Systems thinking
Mapping how people, data and tools interact before building anything, from a trading workflow to a back-office process.
Evidence: the Neshamah ecosystem →Personal Innovation & Business Ecosystem
I explore how technology, data and disciplined thinking can help people and businesses work better. Neshamah connects my projects in automation, business operations, research and personal development.
“I learn by building: understand the problem, test it with real data, and keep only what works.”
More about Neshamah →Capabilities
No titles or credentials beyond what the projects show. Every strength links to the work behind it.
Mapping how people, data and tools interact before building anything, from a trading workflow to a back-office process.
Evidence: the Neshamah ecosystem →n8n workflows, AI-assisted pipelines and multi-agent operations with human review at each gate.
Evidence: Neshamah Systems →Turning recurring manual work into scoped, testable automation with explicit economics.
Evidence: market research →Market data, training data and documented research with sources, dates and limitations.
Evidence: Trading Workspace →Shipping working web tools quickly, then hardening what proves useful.
Evidence: Runner Intelligence →Hypothesis, test, measure, decide. Applied to products, markets and personal training alike.
Evidence: project registry →Selected projects
Every card states what exists today, what is still being built, and the limits of the project.
A research workspace for trading workflows: journaling, review and risk analytics. Educational research, not investment advice.
Training progress tracking and running research. No health or performance promises, and no personal metrics shown without consent.
Automation for small businesses: workflow audits, lead-to-CRM and PDF purchase order to ERP CSV. Desk research is complete and a synthetic demo has been specified. No client results yet.
The ecosystem
Three directions have working projects today. The other three are planned and will only launch after real demand and evidence.
Business automation, document workflows and AI-assisted operations.
Trading research workspace, journaling and risk tooling. Not investment advice.
Training intelligence and running research.
Evidence-based product research and comparisons.
Scoped consulting on systems and operations.
Guides and courses built from real project experience.
How I work
AI agents speed up the work, and a person reviews and approves every important step.
Who has the problem, how often, and what it costs.
Dated sources and alternatives. Unknowns are written down.
Scope, data flow, privacy and acceptance tests first.
Small increments on synthetic or consented data.
Automated checks plus human review before release.
Measure, keep what works, retire what does not.
Research & solutions
Three proposed solution families from published desk research. These are pilots in preparation, not finished products.
Map a recurring workflow, estimate the economics, then build one scoped n8n automation.
Consent-checked intake, deduplication and routing into an existing CRM.
Validated line items, SKU and total checks, and an exception review before export.
Collaboration
Small teams, operators and builders. Tell me about the problem and I will reply with an honest view of whether it is worth automating.