Intelligence that finds the mechanism, not the pattern.

Point Askar at the questions that matter to your organisation. It finds out why — and keeps watching.

Request early access How it works ↓

FIG. 1— Your numbers look steady while a cause underneath is already moving.Illustrative

02The problem

Soon every organisation will run the same AI. The advantage is what you know.

Data tells you what moved — not why.

“Why” takes weeks and five figures, so it’s rarely asked.

And it’s out of date the day it lands.

03How it works

It works as a standing loop, inside your organisation.

Needs come from your people, your agents, or its own watch on the world. Askar agrees the plan, investigates, says what it could not establish, and delivers. Every use and challenge feeds the next turn.

FIG. 2— Needs in, intelligence out, and every challenge feeds the next turn.

04Why it holds up

See change before the numbers move.

Askar works to Systems Realism. Instead of mining patterns, it models the mechanisms that produce them.

FIG. 3— The cause moves first; your KPI follows. The gap is your early warning.Illustrative

See change coming.

Causes shift before numbers do.

Know when patterns break.

Nothing in the real world is a law.

Find what data can’t show.

Some causes never appear in a spreadsheet.

Every claim links to a named source. Every conclusion carries its confidence and its gaps.

05Examples · illustrative

Point it at anything.

MarketsWhere is the UK fitness market heading?01
ConsumersWhy are younger adults drinking less?02
BuyersWhy is spend leaving agencies for in-house teams?03
InvestmentIs the consumer sector splitting into winners and losers?04
PlacesWhich town centres could afford a digital visitor guide?05
RiskWhy does online panel fraud persist?06

FIG. 4— Different questions, shared causes. What Askar learns answering one helps the next.Illustrative

06It compounds

Intelligence that compounds.

Every investigation leaves behind causes it can reuse. One base you share in, one you own — and yours stays private to your organisation.

FIG. 5— Every question adds evidence, findings and causes. Your organisation’s part stays fenced off.Illustrative

FIG. 6— General knowledge flows into your base; your data never flows out.

07Where it sits

Askar supplies knowing.

Modelscapability

Agentslabour

Toolsaction

Dataraw input

Askarknowing

Your people use it directly. And it grows wherever it’s pointed.

08Early access

Request early access.

We’re working with a small number of partners. Tell us what matters to your organisation.

Founded by Francis Marsh, a research methodologist who worked inside the consumer research industry and developed Systems Realism to fix what it couldn’t explain. He builds Askar with a fleet of AI agents — the same kind of system it sells. · LINKEDIN ↗