AI Automation
Month-end close automation for a multi-entity bookkeeping firm
Pave & Co. closed 40 entities with checklists in Notion. We automated evidence collection, reconciliations prompts, and a close cockpit so reviewers see blockers instead of hunting files.
The operational problem
Each entity had a slightly different close. Staff collected bank PDFs, asked clients for the same documents, and updated a checklist that nobody trusted.
Reviewers found missing accruals late. The firm could not take on more entities without another senior.
What was breaking down
- Document chases repeating every month
- Reconciliations parked in personal folders
- No live view of which entity is blocked
How Striders Tech approached it
We built a close model per entity: required evidence, owner, and due date. Automation requested documents, matched statements, and only asked humans to judge exceptions.
What we built
- Entity close templates with required evidence
- Client request portal instead of email archaeology
- Exception-only reconciliation review
- Partner dashboard of blocked vs ready entities
Results the team can measure
- 3 days off a typical 10-day close for standard entities
- One cockpit replaced scattered Notion checklists
- Capacity for additional entities without a new senior hire
Who this case study is for
Bookkeeping and CAS firms whose close is a scavenger hunt, not a controlled process.
Pave & Co. Accounting operates in accounting. The work is a custom system designed around their process, not a generic template with extra fields bolted on.
What changed after the system went live
off a typical 10-day close for standard entities
replaced scattered Notion checklists
for additional entities without a new senior hire