AI agents for finance, built on trust
You can hand the operational work around billing to an agent without giving up trust in the numbers. The calculation stays deterministic, and a person signs off before anything runs.
The foundation
Everything in finance rests on trust. A billing and order to cash tool can look the part and move fast, but an invoice that's 95% right is a wrong invoice, and one wrong number can cancel out everything. Mistakes aren't an option, so every agent we deploy has to be safe and can't introduce errors of its own. That is why the billing engine stays deterministic underneath them.
What you hand to an agent
Inside Sequence, agents take on the manual side of billing. They chase missing inputs, send follow up on late payments, flag anomalies, help amend invoices, answer billing queries and more. These are routine tasks that run on context the revenue system already holds, which is what makes them the right work to hand to an agent. A person still makes a judgment on each task in Watchtower before an agent proceeds.
The one place agents don't go
An agent never touches the calculation of what a customer owes. LLMs are probabilistic by design, predicting the most likely output rather than computing a fixed one, so the same request can come back slightly different from one run to the next. You need 100% billing accuracy month on month, and the numbers have to hold up for everyone who relies on them.
So the billing engine underneath needs to be deterministic. Every charge is worked out step by step, traced back to the contract, and it is formulaic and comes out the same every time. Feed it the same inputs and you can reconstruct exactly how it got there, which is a stronger promise than being able to audit it after the fact. The agents work around the billing engine, never in it, so they can speed things up without ever putting the number at risk.
How agents are run
When the system is turned on for an agent, it's sandboxed to a single workflow with access only to the data that workflow needs. There's no opportunity for it to look at another account or reach data outside that particular workflow. We set out exactly what each agent can and can't do, and getting that boundary right is what stops an agent becoming a new source of error.
Nothing runs without a human
Every action an agent wants to take goes through Watchtower first, the human-in-the-loop interface for agents. The agent lays out what it plans to do, its reasoning and the decision behind it, and someone on your team either approves it or sends it back. Nothing moves until a person gives the go-ahead. The agent prepares it, the human keeps final control. Jobs that would take a team days by hand can clear overnight.
Agents carry the load, the engine does the math, and Watchtower records each action and who approved it. This is automation you can put in front of your board and your auditors, because you can show exactly what the agent did and why.
