AI Advisory
for PE-Backed Companies
Most AI consulting is strategy decks. This is fixed-bid diagnostics and shipped builds. I help PE sponsors and portfolio operators find the workflows where AI agents compound into EBITDA. Then I build them.
How I Engage
Three phases. Each one a real contract.
Most clients start with the diagnostic. Some stop there with a roadmap they execute themselves. Others run the full path. Each phase stands on its own.
Operating Diagnostic
2–3 weeks · fixed fee
From $15K
A structured scan of the business across revenue, operations, and back office. I interview the operating team, score every workflow on a leverage framework, and deliver a ranked roadmap with build / buy calls and effort estimates.
- Workflow inventory across revenue, ops, and back office
- Scored leverage map (Volume × Latency × Variance × Synthesis)
- Ranked build queue with effort and value estimates
- Recommended 90-day implementation plan
Build Sprints
4–8 weeks per workflow · fixed bid
From $20K
Fixed-bid build of the highest-ROI workflows from the diagnostic. Shipped into production, integrated with existing systems, instrumented so the value is visible. Each sprint is one workflow, one milestone, one bill.
- Production agent or workflow shipped
- Integration into existing tooling and systems
- Operator training and handover docs
- Instrumentation to track time saved and revenue moved
Ongoing Partnership
Monthly retainer
From $5K / mo
For platforms with an active M&A cadence. I maintain the agent stack, build new workflows as they surface, and onboard each newly acquired company to the same playbook. Scales with your deal flow, not my sales cycle.
- Agent maintenance and version upgrades
- New workflow builds as priorities shift
- AI integration playbook applied to each add-on
- Quarterly leverage review with the operating team
How We Pick
Effort vs impact. Nothing fancier.
Every candidate workflow gets two scores: how much it would move the business if shipped, and how much it would cost to ship. We start at high impact and low effort. We work down from there. We don't build vanity AI.
Build first
Where most of the diagnostic budget goes. Quick wins with real EBITDA attached. The bar to ship is low because the cost of being wrong is small.
Build next
Worth the investment, but scoped carefully. We sequence these behind quick wins so the team sees ROI before committing capital to longer builds.
Defer
Cheap dopamine. Often what teams ask for first because it’s familiar. We park these and revisit only after the high-impact queue is shipped.
Don’t build
Every business has them. These are the AI projects you regret six months in. Naming them out loud in the diagnostic is half the value.
Example Workflows
What this looks like in your business.
A few of the patterns we see ship fast and pay back quickly across services businesses. Not exhaustive. The diagnostic surfaces which apply to your specific operation and what they're worth in dollar terms.
Speed-to-lead
Service request lands at 11pm. By 11:02 the agent has pulled the account history, drafted a personalized reply with a same-day SLA, and woken the on-call rep. After-hours win rate doubles.
Proposal and quote generation
A rep used to lose four hours per quote pulling specs, codes, prior pricing, and history. The agent drafts the proposal in ninety seconds. Reps spend the week selling, not formatting.
Prospecting and lead intelligence
Agent watches filings, hiring patterns, and tech-stack signals across thousands of target accounts. When a buying trigger fires, the rep gets the lead with the context already written.
Renewal and churn defense
Every contract expiry, usage signal, and support history monitored continuously. At-risk renewals flagged ninety days out with a drafted save outreach. Net retention is the valuation story.
Customer service triage
Sixty percent of tickets are simple and never reach a human. The forty percent that are hard reach the right human with full context already attached. AHT drops, CSAT rises.
Compliance and inspection documentation
Every regulated artifact extracted, structured, filed, and searchable. The compliance officer goes from drowning in PDFs to actually running a function.
Knowledge capture from senior operators
Forty years of tacit know-how from your senior tech, recorded across normal workflows, becomes a searchable layer the whole team can query. Retirement risk solved.
M&A integration glue
Every add-on you acquire has different software. The agent bridges schemas in days instead of months. Your platform absorbs new companies without burning out IT.
