Where we get involved
Operations Intelligence.
AI inside the systems that actually run the business.
Three threads of operations — vendor, growth, and marketing — with AI wired into the systems your team already runs. We diagnose where the leakage is biggest, ship the highest-leverage move first, and leave a copilot behind your team uses every week.
What it solves
The real problem, not the pitch.
Most SMBs and mid-market businesses have three operational backbones running their day-to-day: vendor and procurement, growth and revenue operations, and marketing operations. AI can move all three. The hard part isn't the model. It's the wiring into the tools your team actually opens — your CRM, your spend dashboard, your campaign tooling, your contract repository.
Done wrong, AI-for-ops becomes another tab nobody looks at. Done well, it sits inside Slack, your CRM, and your project tooling, surfacing the decisions that need attention this week — vendor renewals about to auto-trigger, leads stuck mid-funnel, campaigns under-performing, contracts non-compliant with the playbook.
That's where we get pulled in. We diagnose the highest-leverage move across vendor, growth, and marketing operations, ship it in production in weeks, and train the team that will run it after we leave.
Deliverables
What you actually get.
Every line here is something that runs in production by the time the engagement ends. Not a recommendation. Not a slide.
Vendor & contract intelligence
Every active contract parsed, scored, and indexed. Auto-renew traps, unfavorable indexing, and SLA gaps flagged. Renegotiation queue with prepared evidence.
Growth ops backbone
Lead scoring, routing, and pipeline hygiene wired into your CRM. Attribution that survives the multi-touch reality. Sales activity intelligence so you stop guessing.
Marketing ops backbone
Brief-to-asset pipelines, content QA, campaign orchestration across email, ads, and social, and narrative reports written in your voice — not just dashboards.
Procurement copilot
A chat interface your team uses on every new SOW or vendor proposal: 'Is this better or worse than our standard terms?' Answered in seconds, with citations.
Performance monitoring
Continuous tracking across vendors, campaigns, and pipeline. Alerts when SLAs slip, conversion drops, or spend drifts.
Senior-owned governance
Data classification, access controls, audit logging, and human-in-the-loop checkpoints — designed in, not bolted on.
Timeline
What the first six weeks look like.
Week 1
Diagnose
We audit vendor, growth, and marketing operations together. You get a ranked map of opportunities by leakage and effort, and we lock the first one with your executive sponsor.
Weeks 2 to 4
Build
First system shipped end-to-end against your real data — could be a vendor renegotiation queue, a lead-routing engine, or a campaign QA layer, depending on what won the diagnosis.
Weeks 5 to 6
Ship and train
Production rollout, copilot live, team trained, runbook documented. First monthly ROI report drafted before the engagement closes.
Questions
Before you even have to ask.
Is this one engagement or three?+
One engagement that covers vendor, growth, and marketing operations together — because in real businesses they're the same nervous system. We diagnose all three, ship the highest-leverage move first, and add the others on retainer as the wins compound. You're not buying three things stitched into one.
How is this different from a CRM consultant or a marketing ops agency?+
We don't sell tools and we're not on anyone's partner program. We build inside your existing stack — HubSpot, Salesforce, Marketo, ServiceTitan, NetSuite, whatever you have — and the AI layer is what makes the data finally usable. Most ops consultancies still run on spreadsheets. We don't.
What's the typical first move you ship?+
Depends on the diagnosis. For agencies and SMBs with heavy vendor books, it's usually the renegotiation queue (often $150K to $500K of recoverable leakage in two quarters). For growth-heavy teams, it's lead routing + attribution. For marketing-heavy teams, it's the brief-to-asset pipeline. We tell you which one before you sign.
How accurate is AI on this kind of work?+
On contract clause classification and risk flagging, current frontier models perform at experienced paralegal accuracy with citations. On pipeline scoring and attribution modeling, accuracy depends on data quality — which is why the diagnosis includes a data audit. Every output we ship has a human checkpoint at the conversion-critical step.
Where does the data and the AI live?+
Inside your cloud, under your access controls. No data leaves your environment. PII redaction, audit logging, and region-locked model routing are baked in.
Adjacent areas
What we typically pair this with.
AI Strategy & Adoption
A twelve-month roadmap your team owns.
Read more →AI Workflow Automation
The repetitive work, handled in the background.
Read more →Client Experience AI
Every client gets a senior-level experience, every day.
Read more →SEO, AEO & GEO
Get found on Google. Get cited by ChatGPT.
Read more →Get started
Put operations intelligence into your business.
A 30-minute call to scope this against your actual workflows. You'll leave with a rough plan and a rough number. No pressure either way.