to deliver them. Yet real AI ROI is still 0% — the pressure climbs, the budget is gone, and nothing has actually changed.

A product should be a reaction to an event

Not a plan researched for months and launched after the moment has passed. An event happens — and the product is in the market in days, not months. That's the shift this whole engine is built around.

AI Growth Lab — strategic product decisions in 6 hours, not 6 months

One engine, three stages. A market event goes in. A launched product comes out.

market event
01

Product Generation

An AI agent pipeline scans market signals, generates product hypotheses, and stress-tests them before anyone commits a budget.

Scout Idea Generator
Critic Product Manager
Output A validated product brief, ready for launch.
02

Consumer Validation

We model the market's reaction before the product exists. Synthetic buyers — built on demographics, financial literacy, trust, and formalised cognitive biases — cluster into segments and respond, with a full audit trail behind every decision.

Output Adoption likelihood by segment, barriers, willingness to pay, and misselling risk.
03

Distribution

The validated brief loads straight into your agent sales network: sales bot, live product database, quotes, AI-generated scripts, real-time coaching. Agents are ready from day one.

Output Product in market, agents activated, revenue from week one.
product out

Three layers under the engine

Each layer works on its own. Together, they compound.

01 AI Agents

Specific tasks, immediate ROI. Ready-made agents solving concrete business problems, deployed in your environment and measured from day one.

×50 faster product ideation
02 Agent Platform

Your own AI factory. An orchestration platform your team runs internally — building and managing new agents without calling us for every use case.

5–10× faster launch · 40–60% efficiency gain
03 AI Culture

A self-sustaining innovation engine. Trained champions in every unit, a live initiative pipeline, a governance committee — so innovation keeps running after we leave.

10+ initiatives per unit per cycle

Proven with a leading insurance group

One pilot agent. Then eight more. Here's what changed.

~$12.4M/year
total direct economic impact
×6
TAM expansion
8 agents
deployed in Phase 2
Stage Before After Acceleration
Idea selection ~6 weeks ~1.5 hours ×30–40
Product validation ~3 months ~3 weeks ×3–5
Pilot preparation ~6 weeks ~2 weeks ×3
"Let's start with one agent, evaluate the impact, and then expand our funnel with additional initiatives."
Leadership team, Change Division — leading insurance group

Why CirkaFlow

The buyer's intuition, encoded

Our model belongs to someone who spent 30+ years selling insurance — from frontline sales to Deputy CEO. He knows the buyer because he was the buyer. With every engagement, the model sharpens.

"He knows the buyer because he was the buyer."

We leave a way of thinking

Most AI programs get built by IT and handed to a business that never learned to think in AI. We do the opposite: your people leave knowing how to spot where AI earns its keep — long after the engagement ends.

"We don't leave a tool. We leave a way of thinking."

Delivery, not decks

We know how to make AI profitable. Measurable, scalable, last-mile business impact — not another pilot that ends in a report.

It stays yours

Your team operates without us. No lock-in, no dependency — the engine, the agents, and the people who run them remain inside your organization.

A methodology built by an insider

Our 13-step product framework rests on 30+ years of enterprise product launches in financial services and insurance — stress-tested on real decisions, not a generic consulting playbook.

Enterprise-grade by default
GDPR ISO 27001 SOC 2

On-premise or cloud.

The Execution Layer

Behind the engine: the architects who build it

The founders know the insurance buyer. A different layer of the team makes sure what we promise actually gets built — enterprise architects with deep banking and financial-domain experience, the people who turn an AI strategy into a system that runs in production.

Chief Information & Data Officer

25+ years in enterprise IT, 15+ at C-level. Built corporate-architecture and data-governance functions inside a national stock exchange and led MLOps that put machine learning into live insurance processes. Hands-on with AI agents, RAG, and model monitoring.

Financial markets Insurance ML in production Enterprise data strategy
Chief Enterprise Architect — Banking

10+ years inside banks and financial institutions. Built architecture practices from scratch, led core-banking modernization and M&A system integration across six financial organizations.

TOGAF 9 CESAMES (EQF Level 7, Paris)
Lead Enterprise Architect

Runs discovery and target-architecture programs end to end — from IT-landscape survey to a multi-year roadmap defended at board level.

TOGAF PMP ITIL
Advisory & Delivery Lead

Executive advisory and delivery oversight: data governance, methodological rigor, and quality control on every deliverable. Hands-on experience across the GCC region.

Executive advisory Data governance GCC delivery

Ready to run a pilot?

Start the way our clients do — with one agent and a clear ROI question. Prove the impact, then scale on your terms. No lock-in, no enterprise-wide commitment up front.