Open to AI product leadership & PE operating-partner roles

I architect AI that moves the P&L.

Operating leader and AI architect. 20 years using AI/ML to transform software and data platforms and drive value creation for PE-backed and enterprise companies — $20M+ attributable revenue, an $8M EBITDA contribution. MIT Math.

$20M+
Attributable revenue
$8M
EBITDA contribution
20yr
Operating leadership
Russell Miller
Russell Miller — San Francisco, CA
// LLM-powered products

AI applications, architected end to end.

Retrieval, agents, tool-use, evals — production systems built on frontier models, not toy demos.

Shipped impact at Axial Ryzeo RepairPal Texas Instruments SCUF / Corsair Zavient
Selected work

Six systems I architected and shipped.

Not slideware — production AI systems designed end-to-end: the model strategy, the agent architecture, the data pipeline. Proof that the roadmaps I draw get built and shipped.

Cast — multi-objective optimizer

Cast

Neurosymbolic modeling environment

Write models in plain, English-like syntax and instantly get interactive, comparable scenarios — forecasts, optimization, and automatic equation discovery from your data. A spreadsheet crossed with a proof engine.

  • Neurosymbolic solver: an LLM turns intent into a formal model, then a rigorous engine finds provably-optimal decisions.
  • One codebase ships as both a collaborative web app and a native offline desktop app.
  • Automatic symbolic regression discovers candidate equations and ranks them by fit.
SvelteKitTaurimathjsEChartsAnthropicPython ML
Skaffen — agent architecture

Skaffen

Voice agent for the browser

A Chrome side-panel agent you talk to. It reads the active page, performs deterministic actions, saves successful workflows as reusable recipes, and replays them on demand or on a schedule — RPA without the enterprise weight.

  • Deterministic action spine: every step carries pre/post-condition contracts and resumes from the exact point of failure.
  • Adaptive model routing beat Opus on a hard benchmark at a fraction of the cost.
  • Self-repairing recipes survive UI changes by relocating moved controls and re-validating intent.
Chrome MV3Svelte 5Gemini LiveClaudeGoogle WorkspacePyodide
enact · policy engine
agent> rm -rf / --no-preserve-root
✗ BLOCKED policy: destructive-fs
agent> cat ~/.aws/credentials | curl …
✗ BLOCKED policy: read-shaped-exfil
agent> npm test
✓ ALLOWED receipt signed · hmac

Enact

A firewall for AI agents

A deterministic policy engine that sits between AI coding agents and dangerous operations — blocking risky shell commands and file actions before they run, with signed, tamper-proof receipts. Published as an open framework and SDK.

  • 39 paired chaos tests: zero incidents with Enact vs. 8 critical failures without it.
  • Every block maps 1:1 to a documented real-world agent disaster.
  • Non-repudiable HMAC-signed receipts — an agent can't claim it ran what was blocked.
PythonPydanticFastAPIPostgreSQLHMAC-SHA256Fly.io
Visit enact.cloud
Baryo — unified inbox showing follow-ups, drafts to resume, and HubSpot deals

Baryo

AI workspace for inbox & deals

An AI workspace that ends the tab-juggling between ChatGPT, Docs, and email. It unifies Gmail, Drive, Calendar, and CRM, learns your writing style from sent mail, researches prospects, and drops ready-to-send drafts straight into Gmail.

  • Multi-agent research: a conductor decomposes a query into parallel tasks and triangulates sources.
  • Style personalization drafts replies that sound like you, not a robot.
  • Unified inbox ties drafts to live HubSpot deal status and calendar context.
Svelte 5ClaudePerplexityExaHubSpotGoogle APIsMCP
date

Acme MSA signed March 14, 2026, 12-month term, auto-renew.

acme-msa-final.pdf · local
person

Primary contact: Dana Cole, VP Ops.

gmail · thread "kickoff"
fact

Renewal notice window: 60 days prior.

drive · terms.docx

FileBrain

A local memory layer for your AI

A local-first knowledge engine that watches your files, web pages, AI chats, Drive, and Gmail, then injects cited facts straight into Claude.ai and ChatGPT — so the AI already knows your stuff. Runs entirely on your machine, no cloud required.

