Why finsait

The market needed something better.

The global cash-management software market is worth ~$13 billion and growing at ~15% a year — yet the largest players serve fewer than 2,000 clients each, implementations run into seven figures and 12–18 months, and mid-market teams are priced out entirely. The gap between what finance leaders need and what exists has never been wider.

The state of the industry

Most cash forecasts are wrong — at significant cost.

Not our claims — the industry's own numbers.

~60%

Typical accuracy of manual 13-week cash forecasts.

AFP 2025
1%

Share of organisations that hit 90% forecast accuracy at 30 days.

HighRadius 2024
72%

Of companies miss their free-cash-flow target by more than 10%.

EY-Parthenon 2024
76%

Of treasurers cite poor data quality as their biggest obstacle.

PwC 2025

Figures from published industry research; sources named per figure. We don't guarantee a minimum accuracy — every dataset is different, which is exactly why the pilot proves the value on your data before you commit.

The incumbent problem

Existing systems were built for a pre-AI world.

They're being retrofitted — and it shows.

Siloed by design

Traditional TMS and EPM stacks were built as separate tools. Cash, forecasting and risk live in different platforms — requiring manual reconciliation between them and making cross-module insight impossible.

Painful to implement

Enterprise TMS implementations routinely run 12–18 months and seven figures. By the time you're live, the business has changed. Mid-market teams are priced out entirely.

AI as an afterthought

Incumbents are racing to bolt AI features onto legacy architectures. The result is intelligence that doesn't connect across modules — a chatbot in the corner of a system that still can't see the whole picture.

How finsait is different

Started from a different place.

01

AI at the core, out to every edge

finsait was designed AI-first, not plastered on top. One intelligence layer runs from the core out to every edge of the loop — position, forecast, risk, decision. Models learn across your data, surface anomalies, and improve continuously. It's not a feature; it's the architecture.

02

One loop, not modules

Your position already knows your forecast; your forecast already knows your risk. There's nothing to reconcile, because there was never more than one source of truth.

03

Trust, by construction

Every number is traceable to its source, and every view can be reconstructed as it stood on any date. Decisions are saved with their full context attached. Built for the scrutiny of auditors, boards and regulators — not retrofitted for it.

04

Live in weeks, hands-on

No seven-figure implementation programme. We bring your data in together, models start learning immediately, and the loop is live from day one — with the team that built the platform doing the onboarding. We're building out bank and ERP connections as we onboard clients: your integrations are built with you, not sold at you.

Security & privacy

Built to hold your most sensitive numbers.

Treasury data is the crown jewels. The foundations are not negotiable.

Tenant isolation

Every client's data is isolated at the database layer with row-level security — enforced by the platform, not by convention.

EU hosting, GDPR native

Hosted in the EU on Google Cloud. GDPR compliance designed in from the first line — see our Privacy & Data Policy.

Enterprise authentication

Auth0-backed sign-in with invite-only access during the pilot phase. Encryption in transit and at rest.

Your data stays yours

Client data is never shared. Future benchmarking uses anonymised, aggregated ratios only — always opt-in.

Built for treasury teams across sectors

Cash is cash in every industry. The band below is the full global sector taxonomy — not a shortlist.

EnergyMaterialsIndustrials Consumer DiscretionaryConsumer Staples Health CareFinancials Information TechnologyCommunication Services UtilitiesReal Estate
Who's behind finsait

Built by people who turn models into decisions.

MM

Marcus Martinsson

Founder & CEO

M.Sc. Theoretical Physics. Over 20 years in strategy consulting, leading data-science and financial-intelligence programmes in executive and senior roles at Accenture, NTT and PwC — focused on translating quantitative models into direct P&L impact for finance and treasury teams. One of his finance-analytics innovations earned an acknowledgement at the Adam Smith Awards, corporate treasury's most prestigious industry recognition.

Founding clients

Judge it on your own numbers.

Test the engines in your browser, visit our playground to walk the real platform, or join the pilot and see the loop run on your data.