Imperium AI Knowledge Base

COMPANY OVERVIEW & MISSION

1.1 Company Identity

Imperium AI is an AI Managed Service (AIMS) Provider founded by Matthew Hebron, pioneering solutions that extend the human frontier through decentralized AI infrastructure. The company’s mission is to reclaim control of artificial intelligence from centralized cloud giants by delivering private, on-premises large language models (LLMs) and AI agents tailored to each client’s environment. Worthy of our Creator and our country’s calling. Founded on six cultural pillars (Customer Obsession, Craftsmanship, Courageous Innovation, Servant Leadership, Liberty & Hope, and Relentless Accountability), Imperium AI serves compliance-sensitive industries including legal, healthcare, and government sectors. The company operates on a Software-on-Demand (SoD) model versus traditional Software-as-a-Service (SaaS), offering complete privacy, security, and cost efficiency through kilowatt-hour metering rather than per-seat subscriptions. With a proven founder who scaled a company from $9M to $20M in 15 months, Imperium AI is positioned to evolve from mid-market custom solutions to enterprise and government contracts, targeting $36.5M ARR through a six-phase growth strategy.

1.2 Value Proposition

Hebron’s latest venture emerges as a response to the rapid centralization of AI. ‘If three mega corps own the latent knowledge of eight billion people, we no longer have a free market,’ he says. In a world dominated by Software-as-a-Service (SaaS), Hebron advocates for what he calls Software-on-Demand (SoD): a decentralized model that delivers private, on-premises large language models (LLMs) and AI agents tailored to each client’s environment. Trained on a company’s internal documents and workflows, these models offer organizations greater autonomy and security. They also significantly reduce costs by metering usage via kilowatt-hours rather than per-seat subscriptions.

LEADERSHIP & FOUNDER PROFILE

2.1 Founder Background

Redefining the Edge: How Matthew Hebron is Challenging the Future of AI Infrastructure. From rebuilding bicycles in the scrapyards of rural East Texas to scaling multimillion-dollar enterprises, Matthew Hebron’s entrepreneurial story is rooted in resilience, ingenuity, and bold, first-principles thinking. Today, he’s applying those same values to one of the most pressing challenges in tech: reclaiming control of artificial intelligence from centralized cloud giants.

As a child, Hebron repaired discarded bikes and bartered them for necessities. That resourcefulness would become the DNA of his leadership style. ‘When you have nothing, you discover everything is negotiable,’ he reflects. That principle followed him into his adult career, where he has since led companies through turnarounds, scaled stagnant firms, and launched new ventures across industries including aerospace, healthcare, real estate, and education.

In 2023, Hebron executed a remarkable transformation: taking a 20-year-old company from $9 million to $20 million in annual revenue in just 15 months, a leap he attributes to process re-engineering, cost discipline, and adaptability under pressure. This demonstrates his proven ability to scale businesses rapidly through strategic operational improvements.

2.2 Leadership Approach

SERVE Leadership Model:
S – See the customer first-hand monthly.
E – Equip teams with context, resources, and autonomy.
R – Remove blockers within 24 hours.
V – Vocalize the vision until everyone can repeat it.
E – Exhibit the pillars under pressure—especially when projects slip or rockets explode.

Leaders are stewards, not owners; authority exists to accelerate others’ talent toward the mission.

COMPANY CULTURE & VALUES

3.1 Cultural Pillars (6 Core Principles)

Six core principles defining our values, behaviors and antipatterns: Customer Obsession, Craftsmanship, Courageous Innovation, Servant Leadership, Liberty & Hope, and Relentless Accountability. These pillars form the foundation of our culture and guide how we fulfill our mission.

Customer Obsession: Begin with the customer and work relentlessly backward. Conduct ‘Day-in-the-Life’ customer interviews. Write ‘Delight Hypothesis’ defining success in customer’s words. Antipattern: Building to spec without firsthand customer input.

Craftsmanship: Build with empowered artisans. Engineers own quality metrics end-to-end. Designers run ‘pixel-perfect’ reviews before release. Antipattern: ‘Ship it now, fix it later’ mindset.

Courageous Innovation: Advance boldly when the odds are long. Run pre-mortems to surface risks, then move fast. Celebrate well-scoped failed experiments on Demo Day. Antipattern: Analysis paralysis; waiting for 100% certainty.

Servant Leadership: Treat work as worship and leadership as service. Weekly 1:1 ‘service check-ins’: How can I unblock you? Profit-sharing tied to community impact KPIs. Antipattern: Ego-driven hero culture.

