Keep your workflows where they are. Threadify follows work across your services and AI agents, checks your rules, and helps you decide what happens next.
One request. Several systems. A shared record of what happened.
A customer asks for a refund. An agent picks it up, your backend checks the order, and a payment service handles the money.
Threadify brings the steps you record into one shared timeline, called a thread. See who did what, what happened next, and where work is waiting.
Your services and agents keep doing the work. Threadify follows it across them.
// Follow a refund across services
const thread = await connection.thread("Refund-4821", { label: "Refund-4821" });
await thread.step("refund_requested")
.addContext(data).success();Already using OpenTelemetry? Send your traces to Threadify to bring the recorded steps of your workflows together.
Put the important rules in a contract: a refund needs approval, an amount must be positive, or a payment reference must match the original order.
Threadify checks the recorded steps and their details against those rules. See what passed, what failed, and the evidence behind each result.
The same rules follow the work across services, partners, and AI agents.
Start with one important rule. Use readable contracts to describe approvals, valid details, and the order of steps. Add more checks as you learn.
Start by watching for rule violations and notifying your team. For sensitive actions, have your application ask Threadify whether the next step is allowed before it proceeds.
You choose the response. Your application carries it out.
// Your application waits for permission.
await thread.waitFor("refund_issued");
// It then performs the action.
await issueRefund();
// Record the outcome and await validation.
await thread.step("refund_issued")
.success("Refund issued", { waitFor: true });Has this agent missed an approval before? Where does this partner’s work keep getting stuck? An Entity Profile connects their past runs so your team can see which rules held, which failed, and what needs attention.
Use that history to review mistakes and improve the next run.
Entity Profile · Support agent
Completion isn’t the whole story. Every run eventually completed, but 256 had already reported a refund without approval. The history keeps those mistakes visible, even after recovery.
View the test evidenceFollow a request across services and partners. See where it stopped, which rule failed, and what happened before it.
Explain an outcome without piecing together separate logs.
Understand where workflows break down, which rules fail repeatedly, and how outcomes change over time.
Find recurring problems across customers, services, and partners.
Give services and agents the recorded history behind a decision. Have them check whether the next step is allowed before continuing.
Apply consistent checks across the systems doing the work.
A reviewer records an approval. A service carries out the next step. Invite participants into the same thread so their actions and rule checks remain part of one record.
// Invite a reviewer to the thread
const invitation = await thread
.inviteParty({
role: "reviewer",
expiresIn: "48h"
});
// Share the invitation with the reviewer
console.log(invitation.token);// Join thread with token
const thread = await connection
.join(invitationToken);
// Record the approval
await thread.step('approval')
.addContext({ payment_reference: 'PAY-12345678' })
.success();Keep the handoff, the decision, and the outcome connected.
Their steps and yours. One shared thread.
Follow what happens. Check the rules. Decide when work can continue. No credit card required.