Ariel LopezSOLUTIONS CONSULTANT PORTFOLIO

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Operating internal system

AIDIS Outreach Command Center

Prospect research, qualification, review, and follow-through

THE BUSINESS PROBLEMHow can prospect research, drafts and follow-up stay organized while keeping the sender in control?
ACTUAL OUTCOME / CURRENT STAGEAn operating internal workflow with a 100-prospect queue in the September 2026 snapshot and a manually controlled pilot.

I designed and operate an Airtable CRM workflow through AI chat and connected tools, directing AI-assisted integration work and reviewing qualification, drafts and next actions.

Explore the workflow ↓View resume ↓

The problem

I organized the work around the decisions needed before outreach: whether a prospect fits, what the research supports, whether the contact is appropriate, and what factual next action should follow.

My decisions

Review before acting

Keep qualification, proposed drafts and manual sending separate. A draft is something to review, not proof a message was sent.

Preserve exceptions

Represent holds, stop conditions and requested callbacks so a generic cadence cannot overwrite a specific contact outcome.

Reconcile the record

Check existing actions before creating more, and distinguish planned activity from completed work.

Explore the workflow · Fictional example

From prospect research
to a reviewed next action.

01 · Research

Understand the prospect

Sample Harbor Services: record the source and a possible workflow need before claiming a fit.

02 · Qualification

Separate evidence from a guess

Business fit appears plausible. Contact-role evidence is missing, so the record remains on hold.

03 · Human review

Resolve the hold first

Next action: verify the decision-maker’s role. The example does not send a message.

System view

Apollo research → Airtable record → AI-assisted draft → human review → manually controlled next action

Hold: contact role unverified. A completed draft does not establish readiness to send.
Actual project: an operating internal Airtable workflow and manually controlled outreach pilot. The evidence below summarizes operating decisions; the walkthrough uses fictional records.

Evidence and outcome

AIDIS Outreach Command Center: Illustrative workflow with fictional data · Private CRM is not shown
Illustrative workflow with fictional data · Private CRM is not shown · Captured September 2026

Selected source evidence, summarized for this portfolio. Newly authored examples use fictional data.

An operating workflow with visible controls

The September 4 reconciliation records a 100-prospect queue and a controlled pilot. It distinguishes manual outcomes, unexecuted actions, and future work; these are operating records, not customer or revenue totals.

Source basis: Final September 4, 2026 operational reconciliation; private records paraphrased.

A correction changed the next action

The reconciliation identified overlap between prior calls and a generic future email cadence. The approved correction preserved requested callbacks and holds, and adjusted remaining outreach preparation to reflect what had actually happened.

  • A requested callback keeps its requested-call path.
  • An unresolved identity or disposition stays on hold.
  • Previously existing actions are reused where appropriate instead of duplicated.

Source basis: Final operational correction record; all personal and company details omitted.

This is actual internal operation through Airtable, Apollo, AI-assisted tools and human review. It does not establish unattended outreach, sustained campaign conversion or revenue results.

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