Every part of the Engine exposes a REST API, and most parts also expose an
MCP server and a skill. The intended operator is as likely to be
Claude, or an agent you wrote, as a person in a console. If that is you, start at
Getting started for AI agents.
What the Engine is made of
The Engine is one product with several parts. Read them as three layers plus the tooling that keeps agents accountable.Commerce state — objects and transitions, not just text
Systems of record — operate what you already have
StateSet is not another ERP. It sits above and across your systems of record and makes them safely operable by agents.Agent surfaces — resolve the interaction, execute the fix behind it
A support ticket is usually a symptom of an order, subscription or fulfillment problem. These are the parts that handle the interaction and close the operation behind it.Keeping agents accountable
StateSet Agents is the evaluation and training tooling: it grades an agent’s production conversations against a reward, curates the ones that worked, retrains, and evaluates the result on prompts the model never saw — with lineage from the deployed model back to the conversations that produced it. It is how you show that an agent got better, not just that it changed.How it is different
StateSet is not only an AI interaction layer or a workflow connector. It combines commerce semantics, deterministic execution, policies, integrations, auditability and outcome measurement.Commerce-native
The Engine understands commerce objects and state transitions, not just text and API calls:
orders, inventory, payments, returns, fulfillment, warehouse, finance.
Safe execution
Probabilistic reasoning bounded by deterministic validation, policies and approvals —
invariants, auth, audit logs, simulation, replay, idempotency, fail-closed writes.
Operational breadth
The whole commerce lifecycle — CX, orders, subscriptions, returns, fulfillment, inventory,
finance — instead of one interaction channel.
Interoperable
Works with the AI and protocol ecosystem you already use — MCP, embedded toolkits, multiple
agent frameworks — rather than requiring a proprietary front door.
Embedded and deployable
Execution can run close to your infrastructure and data: customer-controlled deployment
options, local and embedded runtimes.
Outcome accountable
Measured on the business work completed — successful autonomous commerce actions — not seats
or messages.
Who it is for
Where things stand today
Not every part is at the same stage, and each API tab says which is which.
Measured across production deployments: agents resolve 62% of contacts one-touch in the
measured cohort, with an AI-handled CSAT of 4.82, and a typical deployment takes two to
four weeks. Each figure is scoped to the deployment it was measured on — ask for the
methodology before quoting it.
Pricing
The Engine is priced on outcomes, not seats, tokens or capacity: you pay when work is completed — a return resolved, a cart recovered, a lead qualified. Every plan combines an optional monthly platform fee with a per-outcome price; higher tiers trade a larger fee for a lower rate.
An outcome is a verified, end-to-end resolution, billed per SKU — today a Triage Outcome
(human hand-off, 2.00), with further SKUs confirmed
per contract. Outcomes can be disputed within 14 days; anything at or above $100 requires human
approval before the Engine acts. Voice, Chat Widget, Email and Computer Use are activated as
modules with their own subscription. Details, entitlements and invoices are in
Billing; the comparison with helpdesk AI, iPaaS and building it yourself is
on Why StateSet.
Next steps
1
Create an account
stateset.com/sign-up — no card required.
2
Make a first call
The quickstart creates and launches a ResponseCX agent in five minutes.
3
Give your agent the Engine
Add the MCP servers or load a skill into your harness.
4
Talk to us
Book a demo or join the
Discord.