We publish the receipts
We have not published a story for this service yet. The ones we have published carry the real numbers, named clients, and quotes from the people who lived it.
Browse customer storiesAI that does work, not demos.
We build AI agents inside your revenue engine, researching accounts, routing leads, drafting follow-ups, keeping the CRM clean, wired into HubSpot and supervised like employees, because that's what they are now.
the situation
Your board wants an "AI strategy." Your team has 14 ChatGPT tabs and a prompt doc nobody updates. Somewhere between those two is the actual opportunity, and it's not a chatbot on your pricing page.
Here's the unglamorous truth: AI in a revenue org is only as good as the system it works in. An agent connected to a messy CRM just automates the mess, faster, confidently, and at scale. That's why an AI project from us starts with RevOps discipline, not a model demo.
what you get
What we build
Research & enrichment agents, every inbound lead arrives pre-researched: company, tech stack, buying signals, suggested talking points. Your reps open the record and it's already done.
Routing & triage agents, leads, tickets, and handoffs decided by judgment, not just round-robin. The agent reads context; the rules engine never could.
Follow-up & pipeline hygiene agents, drafts the check-in, flags the stalling deal, chases the missing next step. The nagging your pipeline needs, without a human doing the nagging.
Reporting & insight agents, "why did conversion dip in March?" answered in plain English, from your actual data, before the Monday meeting.
HubSpot Breeze, done right, we configure what you're already paying for before selling you anything new. Radical, we know.
Every agent ships with guardrails: human approval where it matters, logs for everything, and a kill switch. Autonomy is earned, not assumed.
how it works
How it works
1
AI Readiness Assessment
Where agents will pay off first in your process, and what data needs fixing before any of it works. (This is the free score, deepened.)
2
Pilot · weeks 1–4
One agent, one workflow, measured against a baseline. Small, visible, undeniable.
3
Prove & expand
Pilot metrics reviewed. Works → next agent. Doesn't → we say so and adjust. No AI theater.
4
Run
Agents monitored, tuned, and improved as part of a retainer, models change monthly; your agents should too.
investmentSee full pricing
Pilots from $7,000 (typical range $7,000–$13,500); ongoing agent ops folded into RevOps as a Service or scoped standalone. Ranges on the pricing page.
The AI stack we work with
questions we actually get
Questions, answered.
Is our data ready for this?
Statistically: no, not yet. That's normal and fixable, it's usually a 2–4 week cleanup, and it improves everything else too. The assessment tells you exactly.
Will agents email our customers unsupervised?
Only when you decide they've earned it. Everything starts in draft-for-approval mode. Most clients loosen the leash gradually; some never do. Both are correct.
Which model do you use?
The right one per job, swappable as the market moves. You're buying outcomes, not a model subscription.
Is this going to replace my team?
It replaces the part of their job they complain about at dinner. The research, the data entry, the chasing. What's left is the part you actually hired them for.
Every month, this gets easier for your competitors too.
Take the AI readiness score, or book a call and bring your most repetitive workflow. We'll tell you if an agent can eat it.