Ongoing
Ongoing Optimization
Month-to-month support after the first sprint proves useful.
After the first automation is live, we can stay involved to tune it, monitor quality, and build the next workflow. Keep going only when the results justify it.
Deliverables
What you get, on paper.
- Rolling automation pipeline with monthly prioritization
- Continuous optimization of live systems as models and prices change
- Governance and compliance reviews on a regular cadence
- Prompt, retrieval, and model tuning for cost and accuracy
- Monthly executive reporting with portfolio-level ROI
Process
How we run it.
- 1
Onboarding: access, baselines, and a rolling backlog
- 2
Monthly planning: prioritize two to four workstreams with your sponsor
- 3
Build and ship new automations; tune live ones
- 4
Monthly readout with outcomes, costs, and next-month plan
Outcomes you can measure
What you leave with.
A continuously expanding portfolio of working automations
Lower unit cost as models improve and we re-tune
Governance and compliance confidence with documented reviews
Clear leadership visibility into cumulative AI ROI
Next step
Start with one workflow.
Ship something useful.
Bring the repetitive process your team keeps doing manually. We will audit it, scope the sprint, and tell you whether it is worth automating before you spend more.
$10k flat sprint. One workflow. Senior engineer, hands-on.