AI & business automation · consulting · secure implementation

Make your business work smarter.

Helping businesses identify inefficient processes, design practical AI and non-AI automations, and implement solutions with security in mind. From the first conversation to a working solution, the focus is on meaningful business results.

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Messy documents flowing through AI into clean structured data

How I can help

Start with the business problem. Build the right solution.

Not every problem needs AI. The first step is understanding the process with your team, identifying where time and effort are being lost, and choosing an approach that fits your tools, people, and requirements.

AI & Business Automation

Identify repetitive or inefficient workflows, then design and build custom automations that reduce manual work and improve consistency.

Secure AI Implementation

Evaluate AI use cases, tools, data exposure, and access requirements. Build security, privacy, and appropriate human review into implementation.

AI Consulting & Training

Help your organization choose useful tools, find practical use cases, set responsible-use guidelines, and train employees around their real work.

Measured impact

Automation that delivers measurable results.

These results come from automation tools independently designed and built for real business workflows.

70%+Reduction in manual hours.

2 weeks → 1 hourMatching records across large datasets, with over 95% acceptance on expert review.

Results reflect specific workflows and are not a guarantee of outcomes for other projects.

Examples of the work

Different industries. The same approach.

The examples below show the approach to data-heavy operations, compliance workflows, and responsible AI adoption.

Medical billing automation

Standardize billing information arriving in different formats.

GRC automation case studies

Control mapping, questionnaire generation, and risk recommendations.

Secure AI adoption

Practical steps for using AI while managing business and data risks.

AI training for teams

Role-specific training that connects AI to everyday work.

Explore practical automation examples

Choose an industry to highlight relevant examples. The underlying approach can be adapted to other teams and workflows.

Have a process that takes too much time?

Explore a sample medical billing workflow to see how information from different formats can be standardized. The demonstration uses illustrative sample data.

View the billing example

Questions, answered

What AI can do for a data-heavy team, and how working together goes.

Tools used

ExcelPower QueryPythonOpenAI & ClaudeRAGAWS BedrockAPIs

Start a conversation

Have a process you’d like to improve?

Share what’s taking up your team’s time, where work gets stuck, or what you’d like to do differently. You don’t need to know whether AI is the answer.

← All automations

Medical billing

Every bill arrives in a different format. Your file should not.

Billing information can arrive as faxes, spreadsheets, PDFs, emails, and handwritten notes. This illustrative demo shows how information from different formats can be extracted and organized into a consistent structure.

The five bills

Sample data, made up for this demo.

See the workflow

The timings and sample records below are illustrative, not a measured benchmark. In a real implementation, extraction quality and review rules would be tested against your own documents.

By handReady

With AIReady

Have billing data arriving in different formats?

Map the process, identify the exceptions, and assess whether extraction and standardization can reduce manual entry.

Discuss a billing workflow

GRC automation

AI that does the slow parts of compliance work.

These case studies come from hands-on AI automation work inside a cybersecurity GRC software company. High-effort analyst workflows were identified, then Python- and LLM-powered tools were independently designed, built, and maintained to improve speed, consistency, and scale. The work included retrieval, similarity and confidence scoring, structured generation, and production implementation.

2 weeks → 1 hourControl mapping

70%+Fewer manual hours

The examples describe work completed as part of a commercial GRC platform. Details are presented at a high level and do not disclose proprietary implementation information.

Have a slow, rules-heavy process?

Describe it in an email to find out what could be automated and how to do it securely.

Send an email

Security & AI

Adopt AI without compromising security.

AI adoption creates new opportunities and new risks. Helping businesses assess how AI fits into their operations, choose appropriate tools, and build practical safeguards around data, access, vendors, and human oversight.

Discuss secure AI adoption

A shield protected by a network of AI nodes

How I can help

Risks to consider when adopting AI

What companies should do

Set clear rules and know your tools
Publish a short AI acceptable-use policy. Keep an inventory of approved tools, and give people a good approved option so they don’t go looking for one.
Decide what data may go where
Classify data, and say plainly which kinds may never go into which tools. Remove names, numbers, and secrets before using AI whenever possible.
Vet vendors before you rely on them
Ask about data retention, whether your data trains their models, where it is stored, and what contract protections exist.
Limit access, keep a human in the loop, and keep logs
Give AI tools the least access they need. Have a person review anything important. Log usage so you can investigate when something goes wrong.
Train your people
Rules only work if people understand them. Short, practical, regular training does more than a policy nobody reads. See the training.

