01
Readiness
Define what production requires.
Use reusable controls, evaluations, evidence requirements, and review requirements to determine whether the workflow is ready for approval.
Current product
Platform
Assurance infrastructure for AI workflows that keep changing.
Steerlane connects production readiness, an approved baseline, semantic change, assurance impact, and targeted revalidation in one control model.
Product principle
Approval should create reusable state — not a document that becomes obsolete the moment the workflow changes.
Control loop
Maintain continuity from readiness to re-approval.
The platform treats approval as a state that can be compared, reasoned about, preserved, and selectively reopened when the workflow evolves.
Steerlane control loop · production assurance lifecycle
Current product model
Steerlane maintains continuity between the workflow that was approved and the workflow that is changing, so assurance state does not need to restart from zero after every update.
Pre-approval
02
Approved baseline
Freeze the accepted assurance state.
Capture the approved workflow version together with the evidence and assurance state that justified the production decision.
03
Change intelligence
Compare the candidate against the baseline.
Detect semantic changes across prompts, models, tools, permissions, data sources, and configuration rather than relying on raw file diffs.
04
Assurance impact
Trace what the change can affect.
Follow changed workflow components into controls, evaluations, evidence, and unresolved dependency paths.
05
Revalidation
Reopen only what needs attention.
Preserve unaffected assurance state, rerun impacted evaluation paths, and escalate uncertain relationships for explicit review.
Current product surfaces
The controls behind the approval state.
Each surface contributes to the same goal: knowing what was approved, what changed, what remains valid, and what needs attention again.
01
Production readiness
Define the controls, evaluations, evidence, and human-review requirements that an AI workflow must satisfy before approval.
Reusable assurance definitions
Readiness requirements
Evaluation-backed evidence
Human review where required
02
Approved workflow baselines
Preserve the approved workflow baseline together with the assurance state that supported the decision.
Approved baseline version
Frozen workflow snapshot
Assurance snapshot
Approval and audit state
03
Semantic change intelligence
Compare a candidate workflow against the approved state at the component level instead of treating every configuration difference equally.
Prompt changes
Model changes
Tool and permission changes
Data-source and configuration changes
04
Assurance dependency mapping
Connect workflow components to the controls, evaluations, and evidence that depend on them.
Component-to-control relationships
Control-to-evaluation relationships
Evaluation-to-evidence relationships
Unmapped dependency visibility
05
Selective revalidation
Use the dependency graph to preserve unaffected assurance state and reopen only the paths affected by known or uncertain change.
Targeted evaluation scope
Preserved unaffected evidence
Explicit uncertainty handling
Focused reviewer attention
06
Human review and approval state
Keep human decisions explicit where automation alone should not determine production readiness or re-approval.
Reviewer decisions
Approval state
Escalated uncertainty
Controlled state transitions
07
Evidence and audit trail
Maintain the evidence and decision history needed to explain how the workflow reached its current approval state.
Evidence references
Evaluation results
Baseline history
Audit events
Concrete product behavior
Change becomes a scoped assurance response.
The platform does not stop at identifying that the workflow changed. It traces known dependencies and leaves unresolved relationships visible for review.
5
semantic changes
4
mapped
1
unresolved
This canonical Credit Review Assistant scenario shows the key behavior: mapped change follows known assurance paths, while an unmapped component remains explicit rather than being assumed safe.
Credit Review Assistant · approved v2 → candidate v3
Assurance impact
Candidate workflow compared with approved state
system_prompt
Change
Prompt modified
Assurance
Prompt policy
ResponseRevalidate
primary_model
Change
Model modified
Assurance
Model quality
ResponseRevalidate
credit_data_permission
Change
Permission modified
Assurance
Least privilege
ResponseRevalidate
credit_database
Change
Data source modified
Assurance
Approved source usage
ResponseRevalidate
document_lookup
Change
Tool added
Assurance
No approved mapping
ResponseReview
Decision logic
Preserve unaffected assurance state, revalidate mapped impacted paths, and route unresolved change into explicit review.
Evaluate the platform
Start with one workflow and one real change.
Use a representative production workflow to see how Steerlane establishes the baseline, traces assurance impact, and scopes the resulting review.