Agentic AI · Data strategy · Fractional leadership

Agentic AI, built in production. Not in PowerPoint.

I design, deploy, and run agentic AI for revenue and data teams, backed by 30 years of enterprise data strategy and none of a large consulting firm's overhead.

Start a conversation How an engagement runs
Years in enterprise data
30+
Pipeline supported
$103M+
Engagements
359
account-hygiene Nightly · 06:00
  1. 06:00:02Pulled 18,406 CRM accounts
  2. 06:03:41Scored completeness, duplicates, staleness
  3. 06:07:15Matched 1,204 duplicate pairs
  4. 06:07:16Held 87 uncertain matches for review
  5. 06:07:18Posted the readout to #revops
  6. 06:09:30Merged 1,117 records; audit trail saved

Waiting on a person

Merge 1,117 confident matches?

Approved by Jeff Miller

Merging 1,117 records

Held for review

Nothing changed in the CRM.

Illustrative run

What I build

Agents first. Data underneath.

Agents on real work, running on data someone has made trustworthy, with a person approving anything that leaves the building.

Agents that run every day

Agentic AI, in production

Agents that do real work on a schedule, with multi-model routing, human approval gates, and the health checks that keep them running. I run the same patterns in production myself: six months on an OpenClaw stack, and now Claude Code, with scheduled agents running every day.

  • Agentic AI
  • Claude Code
  • OpenClaw
  • MCP
  • Approval gates
  1. Slack or Teamswhere results land
  2. Human approvalnothing leaves without a yes
  3. Scheduled agentsClaude Code · MCP
  4. Trusted dataMDM · entity resolution

The data agents run on

Data strategy for SaaS and DaaS

From commercial data markets to MDM architecture and data-quality frameworks, I've built and led the teams that operationalize data at enterprise scale. That foundation is what makes an agent's output worth trusting.

  • MDM
  • Data Quality
  • Commercial Data
  • DaaS
  • SaaS

Senior GTM leadership, embedded

Fractional leadership

Fractional VP- and Director-level leadership for data and SaaS companies scaling their go-to-market motion. I embed with your team to drive solutions consulting, pre-sales architecture, and revenue operations.

  • Solutions Consulting
  • GTM Strategy
  • RevOps

How an engagement runs

Each stage stands on its own.

Agentic data quality, delivered in three stages. Each one produces something you can use, and each builds on the last, so you see results before you commit to the next.

  1. Stage 1 · Crawl

    Assess

    Start here

    An agentic data-quality assessment of your CRM and account data. Completeness, duplicates, and staleness are scored and turned into an executive ROI readout: the deliverable I used to build by hand, now built by agents and reviewed by me.

    You getExecutive ROI readout
  2. Stage 2 · Walk

    Resolve

    Entity resolution across your CRM and ERP records. Agents match and merge company records and explain every decision, and anything uncertain goes to a human before it changes your data.

    You getResolved, explained records
  3. Stage 3 · Run

    Operate

    The same checks on a schedule, behind approval gates, delivering ongoing data-quality results into your team's Slack or Teams. Built on the patterns I run in production myself.

    You getScheduled results in Slack or Teams
Jeff Miller
Jeff Miller Founder · Sr. Solutions Architect at 6sense

Who I am

From enterprise data to agents in production.

I'm Jeff Miller, founder of Miller Advisory Partners. I've spent more than 30 years in enterprise data, solutions consulting, and data strategy.

Today I'm a Sr. Solutions Architect at 6sense, helping revenue teams put AI, intent data, and account intelligence to work across their GTM stack. Before that I was AVP of Solutions Consulting at Dun & Bradstreet, where my 9-person team supported $103M+ in pipeline across 359 engagements in under a year. Earlier, I was D&B's Principal Data Management Strategist and subject matter expert across Banking, Insurance, and Retail CPG.

I founded MAP because I kept seeing the same gap: organizations with real data and AI ambitions, but no senior practitioner to turn strategy into something that runs. That's the work I do: built in production, not in PowerPoint.

Writing

Notes from production.

Articles on agentic AI and enterprise data, published here and on LinkedIn.

All writing

Get in touch

Start with the data you already have.

Whether it's an agent you want in production, a data strategy decision, or fractional leadership, tell me what you're working on. I'm straightforward to work with and quick to respond.

Boca Raton, FL · Est. 2026