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MIT xPRO Certificate in AI Strategy & Google Cloud Certified

Turn missed calls, manual follow-up, and repetitive admin work into secure AI-powered workflows—without building an internal AI team.

We translate enterprise AI discipline into a phased execution model for owner-led and growth-stage teams. Every engagement is scoped around operational outcomes, security controls, and a delivery rhythm your business can sustain.

Executive proof signals

  • Average implementation cycle: 14 days to first deployment milestone
  • Advisory + execution model aligned to security and governance controls
  • Operating playbooks designed for internal adoption, not vendor lock-in

Operational Proof Ledger

SYS.UPDT: v1.2.0.15 (2026-09-10)

Efficiency Potential

30%+

Targeted support & data entry savings

Security posture

Pass

Control & configuration review

Typical delivery

14d

Strategy to implementation

Engagement model

Advisory + Build

Executive advisory paired with technical execution

Capability Architecture

A curated operating model that blends advisory depth with implementation speed.

Level 1 · Strategic Core

Strategic AI Security and Execution

We establish the operating thesis, identify high-value workflow candidates, and sequence implementation around control requirements and adoption risk.

Primary outcome

Prioritized ROI roadmap

Governance baseline

Security-first rollout controls

Level 2 · Build Track

Custom AI Automation

Deploy workflow automation, internal copilots, and applied integration patterns mapped to your existing systems and team capacity.

Level 3 · Operating Advisory

Executive Technical Advisory

Guide tool decisions, vendor selection, capability budgeting, and phased implementation governance for sustainable scale.

Transparent Investment

Productized Service Tiers

Predictable pricing, zero hidden fees, and clear deliverables designed for growth-stage businesses.

Explore all advisory tiers & full options — more... →

Self-Service & Strategic Advisory Offerings

Diagnostic Stage

Self-Service AI Opportunity Audit

Rapid automated architectural evaluation, readiness score, and prioritized workflow ROI roadmap.

$0 / FREE! Previously $199; now free.
Free scored assessment
  • Complete a scored AI readiness assessment
  • Receive a readiness score and tailored next steps
  • View estimated time-savings potential
Strategic Advisory

Strategic AI Roadmap

Guided consulting blueprint, vendor selection, risk posture audit, and 60-day action plan.

$1,499 Focused strategic roadmap
  • Audit your business-critical operational workflows
  • Security & compliance review
  • Priority implementation roadmap
Book Strategic AI Roadmap →

Implementation & Operating Retainers

Diagnostic Stage

AI Opportunity Assessment

Comprehensive architectural audit, viability matrix, and prioritized ROI roadmap.

Custom scope & pricing Tell us what you need. We’ll share a clear, tailored price.
  • 1-3 day diagnostic turnaround
  • Security & compliance posture evaluation
  • Top 3 automation sprint candidates
  • Executive implementation blueprint
Request Custom Pricing →
Most Popular
Implementation Stage

AI Automation Sprint

Full production deployment of scoped workflow automation pipelines and system integrations.

Custom scope & pricing Tell us what you need. We’ll share a clear, tailored price.
  • Production-ready code & integrations
  • 2-4 week deployment delivery
  • Full IP ownership & documentation
  • 30 days post-deployment support
Discuss a Custom Build →
Continuous Operating Retainer

MAGO Partner Tier

Continuous algorithmic validation, model monitoring, security patching, and prompt drift auditing.

Custom scope & pricing Tell us what you need. We’ll share a clear, tailored price.
  • Continuous prompt drift & model monitoring
  • Zero-data-retention & security patch audits
  • Quarterly capability enhancements
  • Priority 24/7 engineering SLA
Discuss Custom Support →

Practical Starting Points

Popular Small Business AI Projects in Industry

Explore common project themes for service businesses. Choose a category to see relevant starting points, then validate fit, data, and safeguards before implementation.

Initial themes are based on recurring small-business AI use cases in public guidance and are not a ranking or a promise of results. Sources:

Why Allen AI

Enterprise operating discipline translated for growth-stage businesses with practical timelines and measurable outcomes.

Verify Brad Allen on LinkedIn →

Leadership pedigree

25+ years operating at enterprise scale

Experience leading technology programs across high-accountability organizations including Raytheon, Verizon, AT&T, and Hyundai.

Proof of impact

Focusing on high-value potential efficiency outcomes

Engagements are scoped around targeting and unlocking operational value first, then translated into delivery milestones and adoption plans.

Zero-Risk Data Commitment

Enterprise Data Privacy & Security Promise

Concrete technical safeguards designed to ensure your proprietary business data never leaks, never trains public AI models, and remains 100% your intellectual property.

01

Zero Model Training Guarantee

Your customer interactions, internal SOPs, and financial data are isolated. Formal Zero-Data-Retention (ZDR) agreements ensure public AI models never train on your inputs.

02

Isolated Tenant & VPC Options

Deploy within private Virtual Private Clouds (AWS/Azure VPC) or isolated on-premise LLM runtimes for maximum perimeter boundary protection.

03

Encryption & Access Control

Full AES-256 data encryption at rest and TLS 1.3 in transit. Enforced Role-Based Access Control (RBAC) and immutable audit trail logging.

04

Algorithmic Governance

Continuous prompt drift auditing, hallucination prevention guardrails, and automated vulnerability patching integrated into every deployment.

Verified Security Posture: SecurityHeaders A+ Grade

Thought Leadership

AI Executive Insights & Practical Notes

View Archive →
Security Architecture FEATURED

Zero-Data-Retention Safeguards for Small Business GenAI

How small-to-midsize businesses can utilize enterprise foundation models without compromising customer PII or proprietary IP.

