Connect a hundred market and internal data sources for millisecond trade risk, deep filing analysis and automated credit due diligence.
Look at the last 90 days of paid acquisition across North America and Europe. Find what is driving the drop in return on ad spend, and tell me what to do about it.
These are exchanges the team published, replayed here. Nothing on this page calls a language model, and nothing claims to.
A prompt library, a node-by-node board, a financial model you can argue with, and the API as it is actually documented.
Each agent below is configured for Financial technology and risk work, and carries its own measured throughput, accuracy and latency.
Connects to the warehouse, turns a question in plain language into SQL, runs the attribution, and returns a chart with the reasoning attached.
Answers in 52 languages across every channel you run, reads the actual returns policy rather than guessing at it, and hands over to a person the moment it should.
Scores transactions against the graph they sit in rather than in isolation, and writes the regulatory filing when it decides something is worth filing.
Reads a filing the way an analyst does — footnotes first — and tells you what changed against the last one and against the sector.
Samples transactions against the control they are meant to satisfy, and writes the working paper with the evidence attached.
Every template is a chain of nodes with a trigger at one end and something the business actually needed at the other.
Every transaction is scored inside the authorisation window against the counterparty graph, and anything that trips the threshold is held with a draft regulatory filing already written.
Scoring inside the authorisation window, filings drafted with their evidence, and an audit trail for every decision the system made.
Problem
The rules engine flags too much, so analysts triage noise instead of risk.
After
Graph context separates the ninth structured transfer from the one large ordinary payment.
Problem
A filing takes a day to assemble because the evidence is in six systems.
After
The draft arrives with the transactions, the timeline and the reasoning already attached.
Problem
The regulator asks why a decision was made and nobody can reconstruct it.
After
Every decision keeps its inputs, its model version and its score.
A hard latency budget the agent is held to, so risk can sit in the payment path rather than behind it.
The system prepares; a compliance officer reviews and signs. That boundary is not configurable.
Model version, feature values and score retained together, so a decision can be re-examined months later.
The alert volume dropped by two thirds and we caught more, not less. The analysts noticed within a fortnight.
A worked example, not a promise. Change the inputs on the full model and the arithmetic changes with them.
repetitive hours a year across 40 people at 8 hours each per week
hours automated at a 62% automation rate
labour value released a year, at $40 an hour fully loaded
Forty-six working weeks a year, before licence cost. Released hours are hours people spend on something else — whether that becomes cash depends on what you redeploy them to, and this figure does not assume you will.
One REST surface, documented request and response for each route, and a token you can revoke.
Routes
{
"data": [
{
"id": "agt_8fk2",
"name": "DataPulse",
"model": "nexus-dense-70b",
"status": "ready",
"quota": { "used": 4120311, "limit": 120000000 }
}
],
"has_more": false
}
Every tier states its own ceilings. Where a limit is not listed, there is not one.
For a team automating its first few processes.
Billed monthly, cancel at any time
For a department running automation as part of how it works.
Billed monthly, cancel at any time
For an organisation with regulators, auditors and a security review.
Billed monthly, cancel at any time
For deployments that cannot touch a public network at all.
Scoped to your deployment
For a team automating its first few processes.
20% below the monthly rate of $299
For a department running automation as part of how it works.
20% below the monthly rate of $1,290
For an organisation with regulators, auditors and a security review.
20% below the monthly rate of $4,900
For deployments that cannot touch a public network at all.
Scoped to your deployment
Two thirds fewer alerts and better detection. I did not believe that combination until the second quarter of data came in.
False positives down 62%
Verified customer, 9 months, self-hosted.