For revenue leaders
Your AI sales tools produce junk
You bought the tools, the demos were good, and the output still reads like it was written for someone else's company.
What is usually wrong underneath
The tools are rarely the problem. An AI sales tool writes from the data it can reach. If that is a shared contact database and a thin CRM record, every one of its customers gets the same output you do.
What makes output specific is proprietary context: which deals you won and why, what you charged, who bought, and what they said. In most mid-market companies that context is spread across the CRM, spreadsheets, call notes, and people's heads. No tool can read it.
There is also an ownership gap. Sales tools come from the revenue budget and infrastructure comes from IT. Making the tools you already bought work sits between the two, so nobody owns it. The renewal arrives before anyone has fixed the foundation.
What we do about it
This door opens into foundation and governance, pipeline creation, forecast, capacity and board.
- Proprietary context layer. Win history, pricing, and customer records modeled so your tools can read them.
- Data quality enforcement. Duplicates, missing fields, and routing failures caught by rules that fire, not by reminders.
- Signal detection. Account triggers built from your own data sources, not a list your competitors also buy.
- Dormant lead revival. Untouched leads scored and returned to sellers with a reason to call.
- Tool ROI measurement. Tool spend tied to pipeline that is measured in your own CRM.
The Pipeline Diagnostic
Every engagement starts with a fixed-price diagnostic. You keep the findings whether or not you continue.
Price and duration are not published yet
The diagnostic is fixed price and fixed length. Both numbers appear here once the pricing record is approved. We will not show a number we have not committed to.
What you walk away with
- A map of your revenue data and the points where it breaks
- A ranked list of fixes, each with the evidence behind it
- A review of what your current AI sales tools can and cannot see
- A scoped build plan you can run with us or without us
How it works
We read your CRM, enrichment, and sequencing data through scoped, read-only access, interview the people who run the tools, and trace where pipeline is lost between systems.
Data access
Read-only service accounts on credentials you own. Access is time-boxed, logged, and revoked when the diagnostic ends.
Who it is for
- Revenue leaders with a CRM and at least one AI sales tool in production
- Teams with an outbound motion and a named owner for revenue operations
Who it is not for
- Companies looking for an outsourced SDR team
- Teams without a CRM in production
- Anyone who wants a tool recommendation without touching their data
What happens after the diagnostic
Build. A small pod builds the ranked fixes inside your systems, on credentials you own.
Managed operations. If you want us to run the layer with your team, we do, under the same documentation you hold.
Migration. When a platform change is forced on you, we carry the rules that matter across and drop the ones that do not.
Ownership. You keep what we build: the data models, the workflows, and the documentation. Nothing depends on us staying.
Objections, answered
Should we replace the tools instead?
Usually not. A new tool reads the same data the old one did. We start by finding out what your current tools can and cannot see. Sometimes the answer is to cancel one. More often it is to give them better data.
Will my CRM's built-in AI do this soon?
Partly, yes. Native CRM agents already handle summaries, basic scoring, and standard routing well, and they will absorb more. They work on the data inside the CRM. They do not model your win history, your pricing, or the sources that live outside it. That proprietary part is the layer we build.
Why not hire a GTM engineer?
If you can find and keep one, do. A strong GTM engineer is the right long-term answer for many teams. The work stalls when the role takes months to fill, or when one person becomes the only one who understands the system. We build the layer, document it, and hand it to whoever you hire.
Why not a retainer agency?
A retainer agency is a good fit when you need workflows run for you each month. It is a poor fit when the problem sits in your data model, because a retainer has no reason to fix the foundation and leave. We price the build as a project, and you keep what we build.
What access do you need?
For a diagnostic, read-only service accounts on credentials you own. Access is time-boxed and logged, and you can revoke it at any moment. Write access is scoped per module during a build and only with your approval.
Related research
No research published for this situation yet
Limerine Research items tagged to this situation appear here when they are published.
Start with a fixed-price diagnostic
Five questions, then a booking. You leave the diagnostic with a ranked plan you can run with us or without us.