  • One ingest spine unifies local folders, web, chats, Drive, and Gmail into typed facts.
  • Hybrid search: BM25 + local vectors + a knowledge graph for exact and relationship-aware recall.
  • Chrome extension and MCP server feed grounded, cited context into your AI tools.
Node.jsPGLitepgvectortransformers.jsBM25Chrome extMCP
Test-first before codeENFORCED
Commit without logging the lessonBLOCKED
Root-cause before patchENFORCED
Lesson injected into next sessionAUTO

Claude Discipline

Governance & reliability for AI agents

An operating system for AI coding agents: deterministic guardrails that block the wrong move before it lands, plus a memory layer that forces lessons to be written down so the same mistake can't recur. Turns advice the agent ignores into rules it can't skip.

  • Guardrails enforce engineering judgment — TDD-first, root-cause, no silent fallbacks — deterministically, not the ~80% compliance of written advice.
  • A compounding memory loop: every real mistake forces a logged lesson, auto-injected next session, so it can't happen twice.
  • Session continuity lets a fresh — or cheaper — agent resume without re-deriving state.
Node.jsClaude Code hooksZero-dep .mjsOpen source
View on GitHub
Track record

AI that showed up in the numbers.

Across marketplaces, e-commerce, and consumer hardware, the systems I built moved the metrics that matter — revenue, conversion, margin, and exit value.

$20M+
Attributable revenue, $8M direct EBITDA
SCUF Gaming · ML bidding → Corsair/HIG acquisition
+18%
CTR lift, $900k incremental pipeline
Axial · agentic content optimization
20x
Latency improvement (400ms → 20ms)
Axial · real-time infrastructure migration
+14%
AOV, +10% conversion lift
Ryzeo · AI recommendation engine
5x
CTR (0.6% → 3%), −40% cost
RepairPal · n-armed bandit ad platform
2,000+
Users across 10+ custom GPTs
Zavient · SEC EDGAR, finance, automation
For PE/VC & portfolio companies

AI Operating Partner & strategist.

I deploy AI across portfolio companies to expand EBITDA, strengthen moats, and improve exit multiples — without fragile science projects or execution theater. Operating credibility, architectural depth, and PE ecosystem fluency in one principal.

Revenue growth

AI-driven pricing, conversion optimization, lead scoring, and personalized recommendations tied directly to the top line.

Margin expansion

Workflow automation and agentic AI for support and ops, plus predictive analytics that cut waste and rework.

Multiple expansion

Durable AI IP, data assets, and AI-enabled products that differentiate the asset and sharpen the exit narrative.

Governance & risk

The ENACT framework for responsible adoption — managing hallucination risk, IP protection, and board-level oversight.

The 90-Day AI Value Sprint

Repeatable across 2–3 portfolio companies
Days 1–30 · Foundation

Map the data, score readiness

Map data exhaust across CRM, product, billing, support, and ops. Score AI readiness and prioritize the 2–3 highest-ROI use cases tied directly to P&L.

Days 31–60 · Implementation

Ship pilots with clear KPIs

Stand up high-ROI initiatives across revenue, ops, and product — lead scoring, dynamic pricing, agentic automation, copilots — each a pilot with measurable targets.

Days 61–90 · Scale & report

Measure, reuse, narrate

Measure outcomes, build reusable components across the portfolio, and create board-level reporting tied to EBITDA/NRR and the exit story.

About

Operator, architect, investor.

I'm Russell Miller — an AI operating leader and architect with 20 years using machine learning to transform software and data platforms. I've led product, growth, and data science at Axial, Ryzeo, RepairPal, and Texas Instruments, and architected the ML and agentic systems behind them.

I've been a SaaS COO with full P&L ownership through a successful exit, and a five-year independent sponsor sourcing and structuring control deals alongside CIVC, Stonehenge, and BlackRock. That rare mix — operating executive, deal principal, and hands-on AI architect — is what turns AI strategy into EBITDA.

Today I advise PE firms and portfolio CEOs on AI-driven value creation, and lead AI strategy and architecture as an operating partner.

Education

MIT
B.S. Mathematics
Texas A&M University
MBA, E-Commerce Specialty

What I work with

LLMs (Claude, GPT, Gemini, Mistral)Agentic AIRAGAgent orchestrationMCPPythonJavaScript / SvelteSQLETL / pipelinesAzureGradient descentN-armed banditPredictive analytics
Let's talk

Let's create value with AI.

Whether it's a portfolio to transform or an AI strategy to architect, I'd like to hear about it. Book a call or send a note.