Use case
AI operator for revenue teams
Grow connects to the CRM your team already sells from, matches the accounts worth contacting, drafts outreach grounded in what the record actually says, and stages every send for a person to approve.
What this delivers
Your CRM stays the source of truth: Grow reads live pipeline inside your tenant boundary, proposes the next account and the next message from what the record actually says, and stages every send for a human decision before it leaves.
Live CRM data
Grow reads your connected Salesforce or HubSpot record, not an uploaded snapshot
Review before send
Outbound is staged for a person to approve, edit, or discard before it goes out
Grounded drafts
A message can be traced back to the account context that produced it
The operating problem
Selling time gets spent on the work around selling.
Revenue teams rarely lack tooling. What they lack is a system that reads the pipeline they already have and does the assembly work between the CRM and the next conversation.
Failure mode 1
Pipeline data drifts
Updating a deal competes with working the deal, so the record moves away from reality and every report built on it inherits that drift.
Failure mode 2
Account research is manual
Choosing who to contact next means re-running the same search across the CRM, a browser, and someone’s private notes.
Failure mode 3
Personalization does not scale by hand
Templates that ignore the account record read like templates, and the personalization that fixes that is done one message at a time.
Failure mode 4
Forecasts come from memory
A forecast assembled in a spreadsheet reflects what the person remembered, not what the CRM shows on the day it is asked.
Why this matters commercially
The pipeline data you already pay for is the asset most GTM tools never read.
Grow runs against the connected CRM rather than a separate copy of it, so account selection, outbound drafting, and pipeline questions all resolve from the same record the team is measured on. That removes the export-edit-reimport loop and keeps the reviewed message and the CRM inside one operating boundary instead of two tools that disagree.
One source
Account selection and message drafting read the same connected CRM record
No export loop
Work runs against live data instead of a spreadsheet copy that ages immediately
Human in the loop
A person approves outbound, so volume never means giving up the message
How the work runs
From a connected CRM to a reviewed message.
01
Connect the CRM
Authorize Salesforce or HubSpot through the governed connection layer; Grow reads pipeline inside your tenant boundary.
02
Describe the motion
Say what you sell and who you sell it to. That becomes live targeting criteria, not a static list someone maintains.
03
Match accounts
Grow surfaces accounts that fit, along with the record context that made each one a match.
04
Draft grounded outreach
Sequences are written from the account record rather than a generic template with a merge field.
05
Review, send, write back
Every send waits for a human decision, and the resulting activity returns to the account it came from.
System view
Where Grow sits between your CRM and your outbound.
Architecture
How a revenue workflow is assembled.
Grow is a surface on the UbiVibe runtime. The layers below are the same ones every other workflow uses; what changes is the pipeline data attached at the context layer.
Identity
Resolved before executionYour tenant, team, and CRM permissions resolve before any account data is read.
Pipeline context
Scoped to the tenant boundaryThe connected CRM becomes usable operating context: accounts, owners, stages, and activity.
Targeting and drafting
Provider-agnostic routingModel routing turns your description of the motion into account criteria and message drafts.
Staged execution
Review gate before sendSends and CRM writes run as bounded actions that hold for approval where approval is required.
Evidence
Trace attached to the actionEach send carries the account context that produced it and what happened afterward.
How it is built
What the revenue workflow actually does underneath.
Governed CRM access
Salesforce and HubSpot are reached through the canonical connection layer, so one connection serves reporting, outreach, and follow-up instead of an integration per feature.
Record-grounded generation
Drafts are generated against fields on the account record, so a message can be traced back to the data that produced it.
Staged actions
Outbound is an explicit action with a review state, not a side effect of a chat response that already happened.
Write-back with provenance
Activity returns to the CRM attached to the account it came from, so the record stays the system of record.
Connected systems
The systems a revenue motion already runs on.
Grow reaches CRM, email, calendar, and enrichment systems through one organization-scoped connection layer, so a system connected for one workflow is available to the others inside the same tenant boundary.
Governance & security
Outbound that runs on your rules.
Revenue work touches customer records and sends messages in your company’s name, so the control surface is part of the workflow rather than a setting somewhere else.
Human review before send
Generated outreach is staged for approval; volume never means an unreviewed message going out under your domain.
Scoped CRM permissions
Grow operates inside the permissions granted to the connection, never above them.
