Your CRM isn’t in the index.
By default your deals, accounts, and notes aren’t in the tool’s reach — so it answers from the public internet instead.
BUILD 03 · AI YOUR TEAM USES
The AI you’re paying for should know your business, as much as it knows about the world.
Your team bought the AI licences for the right reasons — the promise was real, and the tools are genuinely good. But out of the box they know everything about the world and nothing about your deals, so reps asked twice, got generic answers, and quietly went back to work. The licence didn’t let you down as much as it was never introduced to your data.
AI Grounding connects the AI tools you already license to your actual sales data, from $7,999: the five grounding gaps — retrieval scope, export structure, vocabulary, freshness, and access hygiene — closed in order, so Gemini, Claude for Teams, or ChatGPT Enterprise answers about your deals, accounts, and pipeline. Scoped at a two-day diagnostic, delivered in two to three weeks.
THE REFRAME · WHY IT FEELS GENERIC
The tool isn’t broken. It’s ungrounded.
You can’t prompt your way to answers the tool can’t see, and switching vendors just swaps one ungrounded model for another — every AI answers from the data it can reach, and none can reach yours until someone connects it. The difference between a guess and a forecast is the data underneath, and right now your AI is guessing.
The line worth repeating internally: the AI isn’t broken, and buying it wasn’t a mistake — it just hasn’t met your data yet.
THE FIVE GROUNDING GAPS
Five gaps stand between your licence and your pipeline.
Every ungrounded AI deployment fails through some mix of the same five gaps. Each one below stands on its own — and each has a check you can run against your own tool today.
Relationships flattened into CSV soup.
Contact → account → deal is a web of relationships. A flat export destroys it, and the AI can’t reason across objects.
The AI doesn’t speak your pipeline’s language.
Your stages and shorthand mean nothing to a model that’s never been told them — so your questions miss your own data.
Answering from last quarter.
Stale grounding is wrong with confidence — the answer reads right and describes a pipeline that no longer exists.
The AI sees what reps shouldn’t leak.
Grounded carelessly, it can surface compensation or unreleased pricing to anyone who asks — so this gap closes first, behind a field-level allowlist.
The order matters: gap five closes before anything ships, then one through four. And what this page can’t tell you is which gap is costing you the most — that takes a look at your actual stack and field-level data quality, which is exactly what days one and two of the build measure and score.
WHAT YOU GET
What lands in your hands after two to three weeks.
The grounding architecture
The AI you already license answers about your deals, your accounts, your pipeline — not the world in general.
- A field-level allowlist, reviewed with you before anything connects — access hygiene closes first, not as an afterthought
- Structured, relationship-preserving exports of your sales data — not a flattened CSV the model can’t reason over
- A refresh pipeline, so answers come from this quarter — stale grounding is wrong with confidence
The retrieval layer
Questions asked in your team’s own language find your team’s own records — current, scoped, and specific.
- Curated retrieval sets over CRM records, call notes, and deal history — the sources that make an answer specific
- Your pipeline’s vocabulary — stages, segments, product names — encoded so your language maps to your data
- Delivered inside the enterprise tenancy of the tools you run — Gemini, Claude for Teams, or ChatGPT Enterprise
The operating layer
Your team reaches for the tool because it finally earns the reach — and you can see what changed.
- A prompt library written for your motion — the questions your reps actually ask, pre-built and documented
- A before-and-after evaluation: the questions the tool couldn’t answer at kickoff, answered at handover, verified with you
- Hands-on enablement for reps and managers, plus the runbook and the acceptance checklist you sign against
This is the build you need? Start here.
Book a scoping callTHE CASE · WHAT THE RESEARCH SAYS
The upside is real. Grounding is what unlocks it.
The research on AI in sales organizations points one direction: the tools pay off for teams whose AI actually knows their business — and stall for everyone else.
3.7×
more likely to meet quota — sellers who effectively partner with AI — Gartner, 1,026 B2B sellers surveyed (2024)
The gap between owning AI and partnering with it is the gap this build closes: a tool that knows your business is one reps actually work with.
45%
less likely to hit quota — sellers overwhelmed by their tools; half say the amount of technology itself is the problem — Gartner, 1,026 B2B sellers surveyed (2024)
Another tool isn’t the answer. Making the ones you already pay for genuinely useful is.
76%
of CRM users say less than half of their organization’s CRM data is accurate and complete — Validity, State of CRM Data Management, 602 CRM users surveyed (2025)
Grounding is only as good as the data underneath — which is why the diagnostic scores readiness first, and why the honest first step is sometimes the data foundation.
HOW IT RUNS · WEEKS 1–3
Two to three weeks, each phase accounted for.
Every build opens with the two-day diagnostic. On AI Grounding it scores your data readiness against the five gaps — and access hygiene closes before anything ships. Scoped and priced at the diagnostic — the number we lock is the number you pay.
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The diagnostic — read-only
We audit the AI tools you license, map your CRM and sales data against the five grounding gaps, and score which gap is costing you the most. Nothing connects yet. Findings land in the Kickoff Findings Brief, reviewed with you line by line.
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The scope lock
Scope quotes the findings verbatim and the price locks against it in the SOW. If your data layer needs foundation work first, the brief says so plainly — including when the honest first step is the CRM + Data Foundation build instead.
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Access hygiene, then structure
Gap five closes first: the field-level allowlist is agreed and reviewed before any connection exists. Then the structured, relationship-preserving exports and the refresh pipeline that keeps grounding current.
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Retrieval and vocabulary
Curated retrieval sets go in over your real records, the vocabulary library encodes your pipeline’s language, and the prompt library is written and tested against your actual data — not a demo set.
