01
Signal-to-Task Workflows
What gets built
Trigger logic that turns intent, CRM changes, meetings, and account events into prioritized sales tasks.
Outcome
Reps act on the right accounts faster without manually watching every signal.
Sales systems
AI Sales Automation.
We build AI sales automation systems that connect account signals, enrichment, CRM tasks, routing, follow-up, and rep workflows. The goal is not replacing sales work. The goal is removing the manual work that slows qualified pipeline.
Updated June 5, 2026
When it breaks
The sales team is doing work the system should handle.
Reps spend too much time researching accounts, updating fields, and creating follow-up tasks.
High-intent signals do not reliably turn into CRM activity or sales action.
AI tools exist, but they are not connected to routing, governance, or pipeline reporting.
Follow-up quality depends on individual discipline instead of a maintained operating workflow.
Operating model
The workflow we automate.
01
Signals
website activity, CRM movement, job changes, intent, meetings, and account events.
02
Context
account enrichment, contact data, recent activity, and qualification inputs.
03
Decisioning
fit scores, ownership rules, next-best-action logic, and suppression criteria.
04
Activation
CRM tasks, Slack alerts, follow-up prompts, sequences, and meeting handoffs.
05
Governance
QA rules, approval paths, field ownership, and escalation procedures.
06
Visibility
task completion, source quality, reply quality, conversion, and pipeline impact.
What we build
AI sales automation systems that protect rep focus.
02
AI Research Briefs
What gets built
Account summaries, recent news, stakeholder context, pain-point hypotheses, and call prep outputs.
Outcome
Sales conversations start with context instead of generic discovery.
03
CRM Automation
What gets built
Field updates, lifecycle movement, owner routing, task creation, deduplication, and audit trails.
Outcome
The CRM becomes easier to trust and easier for reps to keep current.
04
Follow-up Systems
What gets built
Post-meeting reminders, sequence triggers, proposal follow-up, stalled-opportunity nudges, and reactivation workflows.
Outcome
Follow-up quality improves without depending on memory or spreadsheet tracking.
05
Sales QA Guardrails
What gets built
Approval rules, suppression checks, message constraints, data confidence scoring, and exception handling.
Outcome
Automation supports judgment instead of creating avoidable sales risk.
06
Performance Readouts
What gets built
Dashboards for task completion, signal quality, meetings, conversion, and pipeline sourced from automated workflows.
Outcome
Leaders can see which automations create useful sales motion.
Where it fits
The layer between sales signals and sales action.
Signal capture
Collect account movement, CRM events, web activity, intent, and meeting context.
A usable event stream instead of scattered sales alerts.
Context and scoring
Enrich records, classify fit, score priority, and decide what should happen next.
Sales actions are based on qualified context.
Activation
Create CRM tasks, follow-up prompts, alerts, sequences, or owner handoffs.
The right rep gets the right action at the right time.
Measurement
Track action completion, conversion quality, data quality, and pipeline outcomes.
The team knows which automations deserve to scale.
Best fit
Hire us when the system has to work.
- Your reps are losing selling time to research, admin, routing, and follow-up work.
- Your CRM has enough activity to automate, but the current workflow is inconsistent.
- You want AI to support rep judgment, not replace it.
- You need sales automation connected to data quality, governance, and reporting.
Not a fit
Do not hire us for isolated tasks.
- You only need a list pull without system design or downstream activation.
- You want AI-generated copy without data, QA, targeting, or delivery logic.
- You need a one-off automation that no one will own after launch.
- You are looking for a pure strategy deck instead of a working system.
Implementation
From audit to operating cadence.
01
Audit the sales workflow, CRM tasks, signal sources, and current automation gaps.
02
Define the highest-leverage manual work to remove first.
03
Set data requirements, ownership rules, QA checks, and exception handling.
04
Build the first signal-to-action workflow and test against real records.
05
Connect CRM updates, alerts, tasks, and reporting.
06
Run a reverse demo with sales and RevOps owners.
07
Document maintenance, escalation, and performance review cadence.
08
Prioritize the next automation based on pipeline impact.
Clay-connected sales automation
Clay can enrich the signal layer.
As a Clay First 100 Solutions Partner, Delverise can use Clay to enrich accounts, build AI research briefs, transform signals, and route clean data into the CRM. The sales automation system still has to connect into ownership, follow-up, QA, and reporting.
Explore Clay systemsWhat is AI sales automation?
AI sales automation uses data, workflow automation, and AI research to reduce manual sales work across account research, CRM updates, routing, follow-up, and prioritization.
Does AI sales automation replace sales reps?
No. Delverise builds automation that supports reps by removing admin, surfacing context, and making the next action clearer.
What tools can this connect to?
It can connect to CRMs, Clay, enrichment providers, Slack, sequencers, calendar systems, and reporting tools.
When is a team ready for AI sales automation?
A team is ready when the sales process is repeatable enough to define rules, owners, QA checks, and measurable outcomes.
Next step
Build the system your team can actually run.
We will look at your current motion, identify the highest-leverage system gap, and tell you what we would build first.