Tenant isolation
Pipeline data, drafts, and activity history stay inside your organization boundary.
Traceable actions
Each send and write-back records what triggered it and which data it used.
Implementation
What adopting this looks like.
01
Connect the CRM
Authorize the connection first; nothing is read before identity and permissions resolve.
02
Describe the motion
State the offer, the segment, and the territory rules the team already works to.
03
Review the first batch
Work through matched accounts and drafts with a person in the loop to calibrate targeting and tone.
04
Move to a running cadence
Once the pattern is right, the loop runs continuously with review kept where you want it.
Example workflows
Concrete revenue workflows.
Example
New-segment prospecting
Point Grow at a segment you have not worked yet; it matches accounts from the connected CRM and drafts a first-touch sequence grounded in each record.
Example
Stalled-deal review
Ask which open deals have had no activity since a given point and get the list with the account context that explains each one.
Example
Reply triage
When a prospect replies, the reply is classified and a next action is proposed against the account instead of sitting in an inbox.
Example
Pipeline question in plain language
Ask what changed in the pipeline this week and get an answer read from the CRM rather than from a spreadsheet someone assembled.
Example
Renewal and expansion pass
Surface accounts approaching renewal with the activity and ownership context already attached to the record.
Example
Territory handover
When ownership changes, the incoming rep gets the account context and open threads from the CRM instead of a verbal handover.
Limitations and considerations
What this does not do for revenue teams.
- Grow reads what the CRM contains. If a deal advanced in a phone call that nobody logged and no connected system observed, that context does not exist and no model recovers it.
- Outbound is constrained by deliverability, sending domain reputation, and the consent and privacy rules applicable to the contacts involved. Those are boundaries, not settings.
- Review in front of sends is a real operational cost. Teams that want fully unattended outbound at volume are asking for a different risk posture than this is designed for.
- ICP definition remains a human judgment. Account selection is only as good as the criteria written down, and vague criteria produce vague lists faster.
- Connector coverage for heavily customized CRM objects, managed packages, and unusual field types may require mapping work before those fields are usable.
- None of this fixes a pipeline model that does not describe the real sales motion. That correction is a business conversation that has to happen first.
Questions
Does Grow replace our CRM?
No. Salesforce or HubSpot stays the system of record. Grow connects to it and runs the execution layer — account selection, outreach, reply handling, and scheduling — against live records, so the CRM stops being a place people retype what already happened.
Does it send emails without us seeing them?
No. Every outbound message is staged for human review before it leaves. That is the default posture rather than an optional setting, and approval scope widens only where a team has evidence the review queue is consistently clean.
How is this different from a sequencing tool?
A sequencer runs a template against a list and finds out about pipeline changes later, if at all. Grow reads the live CRM as it works, so account state is current at send time and the outcome is written back to the same record rather than to a parallel system.
What data does it read?
Only what the connected credential is permitted to read, scoped to the objects the motion needs. Reads are live rather than from an export, so decisions reflect the current record state.
Do we need clean CRM data first?
You need one segment where the records are trustworthy and the stage definitions match reality. A full data cleanup project is a common way to spend a quarter without shipping anything; a single verified segment produces a measurable result much sooner.
What should we measure?
Qualified conversations created and pipeline generated, compared against a baseline you established before turning anything on. Activity volume is easy to increase and tells you almost nothing about whether the motion improved.
What happens to replies?
Reply handling is usually the real constraint, and it is the step most often left manual. Replies are surfaced against the account they belong to with a proposed next step staged for review, rather than depending on somebody noticing an inbox at the right moment.
Can we start without changing how the team works?
Largely, yes, and that is the point of starting with one segment. The CRM stays where it is, the motion stays what it is, and the change is that execution reads live records instead of an export. If the change requires a reorganization before it can produce anything, the scope is too wide.
Start with ARIA
Ask ARIA to run ai operator for revenue teams.
Describe the outcome you need here. ARIA determines the capabilities, systems, data, and workflows the job requires, then executes it inside the permissions you set.
- ARIA acts only through the systems and permissions you connect.
- Connections use scoped credentials you can change or revoke.
- Actions are recorded, and consequential ones can require approval.
Use case
Run the revenue motion on the pipeline you already have.
Connect the CRM, describe what you sell, and review the first batch of matched accounts and drafts before anything goes out.