Most companies are bolting AI onto broken processes. We engineer agentic systems directly into your RevOps architecture — so AI compounds your growth instead of adding complexity.
You bought Copilot, ChatGPT Enterprise, maybe a few automations. But none of it connects to your actual revenue workflows — it's a layer of tools sitting on top of the same chaos.
AI agents are only as good as the data they can access. If your CRM is dirty, your APIs aren't exposed, and your systems don't talk — no agent can help you.
Leadership won't greenlight AI that can read, write, and act on customer data without governance. You need controls, human-in-the-loop checkpoints, and audit trails.
Every engagement starts with assessment and ends with production-grade AI running inside your actual workflows.
Before we build anything, we audit your entire RevOps stack against five dimensions of AI readiness. The output isn't a PDF that collects dust — it's a machine-readable knowledge layer your team and AI agents can query from day one.
We don't just recommend AI — we build and deploy production-ready agents directly into your revenue workflows. MCP-native, connected to your real data, with the guardrails your leadership requires.
AI agents that read your CRM, enrich leads, and trigger actions autonomously
Your architecture exposed as a queryable context layer for any AI system
Event-driven workflows that replace manual process gaps
Human-in-the-loop controls, audit logs, and approval gates
AI systems aren't set-and-forget. We operate and optimize your agentic infrastructure on an ongoing basis — monitoring performance, tuning prompts, expanding capabilities, and ensuring everything stays aligned with your revenue goals.
Every deliverable we produce is structured to serve as machine-readable context — an MCP-ready RevOps knowledge base your team and AI agents can query, not a report that collects dust in Google Drive.
Architecture maps, findings reports, data flow docs — all produced in structured, parseable formats. Not flat PDFs.
Documentation becomes context that AI agents can read, reference, and reason over. Your RevOps architecture as a queryable system.
"Which automations touch Chargebee?" "What's the data flow for member enrollment?" — answers in seconds, not hours of digging.
We load all deliverables into NotebookLM so your team can conversationally query findings from day one. Plus the raw structured docs for any MCP-compatible agent or tool your team builds.
Agentic Readiness Assessment across all five dimensions. Map your systems, data, and process gaps.
Weeks 1–2Design your agentic infrastructure — which agents, which workflows, which data connections, which guardrails.
Weeks 3–4Engineer and deploy production agents directly into your revenue workflows with full governance in place.
Weeks 5–10Monitor, tune, and expand. New agents, better prompts, deeper integrations. The system compounds.
OngoingThese are the workflows where AI agents deliver compounding ROI — not science experiments, but production systems that directly impact revenue.
AI agents that score inbound leads against ICP criteria, enrich with firmographic data, and route to the right rep — in real time, not batch overnight.
Agents that monitor product usage, support tickets, and engagement signals to flag at-risk accounts 30–60 days before renewal — not the week of.
Unified health scoring that pulls from CRM, product analytics, support, and billing — then triggers automated playbooks for CSMs based on real-time signals.
An MCP-powered agent that knows your entire RevOps architecture — ask it "What's our attribution model for paid social?" and get an answer in seconds, not a Slack scavenger hunt.
JayOh has been engineering growth systems since 2016. AI consulting is a natural extension of our RevOps DNA — we already know your stack, your data, and your workflows. We're not learning on your dime.
Most AI consultants deliver a strategy deck and leave. We deliver production-grade agents running inside your actual workflows. We're operators, not advisors — we own the outcome from assessment through deployment and ongoing optimization.
No. The Agentic Readiness Assessment identifies exactly where your data gaps are. We then prioritize — some agents can run on imperfect data while we clean the foundation in parallel. We meet you where you are, not where a textbook says you should be.
Model Context Protocol (MCP) is the standard for giving AI agents structured access to your business systems. We build MCP servers that expose your CRM, billing, support, and analytics tools as queryable context — meaning any AI agent (Claude, GPT, custom) can read your architecture and act on it with proper governance.
Most clients see measurable impact within 60–90 days. The assessment itself often surfaces quick wins — data hygiene fixes, automation gaps, broken handoffs — that deliver value before we even deploy agents. The compounding effect hits around month 3–6 as agents learn and workflows mature.
No. We work across the major CRM and RevOps stacks — HubSpot, Salesforce, Chargebee, Stripe, Intercom, Gainsight, and dozens of others. If your system has an API, we can connect an agent to it. The assessment evaluates your specific stack regardless of which tools you're running.
30-minute strategy call. No pitch deck. We'll map your stack, identify the highest-leverage automation candidates, and tell you exactly what's possible.
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