SideGuy Operator Match · Private AI Consulting · San Diego, CA
San Diego Private AI Consulting · CEO Growth Without Hiring · Secure + On-Prem AI
Helping CEOs scale revenue + operations using secure, private AI infrastructure — without hiring more headcount or sending data to public LLMs
✓ Vetted by PJ
Operator: identity protected until Text-PJ intro · same way StubHub holds reseller info
How this works: SideGuy is the operator-honest matching layer. Like tickets without the holding broker info — you see the service + region + specialty + my vetting; the operator's identity stays held until you Text PJ for the intro. I vet the match, route the conversation, and step out. No fee for the intro; if you engage the operator, they may pay SideGuy a referral. The honesty stays the same regardless.
What they offer
Concrete services. No buzzwords. What buyers actually pay them for.
- Private AI infrastructure design + deployment (on-prem, VPC, or air-gapped LLM stack)
- CEO advisory engagements: which workflows to automate, which to leave human, sequencing
- Custom AI agent + workflow builds (no public-API data leakage)
- Knowledge-base + retrieval-augmented-generation (RAG) systems built on owned data
- AI governance + access policy design for executive team adoption
- Vendor selection guidance for private AI stack (model hosting, vector DB, agent framework)
Who they typically help
The operator's ICP — what kind of buyer fits this match best.
- CEOs of $5M-$100M ARR companies trying to scale without doubling headcount
- Family offices + PE portfolio companies needing AI without compliance/data risk
- Highly-regulated industries (healthcare, finance, legal, defense) with strict data sovereignty
- Founder-CEOs whose competitive moat IS their data (don't want it training a competitor's model)
- Executive teams who tried public ChatGPT and hit a wall on data sensitivity
Where this is the wrong fit
The operator-honest moat. If any of these apply, this is the wrong match — Text PJ for a different intro.
- Pre-revenue startups with no proprietary data (public LLMs are fine — save the cost)
- CEOs who want a chatbot demo, not strategic AI infrastructure (wrong scope)
- Companies expecting AI to replace full headcount in week one (this is augmentation, not replacement)
- Buyers unwilling to invest in any infrastructure (private AI has setup cost)
How they work
Engagement model. Project / fractional / advisory / referral — what to expect.
- Diagnostic engagement to start (~$5-15K, 2-week deliverable: AI readiness audit + sequencing plan)
- Implementation engagements scoped per workflow ($25-150K depending on complexity)
- Ongoing advisory retainer available for executive team coaching ($5-15K/mo)
- Honest about which problems AI can't solve — won't sell you on hype
PJ's vetting note
Same lane I work in (operator-honest AI infrastructure) — different layer. This operator goes deeper on the private/secure/on-prem side, which is where I send CEOs who need the stack but can't put their data in OpenAI's training pool. The 'grow without hiring' framing isn't a marketing line — it's the actual delivery mechanism.
Related SideGuy reads
Comparison pages + sibling matches the buyer should also see.