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Evaluation, enablement, handover
The before-and-after evaluation runs: questions the tool couldn’t answer at kickoff, answered now, verified with you live. Then hands-on enablement for the team, the runbook, the acceptance checklist, and every credential in your accounts.
Want the plan mapped to your stack?
Book a scoping callTHE TERMS · EVERY BUILD, NO EXCEPTIONS
Certainty is the product. These terms are how it ships.
The price is the price
Locked at the diagnostic, before build hours start. The number on the SOW is the number on the invoice — and no retainer follows it.
The timeline is the timeline
Two weeks — two to three for AI grounding — with the diagnostic, the build, and the handover on the calendar before work begins.
You own everything
Code, domains, credentials, playbooks — on your accounts from day one. If we disappeared tomorrow, your system wouldn’t notice.
Named owners, start to finish
The people who scope your build lead the build itself. No juniors learning on your instance, no account layer between you and them.
FAQ · ANSWERED STRAIGHT
The questions you should ask anyone building this.
Does our data leave our environment — where does it actually go?
The grounding is built inside accounts you own and the enterprise tenancy of the AI tools you already license — we don’t route your data through a product of ours, and we keep no copy of it. Before anything connects, a field-level allowlist is agreed and reviewed with you, so the AI can only ever see what you’ve explicitly approved. That review closes before any other work ships, not after.
Which AI tools does this work with — and what if we switch later?
By name: Google Gemini, Claude for Teams, and ChatGPT Enterprise. More importantly, the grounding layer itself — the structured exports, retrieval sets, vocabulary library, and prompt playbooks — is built on your data, not inside any one vendor, so if you switch tools later the work carries over. You’d reconnect the new tool, not rebuild the foundation.
Will this work if our CRM data is a mess?
Honestly: it depends on how deep the mess goes, and that’s exactly what the two-day diagnostic measures — grounding built on unreliable data just makes wrong answers faster. If the findings show your data layer needs foundation work first, the brief says so plainly and the right first step is the CRM + Data Foundation build. Being told that before you spend on grounding is the point of the diagnostic coming first.
Do we need to buy new AI licences?
No. This build exists to make the licences you already pay for earn their renewal — it grounds Gemini, Claude for Teams, or ChatGPT Enterprise on your sales data. If you license none of them yet, the diagnostic includes that conversation, but nothing about the build requires new spend on AI tooling.
Isn’t Gemini (or our AI tool) enough on its own?
The tools are genuinely capable — that’s not the gap. Out of the box they answer from what they can see, and your deals, stages, and vocabulary aren’t in that picture: retrieval scope, export structure, vocabulary, freshness, and access hygiene are wiring work the vendor doesn’t do for you. Grounding closes those five gaps so the same licence starts answering about your business.
Will reps actually use it this time?
Reps stopped last time because the answers were generic — usefulness is the adoption plan. When the tool answers about their own deals and accounts, in their own pipeline vocabulary, reaching for it saves time instead of wasting it. The build also ships a prompt library for the questions they actually ask, and hands-on enablement for reps and managers — not a login email and good luck.
Can you show a live system you’ve shipped that’s still running in production?
Yes — ours. Rad Shift’s own revenue stack runs in production: Apollo feeding Instantly, replies landing in Zoho CRM over a direct webhook with full attribution, a CRM that has never been manually updated. That’s the class of data layer this build grounds AI on, and on the scoping call we share a screen and walk it live — the wiring, the records, and the grounding architecture on top.
What happens when a step fails — and how do we find out?
Nothing in this build fails silently. Exports and refresh runs are checkpointed: anything that can’t complete is logged and raised to a named owner instead of vanishing, and a stale grounding set is flagged the moment it happens — because a confident answer from last quarter is worse than no answer. The runbook documents every checkpoint, what the system does, and who gets told.
Which tools have you actually integrated before?
On the data side, by name: Zoho, HubSpot, and Salesforce — plus the outbound stack we run ourselves, Apollo and Instantly, wired over direct webhooks. On the AI side: Google Gemini, Claude for Teams, and ChatGPT Enterprise. If your stack differs, the two-day diagnostic maps it before any build hours are spent.
How do you scope and price — fixed scope, time and materials, or retainer?
Fixed scope, fixed price, no retainer. The category norm is a custom quote at the end of a discovery arc; ours is a number that locks at the two-day diagnostic — AI Grounding starts at $7,999 USD — and goes into the SOW before a build hour is spent. It doesn’t move mid-build, and nothing recurring follows it. The build itself runs two to three weeks.
Who touches our data?
Rad Shift’s core team runs the diagnostic, the allowlist review, and the final acceptance QA. If any disclosed delivery partner ever executes a piece of the work, they are named in the SOW and you consent before any access exists — never silently. Every set of hands on your data is known to you by name, and the field-level allowlist bounds what any of them can reach.
What does handoff look like — are we dependent on you afterwards?
You’re handed a grounded, working setup and everything needed to run it without us: the runbook, the prompt library, the refresh pipeline documented, the before-and-after evaluation results, and every credential in your own accounts. There’s no retainer and nothing that phones home to us. Dependency after handover would be a defect.
THE SCOPING CALL
A 20-minute scoping call. No discovery fee.
We’ll look at your outbound together — the domains, the tools, where replies actually go today — and map it against this build. You’ll leave knowing whether it’s the right fix, what the diagnostic would cover, and the number it locks at. If it isn’t your build, you’ll hear that plainly too.
The calendar reserves a 30-minute slot. The call is the 20 minutes we committed to — the extra ten is buffer, yours back if we don’t need it.
Solving a different problem? Lead-Gen Stack · CRM + Data Foundation — or prefer the diagnosis first? The standalone audit: five days, $2,500, credited in full to any build within 90 days.