Garo Vartabedian

Work with Garo

Practical help for messy workflows and company knowledge.

Independent technical help for operations and knowledge-heavy teams. Start with a bounded diagnostic — whether untangling a manual operations workflow or structuring trapped corporate files into verified dossiers for Google NotebookLM™ and internal LLMs.

Discuss a projectKnowledge Pipeline One-Pager (PDF)Inspect the work

Track 1: Workflow & Automation Audit — $500 fixed

One working week, one bounded workflow, one practical report. The price and scope are posted upfront. You begin with a bounded diagnostic instead of an open-ended consulting commitment.

Good fit for the audit

  • Manual handoffsCustomer or operations work is copied between forms, inboxes, spreadsheets, and internal tools.
  • Recurring tool workA report, intake process, or status update requires the same browser and data steps every week.
  • Unclear automation choiceThe team knows a workflow is wasteful but not whether the answer is an integration, a small tool, AI, or a simpler process.
  • Human judgment still mattersThe useful parts should be automated without hiding the decision, approval, or exception that belongs to a person.
  • Knowledge trapped in messy filesSOPs, manuals, or historical records are scattered across drives, and off-the-shelf AI hallucinates without clean, structured source dossiers.

What you get from the audit

  • Current workflow mapOne view of the people, tools, inputs, decisions, and handoffs visible in the supplied materials.
  • Friction and risk diagnosisWhere time, context, or trust is being lost — including obvious access and data-exposure concerns, without pretending this is a formal security audit.
  • Three prioritized changesThree candidate improvements ranked by likely impact, effort, and risk based on the supplied evidence, including a no-build option when process cleanup is enough.
  • First-pilot briefA bounded recommendation for the first useful change: outcome, inputs, exclusions, acceptance check, and what implementation would require.
  • Review call and reportA 45-minute call to pressure-test the recommendation, plus the complete report to keep whether or not we work together again.

Track 2: Enterprise Knowledge & Dossier Pipeline

Turn messy corporate files into high-density, verified source dossiers engineered for Google NotebookLM™ and internal LLMs.

Teams want to use generative AI and NotebookLM to synthesize internal knowledge, but raw corporate files are messy: scanned PDFs, fragmented SOPs, contradictory spreadsheets, and disjointed manuals. Off-the-shelf tools hallucinate, drop critical nuance, and lose source context when fed uncurated files.

I build pipelines to prepare and check source material: cleaning OCR errors, extracting complex tables, structuring modules with YAML frontmatter, and embedding paragraph-level citation anchors throughout. The output is an inspectable Markdown dossier library with extraction checks, source links, and evaluation questions for use with NotebookLM or private RAG.

  • Sanitized Markdown corpusOCR cleanup, formatted complex tables, noise removal, and deduplication across scattered corporate PDFs, docs, and sheets.
  • Structured YAML metadataConsistent schema tagging (dates, authors, versions, access boundaries, topic classification) on every dossier module.
  • Source-linked provenanceParagraph-level citation anchors connect dossier passages to supplied records so reviewers can check the source of a claim.
  • Target-optimized synthesisDossiers formatted for Google NotebookLM™, Claude Projects, or private RAG, with source notes and questions for evaluating answers against the supplied material.

Try the live Dossier EngineDownload Executive Brief (PDF)

If a build makes sense

The report is useful on its own. If the first change is bounded enough, we can scope a separate working pilot with its outcome, timeline, price, and limits written down before implementation begins. If the right answer is a spreadsheet, a process change, or software you already own, I will say that instead.

  • Working pilotBuild one narrow automation, integration, or internal tool and test it against an agreed outcome.
  • Knowledge and dossier pipelineClean, structure, and index proprietary documents into high-density source dossiers ready for Google NotebookLM, Claude Projects, or internal search.
  • Production implementationExtend a proven pilot into a documented workflow with the failure paths and operating handoff included.
  • Fractional technical partnerOwn a small backlog of workflow and integration improvements without requiring a full-time hire.

Why work with me

I did field service on live customer sites, where the system had to work and the handoff had to make sense to the people operating it. Now I build full-stack applications, browser automation, API integrations, grounded data pipelines, and human-in-the-loop workflows in Python and TypeScript. The case studies are public, and they name what is shipped, what is local, and what is not being claimed.

Workflow audit boundaries

  • BoundaryOne recurring workflow across up to five tools, plus the people and handoff steps around them.
  • BoundaryInputs are one walkthrough of up to 60 minutes plus the screenshots or documents agreed during scoping.
  • BoundaryThe delivery clock starts after those materials arrive; production credentials and direct system access are outside the audit.
  • BoundaryThe audit diagnoses and scopes; it does not include production implementation.
  • BoundaryIt is not a compliance review, penetration test, or legal opinion.
  • BoundaryNo automation is recommended merely because it uses AI.

Knowledge pipeline boundaries

  • BoundarySource files provided as static exports (PDFs, Markdown, docs, spreadsheets). Direct production database write-access is outside scope.
  • BoundaryOutputs are delivered as inspectable Markdown dossiers, structured manifests, and local ingestion scripts.
  • BoundaryDeliverables verify source alignment and data extraction; they do not constitute legal, medical, or regulatory compliance opinions.
  • BoundarySource preparation supports review; it cannot guarantee that an AI answer or Audio Deep Dive is accurate. Generated outputs still need source checks.
  • BoundaryOptimized for Google NotebookLM™ and enterprise LLMs under nominative fair use; no official affiliation or endorsement by Google is implied.

Tell me what is slowing the team down

Two plain sentences are enough: what the workflow is, who touches it, and where it gets stuck. I will reply with whether this audit fits before asking you to commit to anything.

Discuss a project

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