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AI for Finance

System Integration

The ledger has the postings, the billing system has the contracts, the payment processor has the settlements, payroll has the headcount, and the real explanation for last month’s margin lives in a spreadsheet on someone’s desktop. None of them agree on what a customer is called. So a question that should take a minute — what did this account actually cost us to serve — takes an afternoon of exports and a VLOOKUP that someone will have to rebuild next month.

Skynet puts them in one place. Connectors read the live systems, unified memory reconciles the entities across them, and you ask the question in plain language instead of assembling the answer by hand.

How it works

step 01

Connect the systems

Point Skynet at the tools you already run finance on. Connectors read them live, so what you are asking about is the current state, not a snapshot from whenever someone last exported.

step 02

Resolve the entities

The agent works out that the customer named three different ways across three systems is one customer, and holds that mapping in unified memory. That reconciliation is the work everyone does by hand and nobody documents.

step 03

Ask across everything

Questions stop respecting system boundaries. Ask about revenue by cohort, or cost to serve by account, and the agent assembles the answer from wherever the pieces live rather than making you find them first.

step 04

Check the answer

Every figure cites the system and records it came from. You can trace any number back to its source, which is the difference between an answer you can act on and one you have to verify from scratch.

Build it from a prompt

Describe what you want visible.

The gain is not a dashboard. It is that questions stop being projects. Ad-hoc analysis becomes something you do while thinking rather than something you schedule, and because every number is traceable, you can defend the answer to whoever asks where it came from.

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