AGYNTX connects store systems, finance systems, and customer signals into one governed machine. Agents prepare the work. Operators sign the gate. The ledger proves the outcome.
Every figure below is the shipping spec, not the roadmap. If it is on this sheet, it is in the machine.
| Agent Roster | 9 agents across three squads: Growth, Operations, and Finance. Each agent owns one job and writes every action to the shared ledger. |
|---|---|
| Operating Modes | Operator mode prepares recommendations only; a human executes. Automation mode executes within rules you set, with a rollback window on every published change. |
| Confidence Labels | Every number carries one of three labels: VERIFIED · MODELED · INFERRED. No unlabeled figures anywhere in the system. |
| Approval Gate | All customer-facing actions pass the gate. An operator signature is required before anything a customer can see leaves the machine. |
| Rollback | Published price changes reverse with one action for up to 7 days. The ledger records who rolled back what, and why. |
| Learning Loop | Every approval, edit, and rejection is recorded to the ledger and tunes the next run. The system is sharper tomorrow because an operator used it today. |
| Integrations | SHOPIFY · KLAVIYO · META · GOOGLE · STRIPE · TIKTOK · AMAZON |
A number you cannot trace is a liability wearing a suit. AGYNTX labels every figure by how it knows what it knows, and slows itself down as certainty drops.
Observed facts tied to source rows. An order in Shopify, a charge in Stripe, a send in Klaviyo. You can click through to the row that proves it.
Calculated relationships: attribution, projections, cohort math. Always labeled, always kept separate from observed fact, never mixed into a verified total.
Lower confidence reads. When the machine is guessing, it says so, slows down, and routes the action through the gate before anything moves.
The diamond from drawing 001, drawn at four times scale. This is the only path a customer-facing action can take out of the machine.
Recorded decisions are not just an audit trail. They are training data. Every approval, edit, and rejection an operator makes is written to the same ledger the agents read, and the next run is tuned by it.
Approved and rejected drafts, with the operator's written feedback, feed the next generation run. Output sharpens against your standards, not generic taste.
Weekly recommendations are scored by what actually got approved before. Each plan is built from every prior plan's decisions.
The recommendation layer is tuned by operator choices, not a static template. What the team edits, it learns.
Past copy corrections become standing rules. Drafts come back on brand by default, because yesterday's red ink is today's spec.
Nameplates from machines already running. Each installation stamped, serialed, and reporting to its own ledger.
“AGYNTX caught a pricing anomaly on a Friday night that would have cost us six figures by Monday. No one was watching. It was.”
Head of Ecommerce, Zulily · Design Partner
Early access runs installation by installation. Sign below and an operator seat is held under your name.