Liberty & Hope: Unlock new horizons that honor liberty and inspire hope. Open-source non-strategic tooling. Donate 1% of time/profit to civic tech/education. Antipattern: Inventions that centralize power or erode privacy.

Relentless Accountability: Excuses are a sign of mediocrity. ‘Own-the-Outcome’ post-mortems with root cause. OKRs published company wide. Antipattern: Blame-shifting; success measured only by effort.

3.2 Cultural Operating System

Vision & Strategy: North-Star Narrative memo (3 yrs out) keeps every initiative tied to the frontier we’re extending.
Goals & Metrics: Company → Team → Individual OKRs align work to the pillars; surfaces measurable ‘delight’.
Decision-Making: C.U.T.E. filter (Customer first, Uncompromised quality, Test bold hypothesis, Ethical & liberty-honoring) ensures consistent cultural lens.
Rituals: Monday ‘Customer Story’ stand-up, Bi-weekly Demo & Debrief (wins + failed bets), Quarterly Service Day in local community reinforces obsession, courage, service.
Feedback Loops: Semi-annual 360° ‘Craft & Character’ reviews rate both results and pillar-aligned behaviors.
Recognition: ‘Frontier Tokens’ (peer-given points redeemable for learning budget) rewards living the pillars more than title or tenure.

3.3 Talent Practices

Inside his own organization, Hebron emphasizes adaptability and core values over conventional experience. Hiring is based on alignment with six pillars: Customer Obsession, Craftsmanship, Courageous Innovation, Servant Leadership, Liberty & Hope, and Relentless Accountability. Fewer than 1 in 1,000 applicants are hired, but rejected candidates may be invited into a paid fellowship program, which offers training in applied AI and tests for ingenuity. Roughly half of fellow’s transition into full-time roles.

PRODUCTS & SERVICES

4.1 Core Service Offering

Our Solution: Imperium AI is an AI Managed Service (AIMS) Provider. We eliminate the mundane work to allow humans do what they do best, creative, analytical, and strategical decision making. Services: Build local (offline if necessary), private, and secure custom AI software and AI employees. We onboard to your existing tech stack not the other way around. Update your AI infrastructure to include the latest AI tech relevant to your business on a weekly basis. This approach ensures maximum security, privacy, and integration with existing business processes.

4.2 Specific Products

Imperium App – lean job listing mobile app that allows employers to recruit both human and AI employees at 5% of the cost of ZipRecruiter at 6% of the time.

Molly AI – Molly is a cloud-based marketing AI employee that conducts keyword research, competitor analysis, backlink acquisition, blog generation/distribution, podcast generation/distribution, and optimizes your WordPress website. (Included in Imperium App subscription).

Custom built AI employees – from operations and Medicaid billing to document sorting and file management, Imperium AI builds AI employees that operate entirely on your private and local server. Who needs chat GPT when you can have your own LLM that utilizes your database, policies, procedures, and experience.

4.3 Industry Specific Solutions

AI Legal Assistant – Our AI legal assistant is an on-site LLM/AI agentic infrastructure that acts as a direct assistant to any attorney with the privacy security they need for their clients. This AI employee can assist with discovery, document drafting, interrogatories, and much more. Rather than risking sensitive data with ChatGPT law firms now can have an onsite AI model that is an expert on all of their firms’ policies, procedures, best practices, and drafting templates on a portable server.

Healthcare AI (QRTP)
Industry Specific Solutions Custom AI Employees & Software: Imperium AI is currently working on building an AI operations software and an AI employee for one of the largest Qualified Residential Treatment Providers (QRTP) in Illinois.
AI Operations Software – This software & LLM operates completely offline on a private and local server making it one of the most secure AI platforms on the market. This software ensures that behavioral technicians are filling out shift forms on offline devices based on occurred events or regulated time intervals, it then files these forms to their respective files and stores key data points on client behavior allowing them significantly to improve their services.

4.4 Victor Cube Product Line

Powerful AI‑augmented legal discovery in one sleek metal cube

TIER 1 – VICTOR APP ($99k)

“Your Virtual Paralegal in a Box”

Document Conversion: any file type → searchable legal text
Legal Theory Generation: raw documents → court‑ready analysis
Basic Case Summaries: upload files → get legal strategy outline
Secure Processing: attorney‑client privilege protection built‑in

Qualifying questions

“Do you spend more than 10 hours/week on document review?”
“How long to prepare a case summary for new matters?”
“Would a virtual paralegal that works 24/7 interest you?”

