Relay lets your team change a running agent workflow in real time — preserving completed work, avoiding recomputation, and keeping a full audit trail. Think Temporal for agentic systems, with the live observability of Datadog.
Self-host in under 10 minutes. Your data and models stay in your environment.
Drop-in control plane · works alongside LangGraph & CrewAI · no workflow rewrite
A long-running agent workflow can take minutes or hours — approvals, tool calls, data jobs. Halfway through, a policy changes, a human steps in, or priorities shift. Today, that means one thing: cancel and start over.
Restart-based systems re-run every completed step on each change — paying again for the same compute, tokens and tool calls, and waiting all over again.
Intermediate results, partial progress and context are discarded on cancel. There's no clean way to resume from where the work actually was.
When a run is killed and restarted, the record of what changed and why is fragmented — a problem for regulated and high-stakes operations.
LangGraph, CrewAI and custom loops are great at defining and running a workflow. But they treat human input as something that happens before or after a run — not during it. There's no production-grade layer to safely change a workflow while it's executing, and prove what you changed.
Relay models your workflow as a live, mutation-aware graph. When a change arrives, it applies only to the affected steps — everything already completed stays done. The simple version: your workflow can change its mind without losing its memory.
| When something changes mid-run | Restart-based systems | Relay |
|---|---|---|
| Completed steps | re-run from scratch | preserved |
| Recomputation | all steps | only affected steps |
| Execution state | discarded | checkpointed & resumable |
| Mid-run intervention | not possible | first-class & live |
| Record of the change | fragmented | full before/after/delta |
| Unsafe changes | no guard | approval-gated, fail-safe |
Conceptually simple — built for CTOs, product leaders and ops owners, not just engineers.
You run your workflow through Relay — directly, or wrapped around an existing agent loop.
As each step completes, its state is durably checkpointed so progress is never at risk.
A human, a policy, or an upstream signal asks for a change while the workflow is still executing.
Relay applies the change to just the impacted part of the workflow — not the whole thing.
Everything already finished stays finished. No re-running steps that didn't change.
The change is recorded with its before, after and exact delta — exportable as one record.
Relay ships with a live control-plane dashboard. Every figure below is computed from your own workflow runs. We deliberately show definitions here — your real numbers appear in your pilot.
Works as a drop-in control plane layer — no need to rebuild your workflows.
Relay converts system behavior into business outcomes: lower compute spend, faster recovery, reduced operational risk, and clean compliance records. Here's how the math works on a single workflow line.
Assumptions you can replace with your own: a 20-step workflow; ~12 completed steps re-run per interrupt under a restart model; ~$0.40 compute/API per step; ~6s per step; 3 course-corrections per day; 250 working days.
This is an illustrative model using placeholder rates to show how savings scale — not a benchmark and not a measured result. Plug in your real step counts and rates. In your pilot, the dashboard reports the actual measured recomputation avoided and recovery time from your own runs — never simulated. Savings scale with the number of concurrent workflow lines.
Every step's state is written to durable storage with atomic writes, so progress is captured continuously and can't be half-saved.
An interrupted or crashed run reloads its last checkpoint and continues from exactly where it stopped — no lost progress, no manual replay.
Each mutation is appended to the trail with its before-state, after-state and exact delta — a complete, exportable record of what changed and when.
High-risk changes are gated behind approval. If the decision engine can't safely decide, it changes nothing rather than guessing — no unsafe mutation is ever applied.
No. Relay is a control plane that sits alongside your existing framework or agent loop. You keep your workflow logic; Relay adds live steering, checkpointing and an audit trail on top.
Yes. Not by replacing those tools inside the editor, but by wrapping the larger workflow around them: code generation, testing, review, approvals, deploy checks and handoffs. If that workflow changes halfway through, Relay helps you update it without restarting the entire process.
Relay is self-hosted in your environment. Your data and the model you use for decisions stay with you — nothing is sent to a third party by default.
Self-host in under 10 minutes, then wrap an existing workflow with a few lines of the SDK. No rebuild of your logic is required.
Yes. Every KPI is computed from your actual workflow runs. When something hasn't been measured, Relay reports it as unknown instead of inventing a number.
The pilot includes the live runtime, durable checkpoint/resume, real-time steering, approval controls, measured KPIs and the full audit trail. Enterprise add-ons such as SSO/RBAC and alerting integrations are on the roadmap — we're candid about this during your evaluation.
Tell us a little about your workflow. Every submission emails our founding team directly, and we follow up to schedule a hands-on walkthrough.
One form, two intents: demo request tries founder outreach immediately, waitlist stores interest for rollout updates.