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Clear leverage for your business.

Turn messy work into clear business leverage.

Dispella identifies where AI can increase revenue, productivity, or competitive advantage. I then design, build, and put the system into operation — without a strategy-to-developer handoff, and with the finished asset owned by you.

Book a 30-minute workflow fit callSee working systems

Valuable work gets lost in the gaps.

Before choosing technology, the first job is to locate the work, decisions, and context that are creating drag.

  1. Your team loses hours to research, reporting, and repeat decisions.

  2. Important context is scattered across inboxes, folders, tools, and people.

  3. AI experiments are easy. Reliable systems in real operation are not.

Diagnose first. Build what earns its place.

One accountable path from a frustrating workflow to a validated, governed system in real use.

  1. Fit

    Bring one costly or frustrating workflow. Determine whether AI can create enough leverage to justify a Sprint.

  2. Sprint

    Map the workflow, measure what is available, test a working prototype, and define the production recommendation.

  3. Build

    Build, deploy, evaluate, document, and roll out the validated system.

After the build

Expand into more roles and workflows, or keep the system maintained. You never pay merely to retain access to what you own.

Accountability is part of the architecture.

The delivery model, ownership model, and permission model are designed together—not added after the system works.

One person, both halves.

The person who diagnoses the workflow is the person who builds the system. Nothing is lost in a strategy-to-developer handoff.

You own the asset.

You receive a version-controlled repository containing the system logic, rules, workflows, evaluations, integration code, configuration, and documentation. Sensitive data, private records, credentials, and operational knowledge sources remain inside systems you control.

Governed by design.

Every system defines what AI may read, draft, or propose; what a human must approve; what remains prohibited; where important answers came from; and how actions are verified.

A proposal is not permission.

Every system separates what the AI can understand from what it is authorized to do, then verifies the result.

Governed AI control loopSense, reason, and gate occur before a proposal reaches explicit human approval; an approved action is then verified.PERMISSION GATE01SENSE02REASON03GATE04PROPOSE05APPROVEHUMAN AUTHORITY06VERIFYprovenance returns to the next sensing cycle
  1. sense
  2. reason
  3. gatepermission boundary
  4. propose
  5. approvehuman authority
  6. verify

The model is never the permission system.

A visible gate separates analysis from action. Important proposals wait for human authority, then the result is checked and returned to the record.

Built across research, content, and governed decisions.

Different workflows. The same discipline: explicit sources, human boundaries, and systems shaped around the work.

View all five systems

Client system — in operation.

PR Media Intelligence

A media-intelligence pipeline for a PR agency. It monitors news and social sources, deduplicates material, runs AI sentiment and framing analysis with an audit trail, and produces recurring source-linked reports in the client’s language.

Read the system record

Internal operating system — in operation.

NOMI Content Operations

A multi-role AI content operation for an e-commerce brand the founder co-owns. One topic moves through research, writing, translation in two languages, design, review, and publishing.

Read the system record

Open-source R&D — public methodology for governed AI systems.

StrideOS

An MIT-licensed endurance-coaching plugin with six routed skills, evidence provenance, explicit permissions, approval gates, a full test suite, and the control loop: sense → reason → gate → propose → approve → verify.

Read the system record

07 / Ownership promise

The system remains yours when the model changes — or when our work together ends.

The system I build lives in your repository. Sensitive data stays in systems you control. The business logic is designed to be model-portable, so provider changes do not force a rebuild from zero. You keep using what you paid for whether or not we continue working together. Ongoing work is for improvement and expansion — not access.

  • 01System logic and rulesversion controlled
  • 02Workflows and evaluationsdocumented
  • 03Integration code and configurationtransferred
  • 04Sensitive data and credentialsclient controlled
  • 05Provider changeadapt and retest

Bring your most frustrating workflow.

Thirty minutes. Leave with a clearer view of where AI can create leverage — and whether a Sprint is the right next step.

Book a 30-minute workflow fit call