Target: solo practitioners, small firms (1–10 lawyers)
Result: 60 % faster document processing

TIER 2 – VICTOR ASSITANT ($179k)

“Your Virtual Attorney in a Box”

Everything in Victor App plus:

Visual Discovery: interactive relationship maps, timelines, people libraries
Advanced Legal Analysis: pattern recognition, evidence clustering
Case Preparation Tools: brief writing, deposition outlines, discovery requests
Stunning Visualizations: 3‑D case maps, chronological analysis
Legal Research Integration: citation checking, precedent analysis

Qualifying questions

“Do you handle complex litigation with multiple parties?”
“Would visual case mapping help your trial preparation?”
“Are you looking to compete with larger firms on case quality?”

Target: mid‑size firms, litigation specialists (10–100 lawyers)
Result: complete visual legal‑discovery platform

TIER 3 – VICTOR ENTERPRISE ($299k)

“Your Complete Legal Operations Center”

Everything in Victor Assistant plus:

Enterprise Case Management: multi‑matter tracking, client portals
Firm Administration: user roles, billing integration, compliance reporting
Multi‑Industry Adaptation: beyond legal → compliance, due diligence, investigations
Custom Workflows: tailored processes for your practice areas
Infinite Scalability: grows with your firm, handles any document volume

Qualifying questions

“Do you manage multiple practice areas or offices?”
“Would you benefit from one system handling all confidential document work?”
“Are you interested in expanding beyond traditional legal services?”

Target: large firms, corporate legal departments, multi‑practice enterprises
Result: universal confidential‑document intelligence platform

Universal Selling Points

Victor Cube hardware

Plug & Play: ready in 30 minutes — no IT department needed
Your Data Stays Yours: no cloud, no subscriptions, complete ownership
Apple‑Grade Design: beautiful, reliable, silent operation
Future‑Proof: continuous software updates, modular upgrades

ROI calculator

Victor App: saves one paralegal salary ($60 k / year) → 18‑month payback
Victor Assistant: saves one associate’s document time ($120 k / year) → 15‑month payback
Victor Enterprise: saves entire document‑review team → 6‑month payback

Objection Handlers

“Too expensive” → “What’s the cost of missing key evidence in a $2 M case?”
“We have software already” → “Do you own it or rent it? Does it get smarter every month?”
“Not sure about AI” → “This isn’t experimental — it’s proven legal intelligence in a box”

Closing Line

“Victor Cube isn’t software — it’s your competitive advantage delivered as an appliance. Which level of legal intelligence does your firm need?”

Quick Reference – Future Matrix

Feature	Victor App	Victor Assistant	Victor Enterprise
Document Processing	✅ Core	✅ Advanced	✅ Enterprise
Legal Theory Generation	✅ Basic	✅ Advanced	✅ Configurable
Visual Discovery	❌	✅ Full Suite	✅ Unlimited
Case Management	❌	⚠️ Basic	✅ Complete
Multi‑Industry	❌	❌	✅ Universal
Price Point	$99 k	$179 k	$299 k
Target Market	1–10 lawyers	10–100 lawyers	100 + lawyers

For technical questions, escalate to the architecture team. For pricing negotiations, consult sales leadership.

We don’t just vectorize data — we VICTORize data!

BUSINESS MODEL & MONETIZATION

5.1 Revenue Evolution (6-Phase Roadmap P0–P6)

Monetization Framework for Imperium AI’s Phased Roadmap – Custom On-Premises AI Employees.

Phase P0 – Pilot Success: Trigger: 2 additional on-prem wins. Cash Target: ~$180k gross cash in. Build Goals: Hire 4 core devs, Scale ‘Agentic’ dev cluster. GTM Focus: Targeted ABM, Founder-led sales. Revenue: One-time pilot fees (custom AI builds). High-touch service (incl. basic support).

Phase P1 – Repeatable Model: Trigger: First dev team hired. Cash Target: ~$360k add’l

cash (12 sales). Build Goals: Build ‘AI Builder’ software, Fund 2 more devs, Introduce

consulting offering. GTM Focus: Targeted ABM, (still) Founder-led sales. Revenue: One-

time project sales (~$30k each). Paid consulting (integration & training).

