Nothing
Slips.
Sentinel deploys small, focused AI agents that watch your revenue operations around the clock — catching dirty data, stalled deals, and dropped handoffs before they cost you pipeline.
Revenue teams aren't short on tools. They're short on hours.
The average RevOps team juggles 12 to 18 platforms across the revenue stack — and reps and ops staff still spend up to 60% of their week on manual data entry, CRM cleanup, and reconciling reports that don't agree with each other. By the time a stalled deal, a bad handoff, or a duplicate record shows up in a quarterly review, the damage is already in your forecast.
Three tiers. Start narrow, prove it, expand.
One agent, one workflow, human-approved. Fast to deploy, easy to trust.
Multiple connected agents, some running autonomously where the stakes are low and the volume is high.
A full agent layer wired into your team's own definitions of revenue, running as embedded infrastructure.
Sentinel's first deployment ran on our own team's pipeline before we ever pitched a client. See what it caught, what it fixed, and what it gave back in hours.
You already know which workflow is costing you the most hours.
Let's put an agent on it — starting with a free diagnostic call, not a sales pitch.
AI That Watches Before It Acts
Most "autonomous RevOps AI" pitches ask you to trust a black box on day one. Sentinel doesn't. Every agent starts in copilot mode — it watches, flags, and recommends. A human approves. Only once an agent has proven itself on your data does it graduate to acting on its own, and only for the narrow, low-judgment work where that's actually safe (like routing a lead, not rewriting your forecast).
We spend the first week inside your CRM and revenue stack, not a slide deck. We identify where the hours are actually going — stale records, misrouted leads, silent handoff gaps — and pick the single workflow with the clearest, fastest payoff.
We build and launch one agent against that workflow, in copilot mode. It runs alongside your team, not instead of them, for the first 2–3 weeks.
We measure it — hours reclaimed, records cleaned, leads routed correctly — against a clear before/after baseline. No agent moves to autopilot, and no engagement expands, without a number behind it.
Once trust is established, we add the next agent, connect it to the first, and move the proven low-judgment work to autopilot. This is how Watch becomes Guard becomes Command.
What Sentinel Doesn't Do
We don't sell an "autonomous RevOps brain." Broad, unscoped agents are exactly what's driving the reported 40%+ of agentic AI projects that get scrapped within a year.
We don't touch production data without a human-approval step until an agent has earned autonomy on a narrow, well-defined task.
We don't rip out your CRM or force a platform migration. Sentinel works inside the stack you already have.
See the four steps run on a workflow of yours.
A 30-minute diagnostic call, not a sales pitch. We'll tell you which workflow is worth automating first.
One agent. One job.
One measurable outcome.
Every Sentinel agent is scoped to one workflow, one clear job, and one measurable outcome. No agent tries to do everything — that's the point.
Not sure which agent to start with?
That's the point of the diagnostic. We'll find the workflow with the clearest, fastest payoff — then scope one agent to it.
Priced for the outcome owned, not the hours worked.
Every engagement starts at Watch — no client skips the proof step.
1 agent, copilot mode, weekly review.
2–3 connected agents, selective autopilot.
Full agent layer, canonical metrics, embedded retainer.
Figures shown are starting points — final pricing is scoped per engagement.
For clients who want cost to track volume directly, we can offer a lower base retainer plus a small per-outcome fee (for example, per qualified lead routed or per record cleaned). Offered as an option, not the default.
Sentinel, Tested on Our Own Pipeline First
Before Sentinel took on a single outside client, we ran it on our own team's RevOps — because we weren't willing to sell something we hadn't proven on ourselves first.
Placeholder: specific workflow pain, hours lost per week.
Placeholder: which agent, copilot mode, time period.
Placeholder: which agent gets added next.
Want to see this run on your pipeline?
Book a diagnostic and we'll show you exactly what an agent would catch in week one.
Notes from the field
Notes from the field on running AI agents inside real RevOps stacks — what works, what breaks, and what we'd do differently.
We're writing as we ship. Want the first ones in your inbox? Mention it on your diagnostic call.
Why We Built Sentinel
RevOps teams don't need another dashboard, and they don't need an unsupervised AI making decisions in their CRM overnight. They need the boring, reliable version of AI — the kind that watches carefully, flags what matters, and only acts once it's earned the trust to.
Sentinel was built by a team that has already shipped production AI agents handling real, high-volume customer interactions — not demo-stage prototypes. We brought that same production discipline to revenue operations, starting by running Sentinel on our own pipeline first.
How We Work
One workflow at a time, never a black-box "transformation."
Every agent earns autonomy — it isn't granted by default.
Every engagement is measured against a clear before/after baseline.
Who We're For
US mid-size companies (roughly 50–500 employees) with a dedicated RevOps or Sales Ops function, running Salesforce or HubSpot, who are feeling the cost of tool sprawl and manual work — and want AI that proves itself before it's trusted with more.
Let's find your first workflow.
A free diagnostic call — no deck, no commitment.
Book a Diagnostic Call
No sales deck, no commitment. A 30-minute call where we look at your stack and tell you — honestly — which workflow is worth automating first, and whether Sentinel is a fit.
Send a few details and we'll come prepared.