Workflow DSL
Declare agents, guards, handoffs, and retries the way you declare Terraform. Human-readable, version-controllable, diffable.
Platform · Automation
Ship agent workflows
the way engineers ship code.
Declare, version, diff, merge, preview, promote, and roll back, the same discipline your product team uses for software, applied to every agent workflow you run.
The primitives
What's inside automation.
Six building blocks that turn agent workflows from prompt experiments into production assets with CI-style discipline.
Version control
Git-style semantics for every workflow, branch, diff, merge, revert. Every change attributable, every rollout reversible.
Environment parity
Dev, staging, and production with identical tooling, identical policy, and CI-style promotion gates between them.
Instant rollback
Pin any historical version as the live build in under a second. No cold-start, no redeploy, no "please stand by".
Per-unit forks
Fork a workflow per business unit, per region, or per customer tier. Central governance; local tuning where it matters.
Automated policy checks
CI gates for policy, cost, and dependency risk. Changes that would breach policy cannot merge, not "should not", cannot.
Automation in numbers
What automation delivers.
0x
Faster time-to-ship
0+
Workflows in production
0s
Rollback time
0%
Change-audit coverage
Capabilities
What you can do with automation.
Six capabilities that turn agent workflows into production-grade software you can operate confidently.
Declarative authoring
Describe the workflow, not the orchestration. The platform handles sequencing, retries, idempotency, and policy, you focus on the outcome.
Code-review discipline
Pull requests for workflow changes. Reviews, approvals, and required checks, the same workflow your engineers already run.
Promotion gates
Policy, cost, and compatibility checks must pass before a workflow promotes. Gates are defined in code and evaluated automatically.
Live traffic management
Canary a new workflow version against live traffic; route by cohort; promote on evidence, not intuition.
Per-unit customisation
Fork a workflow per business unit, region, or customer tier without copy-paste. Central improvements propagate; local overrides survive upgrades.
Change analytics
Every change, every author, every outcome measured. Before/after comparisons are available as a platform primitive, not a reporting project.
How it works
From edit to production, safely.
Three stages between an engineer's change and a live workflow. Every stage gated, every stage evidenced.
- 01
Author
Declare the workflow in the DSL. Use the SDK where it fits, the DSL where it doesn't. Diff against production, simulate against recent traffic, and open a pull request.
- 02
Review & gate
Policy, cost, and compatibility checks run automatically. Human reviewers see the diff, the simulation, and the gate results. Nothing merges until gates pass and reviewers approve.
- 03
Promote & watch
Promote through staging to production with CI-style gates. Canary against live traffic, measure outcomes, roll back in under a second if signals drift.
In production
How teams use automation.
Six patterns our customers run today, all composable on one platform.
Weekly release trains
Enterprise teams releasing workflow changes on a weekly cadence, not a quarterly roadmap. Governance evidence generated as a by-product of the release itself.
Impact Weeks-to-ship, not quarters
Per-unit workflow forks
Separate tuning for retail vs. commercial lines on the same platform. Central teams propagate improvements; local teams keep what makes them different.
Impact One platform, many operating models
Live A/B experiments
Route traffic across workflow versions, measure real lift, and promote based on evidence. Experiment framework built into the runtime, not tacked on.
Impact Promotion decisions on data, not gut
Emergency rollback
Pin a historical version as the live build in under a second during an incident. No redeploy, no cold-start. Post-incident reviews work from the same audit trail.
Impact Mean time to mitigation measured in seconds
Policy-gated promotion
Changes that would breach policy cannot merge. Gates encode the rules your second line already writes down, now enforced in code, not in review meetings.
Impact Control reviews from weeks to hours
Workflow marketplace
Reusable workflow templates published across the organisation. Central teams maintain the core; downstream teams consume upgrades automatically.
Impact Playbook reuse across business units
Why automation matters
Why prompt engineering is not a shipping strategy.
Change is unavoidable
Models change, prompts drift, policies tighten. Without version control, promotion gates, and rollback, every change is a risk event rather than a planned release.
Governance scales or it breaks
Review meetings do not scale. CI-style gates encode your second-line controls as code so changes land faster, with more audit, not less.
Incidents need rollback, not forensics
When a workflow misbehaves, the first move must be to restore known-good. One-second rollback beats a war room investigating state mutations.
Experimentation is a primitive
You cannot improve what you cannot measure. A/B and canary routing built into the platform makes every change legible and every improvement attributable.
Let's talk
See automation
See automation
on your workflows.
30-minute technical walkthrough. Your architects, our platform engineers.