Phase P2 – Platform Complete: Trigger: ‘AI Builder’ platform complete. Cash Target: ~$360k add’l cash (4 sales). Build Goals: Develop on-demand build infrastructure, Refine development process. GTM Focus: Expanded ABM, Outsourced sales help, Paid & viral lead gen. Revenue: Larger deal sizes (value-based ~$90k each). Support contracts (annual maintenance).

Phase P3 – Scale Operations: Trigger: 10 builds complete. Cash Target: ~$680k cash in (8 sales). Build Goals: Refine ‘AI manufacturing’ process, Design hardware prototype concept. GTM Focus: Internal + outsourced sales, Content marketing, Affiliate programs. Revenue: Tiered pricing (by complexity/value). Cross-sell/up-sell to existing clients, Affiliate referral incentives.

Phase P4 – Enterprise Focus: Trigger: Build time down to 2 weeks. Cash Target: ~$3.2M cash in (32 sales). Build Goals: Invest $2M in R&D, Streamline process, Hire 2 support devs + 1 PM. GTM Focus: Internal/outsourced sales, Content marketing, Affiliate programs. Revenue: Subscription/License options. Support packages (dedicated tiers), Bundles of multiple AI solutions.

Phase P5 – Big Deals: Trigger: Build time 1 week. Cash Target: ~$6.4M cash in (64 sales). Build Goals: Add AI applied physics expert, Pursue major energy/enterprise contracts. GTM Focus: Internal/outsourced sales, Content & affiliate programs. Revenue: Enterprise licensing deals (multi-year). Domain-specific pricing (premium), Partnership revenue (channel sales).

Phase P6 – Massive ARR: Trigger: Build time 1 day. Cash Target: ~$36.5M ARR. Build Goals: Self-sustaining data centers, Supply chain R&D, Prep for ‘super-intelligence’ scale. GTM Focus: DOE/DOD contracts, Government-focused GTM. Revenue: Recurring revenue model (subscriptions), Government contracts (large fixed price), Platform licensing for select partners. 80–90% of revenue from subscriptions and support contracts.

5.2 Pricing & Revenue Streams

Revenue Streams: One-time custom AI software sales – Core revenue in early phases. Ongoing ‘reach-back’ support contracts – Building recurring revenue. Consulting services – Integration, training & customization. Evolution to subscription/licensing in later phases. Enterprise licensing deals – multi-year, bulk discounts. Government contracts – Large fixed-price or T&M deals.

5.3 Target Market Evolution

Phase 0-1: Mid-market

Phase 2-4: Enterprise

Phase 5-6: Government (DOE/DOD)

TECHNOLOGY & COMPETITIVE ADVANTAGES

6.1 Technical Differentiators

Custom AI employees on-premises tailored to client’s specific needs. AI trained on internal documents, processes & policies. Runs securely offline on client’s own infrastructure. Zero data leakage – complete privacy and security. Designed for compliance-sensitive industries. 7-Phase Development Roadmap (P0-P6). Evolution from 2-month build time → 1-day build time.

6.2 Industry Focus Areas

Custom AI Employees & Software: Imperium AI is currently working on building an AI operations software and an AI employee for one of the largest Qualified Residential Treatment Providers (QRTP) in Illinois.

AI Operations Software – This software & LLM operates completely offline on a private and local server making it one of the most secure AI platforms on the market. This software ensures that behavioral technicians are filling out shift forms on offline devices based on occurred events or regulated time intervals, it then files these forms to their respective files and stores key data points on client behavior allowing them significantly to improve their services.

AI Legal Assistant – Our AI legal assistant is an on-site LLM/AI agentic infrastructure that acts as a direct assistant to any attorney with the privacy security they need for their clients. This AI employee can assist with discovery, document drafting, interrogatories, and much more. Rather than risking sensitive data with ChatGPT law firms now can have an onsite AI model that is an expert on all their firms’ policies, procedures, best practices, and drafting templates on a portable server.

6.3 Competitive Positioning

MARKET OPPORTUNITY & STRATEGY

7.1 Market Problem

Legal, medical, and accounting firms struggle to integrate advanced AI due to high risks associated with managing sensitive data and the possibility of AI hallucinations. Job market is sticky and has not adapted to a low attention span, AI adapted labor market. Changes in software requires significant onboarding or structural changes within a company making it extremely difficult for medium to large sized companies to adapt to a quickly changing technology environment.

7.2 Sales & Marketing Evolution

Phase P1 – Repeatable Model: Trigger: First dev team hired. Cash Target: ~$360k add’l

cash (12 sales). Build Goals: Build ‘AI Builder’ software, Fund 2 more devs, Introduce

consulting offering. GTM Focus: Targeted ABM, (still) Founder-led sales. Revenue: One-

time project sales (~$30k each). Paid consulting (integration & training).

