Agentchapel
A multi-client marketing operations workspace that packages specialized AI workflows, client-scoped memory, approvals, cost routing, evidence logs, and billable outcome reporting for small agencies.
A 1-15 person agency can assemble separate automations for inbox triage, content, SEO, ads, analytics, copy, research, and compliance review, but the difficult work begins after the demos: keep each client's data isolated, route tasks to appropriate models, require approval before external action, attribute cost, and show what was actually delivered. Research confirmed two functioning open-source agent stacks, yet found no managed, white-label, per-client-billable product at this layer.
The owner or operations lead at a 1-15 person marketing agency, or an AI-curious in-house team. The input identifies the segment but does not establish budget, current spend, or an exact purchasing role.
A verified low-cost agency stack and active projects create a current commercialization window.
Reusable workflows, model routing, tenant controls, and reporting scale predominantly through software.
One cross-reference and one inbound connection support the direction without broad independent convergence.
Two live open-source stacks validate the workflow, current low daily inference costs improve viability, and multi-client governance plus billing is a clear missing managed layer.
The buyer and budget are incomplete, only one related API was verified, the claimed compliance posture requires independent evidence, and no structural incumbent copying barrier is established.
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