Use the frameworks that already exist. NIST AI Risk Management Framework, ISO/IEC 42001 (AI management systems), and the OWASP Top 10 for LLM Applications are well-known starting points.

Compliance doesn’t pause for AI

The rules you already follow still apply when the data goes into an AI tool.

HIPAA (health information, US)

Protected health information needs safeguards wherever it goes. A vendor that handles it generally needs a business associate agreement, and access should follow the minimum-necessary idea. Pasting patient notes into a consumer chatbot is a classic way to get this wrong.

GDPR (personal data, EU/UK)

Principles such as data minimization, purpose limits, and rules on transferring data abroad apply to AI use. High-risk processing may need a data protection impact assessment, and there are rules on decisions made purely by automated means.

ISO 27001 (information security)

Covers how you manage security risks, including suppliers. AI vendors belong in that supplier and risk process like any other.

EU AI Act and others

New AI-specific laws are arriving with risk-based obligations. Which ones apply depends on where you operate and what the AI is used for.

General information only, not legal advice. Ask your legal counsel about your own obligations.

Planning to introduce AI into your business?

Review the use case, the data involved, and the safeguards needed to make adoption practical and responsible.

Discuss secure AI adoption

AI employee training

Help your team use AI confidently and safely.

Practical, role-specific training that helps employees recognize useful AI opportunities, work more effectively with approved tools, and understand how to protect business information.

Three people learning with laptops and AI chat bubbles

Training built around the way your team works

Find useful use cases

Identify tasks in each role where AI can save time or improve the quality of work.

Work effectively with AI

Practice prompting, refining outputs, and using approved tools for real tasks.

Verify AI outputs

Recognize confident mistakes, check sources, and know when human judgment is needed.

Protect business information

Understand what data can be shared, which tools are approved, and how to avoid common risks.

Sessions can be tailored to your industry, roles, existing tools, and internal AI-use guidelines.

Try a taste

A sample of the kind of game used in the training.

Build AI capability across your team.

Share your organization, the roles you want to train, and the tools your employees use.

Discuss team training

About

Turning complex work into smarter ways of working.

I start by understanding the business.

Good automation starts with understanding the problem, not choosing a tool.

My background is in cybersecurity consulting, GRC, and business operations. I’ve worked directly with business owners, executives, and technical teams to understand how their organizations operate, identify risks and inefficiencies, and turn complex requirements into practical solutions.

I’ve helped approximately 15–20 organizations build and improve their security programs, working across ISO 27001, HIPAA, GDPR, SOC 2, and more than 50 frameworks and regulations.

That experience taught me something important: every business has its own processes, challenges, and priorities. Solutions need to fit the organization, not the other way around.

From identifying problems to building solutions.

At a cybersecurity GRC startup, I moved beyond using existing tools and began building automation from the ground up.

I identified time-consuming workflows, designed solutions, and independently developed Python- and LLM-powered tools to make complex work faster and more scalable. The results included:

Control mapping: Reduced a process that took approximately two weeks to about one hour, with over 95% acceptance on expert review.
Questionnaire creation: Reduced turnaround from 2–4 weeks to 1–3 days, generating nearly 50 regulatory questionnaires.
Operational efficiency: Reduced manual analyst hours by over 70%.
Production implementation: Built a risk-to-control recommendation tool that became part of the company’s commercial GRC platform.

These weren’t just experiments or demonstrations. They were tools designed around real workflows and used to deliver measurable results.

Explore my automation projects

Technology is only part of the solution.

I work across AI-powered automation, Python development, APIs, LLMs, and other technologies, but the technology itself is never the starting point.

I want to understand what your team is doing today, where time and resources are being lost, what needs to improve, and what a successful solution would actually look like.

Sometimes that means building an AI-powered workflow. Sometimes it’s a simpler automation that doesn’t need AI at all. And sometimes the biggest opportunity is improving an existing process before automating it.

My cybersecurity and GRC background also means I approach implementation with security, privacy, reliability, and compliance in mind from the beginning.

Working together.

I bring a combination of business understanding, technical implementation, and security expertise. I can work with you to:

Identify opportunities to automate repetitive or inefficient processes.
Design and build custom AI and non-AI automation solutions.
Integrate tools and systems into your existing workflows.
Help your team understand and adopt AI effectively.
Evaluate solutions with security, privacy, and business requirements in mind.

I’m particularly interested in working with businesses that want to make practical use of automation but need someone who can bridge the gap between understanding the business problem and actually building the solution.

I enjoy figuring out how things work, finding a better way to do them, and turning that idea into something useful. That’s the work I want to do.

Tell me about your team’s workflow

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