AI Workflow Sprint
One high-value workflow — designed, built, tested, and deployed end to end, with approvals, exception handling, and staff training included.
Who it's for: businesses ready to automate a specific process: lead intake to scheduling, discovery call to proposal, document intake to structured data, or similar.
What a sprint installs.
A discovery-call-to-proposal workflow, as one example:
Call recorded and summarized
The meeting is transcribed and a structured summary is generated.
Proposal drafted automatically
Scope, pricing options, and terms assembled from the summary and your templates.
You review before it sends
The draft waits for a person. Nothing goes to a client unreviewed.
E-signature and follow-up
Approved proposal goes out for signature; polite follow-up runs on schedule.
Unusual cases route to staff
Odd pricing, missing details, or unclear scope go to a person instead of guessing.
Everything needed to run it without us.
- The deployed workflow, connected to your existing systems
- Approval points and exception queues configured with your team
- Testing across standard cases, edge cases, and failure paths
- Staff training and plain-English documentation
- Audit logging of what ran, when, and why
- 30 days of post-launch stabilization support
Asked often.
How do you choose which workflow?
If you already know, we scope it directly. If not, the AI Opportunity Audit identifies the highest-value candidate first.
Will this replace our staff?
It removes structured administrative work — data entry, drafting, scheduling, chasing. Judgment calls stay with people, by design.
What happens after the 30 days?
The system is documented and yours. Many clients move to Managed AI Operations for ongoing monitoring and improvement; it's optional.
Start with the audit.
Every engagement begins by understanding your workflows. The audit gives both of us the map.
Book an AI Opportunity Audit