Explore Insights →
Operational ROI FEATURED

Measuring Real Ticket Deflection & Support ROI

Moving beyond chatbot hype: A step-by-step framework for calculating net hours saved across 90-day support ticket cycles.

Explore Insights →
Infrastructure FEATURED

Selecting Private vs. Hosted Models for Operations

Evaluating latency, cost per 1M tokens, and data privacy trade-offs between open-weights local LLMs and API endpoints.

Explore Insights →

How I Approach These Problems

Illustrative scenarios based on real methodology - not client work (yet). Here's exactly how I'd tackle four common situations.

Illustrative customer support analytics and ticket deflection dashboard artifact

Illustrative scenario · Architecture Artifact

Scenario: A logistics operation drowning in repetitive support tickets

A mid-size operations team is spending 15+ hours a week answering the same 20 questions - order status, scheduling changes, and basic troubleshooting. Here's the build sequence I'd run:

  1. Audit the last 90 days of tickets to identify the highest-volume, lowest-complexity categories.
  2. Deploy a scoped chatbot trained only on those categories, with a hard handoff to a human for anything else.
  3. Instrument from day one so ticket deflection is measurable, not assumed.

What this typically targets:

Meaningful reduction in first-response time and support labor hours on repetitive tickets. The exact number depends on ticket mix, which is why step one is a measurement step, not a guess.

Illustrative 24/7 AI voice receptionist telephony routing and scheduling workflow blueprint

Illustrative scenario · Workflow Blueprint

Scenario: A small medical billing office missing after-hours calls

A lean office team is losing inbound opportunities because calls roll to voicemail after hours. Here's the build sequence I'd run:

  1. Review call logs to map peak miss windows, call intent, and existing booking workflow constraints.
  2. Deploy a scoped voice receptionist for appointment requests, billing FAQs, and routing, with immediate escalation for complex cases.
  3. Integrate with scheduling and CRM systems, then track call capture, booking completion, and handoff quality.

What this typically targets:

Higher answered-call coverage after hours and faster appointment intake without adding overnight staffing overhead.

Illustrative AI security and governance audit scorecard artifact

Illustrative scenario · Audit Scorecard

Scenario: A growing SaaS company that has never had a third-party review

The product is shipping quickly, but security controls have grown organically. Here's the build sequence I'd run:

  1. Inventory systems, integrations, and AI-assisted workflows to establish scope and threat surfaces.
  2. Review authentication flows, secrets handling, access controls, and deployment configuration for practical vulnerabilities.
  3. Deliver a severity-ranked remediation plan with implementation guidance and retest criteria.

What this typically targets:

Lower exploitable risk exposure, clearer ownership of control gaps, and a prioritized path to stronger security posture.

Illustrative private LLM isolated VPC architecture diagram artifact

Illustrative scenario · Infrastructure Blueprint

Scenario: A firm that can't send client data to a public API

The team wants AI-enabled search and drafting, but policy and contract obligations require tighter data boundaries. Here's the build sequence I'd run:

  1. Map data classification requirements, retention policies, and approved hosting boundaries.
  2. Stand up a private model and retrieval architecture with network isolation, role-based access, and audit logging.
  3. Run structured evaluations for response quality, latency, and failure cases before broad rollout.

What this typically targets:

Safe adoption of AI workflows for sensitive documents while keeping control over data handling and compliance boundaries.

Enterprise Leadership Track Record

What Enterprise Colleagues Say About Brad

Endorsements from engineering leaders, directors, and partners across enterprise technology organizations.

Founding Client Program

Transparent early-stage offer for teams that want direct founder involvement.

Brad Allen portrait

Founder & Principal AI Architect

Brad Allen

MIT xPRO AI Strategy Certified • 25+ Yrs Enterprise Tech

"I built Allen AI Solutions on 25+ years of enterprise operating experience - most recently at Hyundai Capital America - because I kept seeing the same gap: companies either overpay for generic AI consulting, or underbuild it themselves and create new risk. I'm taking on a small number of founding clients right now, and I'm upfront that you'd be among my first engagements under this name. What you get in exchange is my full attention, founder-level pricing, and a methodology built on real enterprise practice - not a junior team learning on your dime."

Founding Client Program · 3 spots this quarter

I'm opening a limited number of founding-client engagements at founding-client pricing. In exchange, I ask for an honest case study and testimonial once we've delivered results - the kind of proof I can't publish yet because it doesn't exist. If you want to work with someone personally invested in getting your first engagement right, this is the moment to do it.

Reserve a Founding Client Spot →

Routes to the direct consultation form.

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Clear Answers

Frequently Asked Questions

Everything you need to know about our security protocols, engagement timeline, expected investment, and operational deliverables.

Ready to book a Free AI Opportunity Call?

Let's map your operational gaps, prioritize automation opportunities, and outline a secure, practical roadmap for your team.

Length

30 minutes. High-density, engineering-focused session.

Agenda

  • Identify bottlenecks & redundant processes
  • Pre-screen for automation viability & technical feasibility
  • Draft a phase-one implementation outline

Expectations

No sales pitch. Zero obligation. You'll speak directly with Brad to review real technical viability, not marketing promises.

Direct Calendar Access

Prefer to select a time directly?

Skip the back-and-forth email exchange. Pick a confirmed 30-minute discovery slot on Brad's calendar instantly.

Schedule Directly on Cal.com

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