AI native specialty finance platform
FactorFox is an AI native operating system for specialty finance: invoice factoring, asset based lending and purchase order finance on one platform, built from more than twenty years of running factoring operations and on a real double entry general ledger.
It briefs each person on what they are responsible for, shows the evidence behind every answer, watches risk, funding and covenants continuously, and stays model agnostic, so it keeps getting better as the models do.
Two architectures
Same demo, different buildAI enabled
A model is connected to the software.
It is handed a question and some context. It can summarize, draft and answer.
AI native
The intelligence is part of the operating system.
It works from the ledger, applies the policy in force, and refuses to show a change it cannot prove.
And underneath both
The model is the engine. It should be replaceable without replacing the vehicle.
What AI native means here
Each of these is in the product today, and each opens onto its own page. Integration status is stated where it applies.
The first screen
AvailableA dashboard waits for somebody to know what to look for. A FactorFox briefing is written for the person reading it, from what that person is responsible for, and answers the questions a factoring operation asks every morning before anyone has to ask them.
How briefings workActionable Intelligence
AvailableEvery conclusion opens onto the records, the policy that applied and the reason it was reached, then points the person responsible to the next step. An answer that cannot show its evidence is not shown as an answer.
Intelligence with evidenceEvery day, not every month
AvailableDebtor deterioration, concentration, dilution, aging and funding activity are watched as the book moves, and a change that matters reaches the person who owns it with the evidence attached.
Risk monitoringYour lender's terms
AvailableFacility limits, concentration, eligibility, advance rates, reserves and reporting obligations are monitored against the covenants you record, with days to breach on the current trajectory. It supports your judgment and your lender relationship. It does not replace either.
Covenant monitoringWhere decisions already happen
Controlled releaseBriefings, signal cards and approvals arrive in Teams. Releases, overrides and exceptions are approved or refused from the card, with four eyes and facility guards enforced exactly as they are in the browser.
Microsoft TeamsA book you can walk back
AvailableEvery advance resolves to the invoice it funded, the client agreement term it was made under and the facility limit it had to respect. A receivables book that can walk that chain on demand audits itself, which is a different thing to hand a lender than a certificate rebuilt at month end.
Borrowing baseUnderwriting that does not stop at onboarding
AvailableA client is re underwritten when something material happens, not once a year. Each run is versioned, and the platform can stop money on its own authority while only a named person can release it.
Continuous UnderwritingThe financial foundation
AvailableFactorFox runs on a true double entry general ledger that has carried this business since 2002, so every figure the intelligence reports is a figure the books already agree with.
AccountingIndependent of any one model
AvailableFactorFox is model agnostic by design. The model doing the work is a configuration decision rather than an architectural one, so when a better model ships the platform can adopt it, and when a provider has a bad afternoon your funding day does not.
Why model agnostic mattersAI native versus AI enabled
AI enabled means a model is connected to the software. It is handed a question and some context. It can summarize, draft and answer. What it cannot do is see the ledger the way the ledger sees itself.
AI native means the intelligence is part of the operating system. It works from the same records as the ledger, applies the policy that was in force at the time, and refuses to display a change it cannot prove. That is why a conclusion here opens onto its own evidence rather than onto a restatement of itself.
Read how the other platforms in this category describe themselves and you will find AI powered, AI assisted, AI enabled and AI automation. Those are accurate descriptions of capability added to a system designed before the capability existed. We are not aware of another factoring platform that describes itself as AI native.
The test
Ask any vendor to show you the evidence behind a conclusion the software reached on its own.
Software with a model attached will show you the answer again, worded differently. Software with intelligence in the architecture will open the records, the policy that applied and the reason it was reached.
One platform, three kinds of lending
The briefings, the evidence and the monitoring are not a factoring feature. They run the same way across every product a specialty finance company offers.
Funding, verification, collections and client reporting, with every advance traceable to the invoice and the agreement term behind it.
Borrowing base availability computed from live collateral, and covenants watched as the book moves rather than at the monthly certificate.
Purchase orders, supplier payments and the receivables they become, held on one record so exposure is visible from order to collection.
Model agnostic by design
Then · the cloud
You did not buy factoring software. You bought factoring software for Windows, and inherited the upgrade cycle and the migration that came with it. The cloud made the application independent of the operating system underneath it.
FactorFox moved on that in 2002, as the first cloud platform built specifically for factoring companies.
Now · AI native
A platform built around one model family inherits that family’s roadmap, pricing, licensing terms, deprecations and outages. The dependency is invisible while the model is good and expensive the moment it is not.
FactorFox is model agnostic. Same architectural bet, made twice, twenty four years apart.
What it looks like when it is real
Every client agreement already contains the operating rules for that relationship: the advance rate, the fee schedule, the discount terms, the reserve and the concentration limit. Typed in by hand, a transcription error becomes a funding error four months later.
Give FactorFox the executed agreement and it reads the terms, including the fees and the discount schedule, and sets the client up against them, with the clause each term came from attached to it.
Agreement read into terms
In the productEvery configured term keeps a link to the sentence it came from, so a disagreement about what was agreed is settled by opening the clause rather than by memory.
How to check any of this
Start with the integration register, where every connection carries a status word and the vendors we do not connect to are named as well. On accounting, FactorFox holds 2 accounting integrations, QuickBooks Online and Xero, both available, on the double entry core underneath.
On security, we publish where we actually are rather than a badge. A SOC 2 program is in progress, and there is no certification claim anywhere on this site until a report exists. Our security position says so plainly, and how to choose sets out the questions worth putting to any vendor, including us.
Straight answers
Factoring software where the intelligence is part of the operating system rather than a model connected to it afterwards. It reads the same records the ledger reads, applies the policy that was in force at the time, and shows the evidence behind every conclusion. FactorFox describes itself this way, and we are not aware of another factoring platform that does.
No. The same platform runs invoice factoring, asset based lending and purchase order finance, including borrowing base monitoring and covenant monitoring for asset based lenders, on one ledger and one record.
The opposite. The platform is built to use them and to keep using better ones. Which model does the work is a configuration decision that can be revisited whenever a better option ships, rather than a dependency the product inherits.
No, and the asymmetry is deliberate. The platform can stop money on its own authority. Only a named person can let money through. Four eyes applies by default, and every conclusion opens onto the evidence that produced it.
Ask the software to show the evidence behind a conclusion it reached on its own. Software with a model attached will show you the answer again, worded differently. Software with intelligence in the architecture will open the records, the policy that applied and the reason it was reached.
Related
Send a slice of open receivables and a client agreement. We will show you what the first briefing says about your book, read the agreement into terms in front of you, and tell you plainly what we could not see and why.