Build an AI workforce your team can actually use.
Village Consulting designs and deploys AI agents, automations, and revenue operations systems that handle the busywork, surface the signal, and help your team move faster without losing control.
Your next hires might be workflows.
Most teams do not need a pile of disconnected AI tools. They need a practical operating layer: agents that watch the right systems, do the repetitive work, prepare decisions, and hand off cleanly to humans.
Agent strategy
We identify the highest-leverage workflows where AI can reduce drag, improve speed, or unlock revenue.
Agent buildout
We build agents that connect to your stack, respect approval gates, and produce useful work instead of demos.
Operational adoption
We document, train, measure, and refine so the system becomes part of how the team actually operates.
AI systems for the work that creates, converts, and retains revenue.
Revenue AI Agents
Agents that support the daily motions of sales, marketing, success, and operations.
- Lead enrichment, qualification, routing, and alerting
- Follow-up drafts, call summaries, account research, and next steps
- Renewal risk, expansion signals, and customer handoff workflows
AI Revenue Operations
RevOps foundations that make AI useful because the data, process, and ownership are clean.
- HubSpot, Salesforce, Marketo, and lifecycle architecture
- CRM hygiene, workflow governance, attribution, and reporting loops
- Dashboards that show what changed, what matters, and who owns it
Internal AI Workflows
Reusable AI processes for teams drowning in repetitive analysis, documentation, and coordination.
- Inbox, meeting, document, research, and reporting assistants
- Human approval queues for outbound, data changes, and sensitive actions
- Knowledge bases, SOPs, and agent playbooks your team can maintain
StackAudit Diagnostic
A fast way to find the broken data and workflows that usually become the first AI wins.
- Duplicate contacts, missing owners, lifecycle gaps, and bad fields
- UTM and attribution issues before they corrupt reporting
- Plain-English checklist for what to fix, automate, or agent-enable first
Not a chatbot. A coordinated operating layer.
A practical path from AI idea to deployed workforce.
Diagnose
Map current workflows, systems, data quality, bottlenecks, and high-value repetitive work.
Design
Choose the first agents, define permissions, approval gates, inputs, outputs, and success metrics.
Deploy
Build the automations and AI workflows inside the tools your team already uses.
Operate
Measure, improve, document, and expand the workforce as the team learns what works.
Yes, there is a real operator behind the email.
Village Consulting is led by Kyle Garrett, a Revenue Operations operator with 10+ years building the systems behind SaaS growth: CRM architecture, marketing automation, sales process, reporting, and now practical AI agents.
- Operator-led, not agency fluff
- Hands-on systems architecture and implementation
- AI strategy tied to revenue workflows, not novelty
- Human-in-the-loop design for approvals and safety
- Built around your existing stack before adding new tools
Start with StackAudit.
Before building AI into a messy system, find the CRM and RevOps issues that will limit it. StackAudit is the free diagnostic from Village Consulting for CRM hygiene, workflow gaps, attribution issues, and AI-readiness.
AI implementation with RevOps instincts.
Village Consulting sits at the intersection of AI systems and revenue operations. The work is part strategy, part architecture, part build partner: find the workflows worth automating, connect them to your stack, and make sure humans stay in control of the moments that matter.
years in SaaS revenue operations and GTM systems.
agent design, CRM architecture, workflow automation, reporting, and adoption.
Want to see where an AI workforce fits?
Send the rough version. The messy workflow, the stuck process, the team doing too much manual work, the CRM that nobody trusts — that is usually where the opportunity starts.
kyle@village-consulting.com