Phase P4 – Enterprise Focus: Trigger: Build time down to 2 weeks. Cash Target: ~$3.2M cash in (32 sales). Build Goals: Invest $2M in R&D, streamline process, Hire 2 support devs + 1 PM. GTM Focus: Internal/outsourced sales, Content marketing, Affiliate programs. Revenue: Subscription/License options. Support packages (dedicated tiers), Bundles of multiple AI solutions.

GOVERNANCE & ETHICS

8.1 Ethics Framework

Governance & Ethics: Ethics Council – Cross-functional team reviews new products with a Liberty & Hope lens (Privacy impact, Societal consequences, Long-term good). Open Door Policy – Any employee may escalate cultural violations directly to the COO without retribution (Zero tolerance for retaliation). Sustainability Pledge – We tithe 5% of engineering capacity to ‘common-good’ features or open-source fixes annually (Giving back to the ecosystem). We build technologies worthy of our Creator and our country’s calling.

FINANCIAL PROJECTIONS & METRICS

9.1 Key Financial Metrics

Financial Outlook & Evolution:

P0 Pilot (~$90k avg deal, ~8 weeks build, one-time fees, ~0% recurring).

P1 Repeatable (~$30k avg deal, 6–8 weeks build, one-time + consulting, ~0–5% recurring).

P2 Platform (~$90k avg deal, 4–6 weeks build, support contracts starting, ~10% recurring).

P3 Scale (~$85k avg deal, ~4 weeks build, tiered pricing, ~15–20% recurring).

P4 Enterprise (~$100k avg deal, ~2 weeks build, subscription predominant, ~30–50% recurring).

P5 Big Deals (~$100k avg deal, ~1 week build, enterprise multi-year, ~50%+ recurring).

P6 Massive ARR ($100k+ avg deal, ~1 day build, subscription-dominant, ~80–90% recurring).

Ultimate ARR Target: $36.5M by Phase P6.

9.2 Success Indicators

Measurement Dashboard – Tracking our cultural health through key metrics tied to our pillars:

Customer Obsession – Net Promoter Score (NPS) Target: ≥70
Courageous Innovation – % Revenue from products <2 yrs old Target: ≥35%
Liberty & Hope – Privacy-breach incidents Target: 0

OPERATIONAL EXCELLENCE

10.1 Quality Metrics

Craftsmanship – Escaped defects per 1k LOC Target: ↓15% YoY
Relentless Accountability – ‘Own-the-Outcome’ post-mortems closed ≤14 days Target: 100%

3.Servant Leadership – Volunteer hours/employee/year Target: ≥20

10.2 Development Process

Cultural Operating System – The layers that translate our vision into day-to-day operations:

Vision & Strategy: North-Star Narrative memo (3 yrs out) keeps every initiative tied to the frontier we’re extending.
Goals & Metrics: Company → Team → Individual OKRs align work to the pillars; surfaces measurable ‘delight’.
Decision-Making: C.U.T.E. filter (Customer first, Uncompromised quality, Test bold hypothesis, Ethical & liberty-honoring) ensures consistent cultural lens.
Rituals: Monday ‘Customer Story’ stand-up, Bi-weekly Demo & Debrief (wins + failed bets), Quarterly Service Day in local community reinforces obsession, courage, service.
Feedback Loops: Semi-annual 360° ‘Craft & Character’ reviews rate both results and pillar-aligned behaviours.
Recognition: ‘Frontier Tokens’ (peer-given points redeemable for learning budget) rewards living the pillars more than title or tenure.

Courageous Innovation: Advance boldly when the odds are long. Run pre-mortems to surface risks, then move fast. Celebrate well-scoped failed experiments in Demo Day. Antipattern: Analysis paralysis; waiting for 100% certainty.

FUTURE VISION & ROADMAP

11.1 Long-term Vision

While Hebron remains focused on AI infrastructure, his long-term vision is broader: to create tools that enable self-reliance for small businesses and individuals alike. Whether through bespoke software, decentralized computing, or educational reform, his mission centers on sovereignty, not scale.

In five years, Hebron envisions thousands of small and mid-sized businesses deploying their own private LLMs and agentic systems. Personally, he imagines a ranch powered by solar and hydro microgrids, where he can mentor his son while prototyping new energy systems.