The Process
Predictable from week one.
Fixed fee. Fixed timeline. Fixed deliverables. PE buyers are tired of consulting engagements that scope-creep. This one doesn't.
01
Discovery call
We sit down for half an hour. You explain the business and the constraints. I tell you whether the diagnostic makes sense or not. If not, I'll say so and refer where I can.
30 minutes · no fee
02
Diagnostic SOW signed
Scope and timeline locked. I work directly with the operating CEO, the heads of the functions in scope, and the CFO. No layers between us.
Fixed fee, 50% upfront
03
Workflow scoring
Interviews, system walkthroughs, document review. Every candidate workflow gets scored on impact and effort. The output is data, not opinion.
Weeks 1–2
04
Roadmap readout
Ranked build queue with effort estimates, value estimates, and clear build / buy calls. Delivered as a working document the operating team can use, not a deck.
Week 3
05
Build or hand off
You either run the roadmap yourselves, or I take the top items into fixed-bid build sprints. The diagnostic is designed to stand on its own either way.
Optional
Why Me
An operator who actually ships with AI.
Fifteen years running revenue and operations inside SaaS. Salesforce, PagerDuty, Deloitte Consulting, then COO of an 85-person European hotel software business. I left in August 2025 to build a SaaS product solo, with AI doing the engineering. It works.
0
Engineers Hired
$1.4B
Largest BU Operated
15+
Years SaaS Operating
1
Person Building Team
Product Proof
Searcher OS
Production SaaS · built solo with AI agents
Salesforce for business acquisitions. Next.js, Supabase, Stripe, Python scrapers, ~15 integrated surfaces. Profitable, paying customers, growing. No engineering team. Claude Code writes the code. Orchestrated agents help me scale operations. This is the playbook I bring into a portfolio company.
See the productTrack Record
Fifteen years operating SaaS.
The diagnostic doesn't pattern-match from PowerPoint. It pattern-matches from having actually been the operator. Running revenue, ops, and post-acquisition integration at scale.
Mews
2024 - 2025SVP, Business Operations
- COO role with 86-person team across revenue operations, IT, procurement, FinOps, and people technology
- Transformed operations of a hyper-scaling 50%+ growth, $250M revenue business
- Personally redesigned variable compensation plans for a multi-product SaaS/Fintech blended sales motion
- Launched quote-to-cash transformation, company OKR framework, and quarterly business reviews
PagerDuty
2020 - 2023VP, Strategy & Operations
- Reaccelerated growth from 26% back north of 33% on a $200M business within the first year
- Series of GTM transformations: sales process, forecasting, deal qualification, messaging, and incentives
- Drove sustained net revenue retention north of 120% through platform repositioning
- Led GTM due diligence and integration of the largest acquisition in company history
Leanplum
2018 - 2020SVP, Business Operations
- Built first territory and segmentation model. Contributed to several quarters of 75%+ ARR growth
- Launched data-driven forecasting, CPQ, territories, and deal desk from scratch
- New pricing structure and deal desk drove a 12% increase in gross margins
- Designed ICP and propensity-to-buy scoring adopted across sales and marketing
Salesforce
2014 - 2018COO, Platform ($1.4B BU)
- New price point became 30% of bookings within four months and raised average deal size 20%+
- Revenue attribution model eliminated inefficient channels and improved cost to book by 25%
- Propensity-to-buy model: 15% of the customer base delivered 60% of sales
- Grew Desk.com 44% in a single year through incentives, pricing, and analytical rigor
Request a Discovery Meeting
Tell me about the business.
No fee, no deck, no pitch on the first call. Describe the business and the constraint. I'll tell you whether the diagnostic is the right move. If the answer is no, I'll say so and point you somewhere useful.
Most replies inside a day. Engagements are reserved for PE-backed companies, platform launches, and operators serious about shipping. The form on the right is the fastest way in.
Tell me about the business