Capabilities
AI Automation & Systems Architecture
I work across the operating and technical layers behind a growing company: process architecture, AI, automation, APIs, cloud, data, dashboards, CRM, and internal tools. Engagements are async-first by default.
Service 01
AI & Agentic Systems
I design AI-assisted systems that sit inside real operations: summarization, classification, research, enrichment, drafting, routing, review queues, and human approval where judgment still matters.
Signals this needs attention
- Your team spends hours interpreting repetitive information.
- AI experiments exist but are disconnected from the actual workflow.
- You need traceability and human review, not just a chatbot.
What I deliver
- AI workflow architecture and prompt/model design
- Human-in-the-loop checkpoints and review queues
- Integration into existing operational systems
- Logging, evaluation notes, and documented failure handling
Service 02
Workflow Automation & Orchestration
I automate repeatable handoffs across tools while accounting for bad inputs, duplicate events, timing, retries, and the fact that production workflows do not behave like demos.
Signals this needs attention
- People copy the same data between systems every day.
- Handoffs depend on memory or Slack messages.
- Existing automations fail silently or are hard to maintain.
What I deliver
- Multi-step workflow orchestration
- Validation, retries, alerts, and run logs
- Google Workspace automation and custom scripts
- Workflow maps and operational runbooks
Service 03
Cloud & Technical Systems
I help choose and connect the infrastructure behind internal applications and automations — deployment, managed services, edge/networking, serverless functions, data services, and AI infrastructure.
Signals this needs attention
- Your internal tool needs somewhere reliable to run.
- Your systems span multiple hosting and cloud providers.
- You need clearer deployment, DNS, edge, or serverless architecture.
What I deliver
- Practical cloud architecture for the workload
- Deployment and environment structure
- DNS/edge and service connectivity
- Architecture notes for future maintainers
Service 04
API & Integration Engineering
When native integrations are not enough, I connect systems directly using APIs and webhooks with the reliability controls needed for real business data.
Signals this needs attention
- Two tools hold the same data and people reconcile them manually.
- A native integration is missing or too limited.
- You are dealing with rate limits, auth, dropped records, or endpoint failures.
Service 05
CRM & Operational Data Architecture
Before automating a CRM, I make sure the data model, stages, fields, ownership, and reporting logic are trustworthy enough to automate.
Signals this needs attention
- Pipeline stages mean different things to different people.
- Duplicates or free-text fields make reporting unreliable.
- The real process has moved into side spreadsheets.
What I deliver
- Field and stage standardization
- Data cleanup and hygiene rules
- Automation-ready workflow design
- Documented definitions and operating rules
Service 06
Operations Dashboards & Reporting
I build operational views around decisions and exceptions — not just charts — so teams can see what needs attention without rebuilding a report every week.
Signals this needs attention
- Reporting requires repeated exports and manual consolidation.
- Important exceptions surface late.
- Different teams produce different answers for the same metric.
What I deliver
- Operational dashboards and exception views
- Automated refresh/data pipelines
- Metric definitions and source mapping
- Views designed around action and ownership
Service 07
Internal Tools & Admin Systems
When spreadsheets and off-the-shelf tools have run out of road, I build focused internal applications around the workflow the team actually needs.
Signals this needs attention
- The spreadsheet has become the application.
- You need permissions, validation, or multiple operational views.
- Off-the-shelf software almost fits but creates more workarounds.
What I deliver
- Internal dashboards and admin interfaces
- Structured database-backed workflows
- Role/access-aware application patterns
- Deployment and documented handover
Service 08
Systems Audit & Technical Direction
For teams that know something is wrong but do not yet know what should be rebuilt, automated, integrated, or left alone, I map the operating layer and turn it into a prioritized technical plan.
Signals this needs attention
- The stack grew organically and ownership is unclear.
- You have overlapping tools and disconnected automations.
- A founder or operations lead needs technical direction without a full-time CTO.
What I deliver
- Workflow and system map
- Risks, failure points, and dependency review
- Prioritized architecture/build roadmap
- Written technical recommendations and tradeoffs
Ways to work
Choose the level of technical ownership you need
Every model is async-first and documentation-heavy. Meetings are used when they improve a technical decision, not as the default operating model.
FAQ
Common questions
Useful context before you send a systems brief.
Which technologies do you work across?
My work spans Make, n8n, Zapier, Google Apps Script, OpenAI, Claude, AWS Bedrock, Google Cloud Platform, AWS, Cloudflare, Vercel, Render, Supabase, PostgreSQL, Next.js, React, TypeScript, REST APIs, webhooks, CRM platforms, Google Workspace, and operational/marketing systems. The architecture determines the tool, not the other way around.
Do we need to book a discovery call?
No. The default starting point is an async systems brief. Send the current workflow, tools, constraints, and outcome you need. I review it and reply with focused questions or a recommended next step. A meeting is only suggested when a synchronous technical discussion would genuinely be more efficient.
How do you work asynchronously?
Written specifications, architecture diagrams, workflow maps, Loom walkthroughs, GitHub/project documentation, and structured progress updates are the primary source of alignment. Important technical decisions are written down so context is not trapped inside calls.
Why are the case studies anonymized?
Most projects touch private business systems, CRM data, workflows, billing logic, or internal operations. I anonymize organizations and use recreated visuals or sample data while preserving the real technical problem and approach.
Can you operate beyond no-code automation?
Yes. I use no-code orchestration when it is the right layer, but I also work with custom scripts, APIs, databases, Next.js applications, Supabase/PostgreSQL, cloud infrastructure, serverless services, deployment platforms, and edge/network tooling when the system needs it.
Not sure what needs rebuilding? Start with the system, not the tool.
Send the workflow and what is currently painful. I'll review it asynchronously and help identify whether the answer is automation, architecture, data cleanup, an integration, an internal tool — or simply fixing the process first.