AI Workflow Monitoring
acty.dev adds review, monitoring, and quality-check layers around AI-assisted workflows, delivered as a monitoring or checklist layer with review states, failure and edge-case notes, and operational handoff guidance.
We add review, monitoring, and quality-check layers around AI-assisted workflows, delivered as a monitoring or checklist layer with review states, failure and edge-case notes, and operational handoff guidance. Output stays under human review.
The problem we solve
AI-assisted output is often useful but not yet trusted: a workflow needs human review, repeatability, and visible failure handling before a team can rely on it in production rather than running it ad hoc.
How we work
- Task review.We review the AI-assisted workflow, where it can fail, and how output is used, then agree on a scoped monitoring and review layer before any build starts.
- Build with review.We add review states, quality checks, and failure handling against the agreed scope, with human review built into the workflow.
- Deploy or hand off.We deploy the monitoring layer or hand it off with environment notes and a repeatable way to apply the checks.
- Document and support.We hand over a monitoring checklist and edge-case notes, and offer ongoing support or a development retainer when further work is needed.
What you bring / what you get
Inputs
- The AI-assisted workflow to monitor
- Where it can fail and how output is used
- The review or quality bar the team needs
Outputs
- A monitoring or checklist layer with review states
- Failure and edge-case notes
- Operational handoff guidance
Definition of done.A monitoring or review layer around an AI-assisted workflow, delivered with review states, quality checks, failure and edge-case notes, and operational handoff guidance, so output stays under human review before wider use.
Fit and anti-fit
Good fit
- Teams with a useful AI workflow that still needs human review
- Buyers who need implementation and delivery, not just advice
Not a fit
- Teams wanting hands-off automation with no human review
- Micro-budgets with no defined scope
Questions
- What does AI workflow monitoring include?
- Adding review, monitoring, and quality-check layers around an AI-assisted workflow, delivered as a monitoring or checklist layer with review states, failure and edge-case notes, and operational handoff guidance.
- Why does AI output need monitoring?
- AI-assisted output needs human review, repeatability, and visible failure handling before production use, and a monitoring layer makes those checks consistent and reviewable.
- What is out of scope?
- We do not provide around-the-clock staffed coverage, hands-off remediation, or a large observability platform without proof. The layer keeps output under human review.
- What do you need from us to start?
- The AI-assisted workflow to monitor, where it can fail and how its output is used, and the review or quality bar your team needs. We agree the scope in a task review first.
- How is this priced?
- Small scoped tasks can start from a few hundred dollars. Larger implementation work and ongoing retainers are scoped after a task review.
- Can monitoring run on an ongoing basis?
- Yes. It can be delivered once as a monitoring or checklist layer, or run as recurring work. Ongoing retainers are scoped after a task review.
Pricing.Small scoped tasks can start from a few hundred dollars. Larger implementation work and ongoing retainers are scoped after a task review. (Scoped after a task review.)
