
Repair the data your revenue decisions run on
We rebuild source capture, routing, and reporting inside the stack you already own, then put agents on top to keep it clean. Most of it needs no new software.
300+
B2B brands served since 2021
50+
MCP tools wired into the stack
100+
Production workflows running
4.8★
Trustpilot rating
Trusted by 300+ B2B brands
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What an AI RevOps agent does inside your stack
Workflows
Automate the weekly repeat work
We take over the routing, follow-ups, and record hygiene your team runs by hand each week.
Tooling
Run a stack that fits
We select, implement, and connect the CRM and enrichment tools your motion needs, then keep them clean.
Attribution
Trace every dollar
We connect spend to closed won, including visits that blocked cookies and dropped tags would lose.


Why traffic ends up in the Direct bucket
Blocked cookies
Declined banners
Lost UTMs
Return visits
Manual hours
Another subscription

How we repair the
capture layer
Where the source
is normally lost
The repaired path, which
needs no new software
Ad click, Mon

Captured on arrival
Landing page

Cookie blocked
Second page

UTM dropped
Carried across pages and visits
Return, Wed

No referrer
Form submit

Written to a hidden field and mapped to a campaign
CRM record

A script that reads the source on arrival, hidden fields that record it at submission, and one workflow that maps raw tags to channel, platform, and campaign.
01
Capture
We read the source on arrival and carry it across every page, so it survives blocked cookies.

02
Store
We record the true source in hidden form fields at submission, so the last page visited cannot overwrite it.
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03
Translate
We map raw tags into clean values for channel, platform, and campaign in one workflow you can read.
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04
Route
We score and assign each lead against rules your sales team signed off on.
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05
Report
We connect spend to closed won so the pipeline number updates without anyone rebuilding a report.
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Put every revenue signal through one layer
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Why traffic ends up in the Direct bucket
Faster response
Scored inbound
Earlier warnings
Warm accounts
Less wasted spend
Current dashboards
Clean records
Captured calls
Promises tracked
Why our clients pick us over a
first RevOps hire
Capability
TripleDart
Bid tools and in-platform AI
Results from
accounts we run
What Our Clients are Saying
Where we usually start
Inbound
Leads reach the right owner

Attribution
Spend traces to revenue

Enrichment
Your list matches your ICP

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Frequently asked questions about AI Revops Agent
An AI RevOps agent monitors revenue systems continuously and acts on what it finds. It reads the CRM, the ad platforms, and product usage, then routes leads, cleans records, runs recurring workflows, and refreshes reporting.
No. Most of the value is operational: choosing and implementing the stack, automating weekly workflows, keeping records clean, and routing leads without a queue. Allara Global's 80% drop in duplicate records came from that side.
A CRM workflow fires on a trigger you predicted. An agent reasons across systems that store data in different shapes, so it can compare two weeks of ad data against deal stages and raise a change before anyone runs a report.
Four causes cover most of it: browsers blocking the tracking cookie, declined cookie banners, UTM tags dropping on the second page, and return visits arriving with no referrer.
Usually not. We have repaired this with no new software: a script that captures the source on arrival and carries it across pages, hidden form fields that record it at submission, and one workflow that cleans the values.
It shouldn't, and ours doesn't. Monitoring, scoring, alerting, and reporting run on their own. Anything that creates a record, changes a routing rule, or moves budget goes to a named human first.
HubSpot and Salesforce most often, including implementations and migrations. We are a HubSpot Platinum Partner and work with Clay, Factors, and Coupler. We recommend the stack that fits your motion and budget.
In your systems. The agent reads your stack through scoped, permissioned access and writes back to it. The language model is the reasoning engine only, so a better or cheaper model means swapping an API.
It sits underneath both. This layer is what lets our AI PPC agent bid toward qualified pipeline, and what lets our AI SEO agent show which content produced revenue.
GTM Engineering is sold as scoped sprints against a named bottleneck. On the first call we identify the bottleneck, agree the outcome, and price the sprint to it.





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