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Léonard Sellem
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Reporting & data infrastructure

Clean pipelines, trustworthy numbers, dashboards that replace the monthly Excel rebuild. The reporting you keep promising to fix, finally fixed.

The reporting every operator keeps promising to fix. I build the pipelines, the warehouse layer, and the dashboards your team opens daily — the ones that don’t end up in a monthly deck.

What this looks like

Who this is for

Mid-market operators who have outgrown spreadsheet reporting, already own a data stack (even a partial one), and need a reporting layer that survives the next personnel change.


What you get

Autonomous workflow agents

The repetitive, high-volume work done without a human in the loop. Think audits across 77 client sites, or enrichment pipelines turning 2,000 raw leads into 155 qualified M&A targets.

Internal tools and portals

ToolJet, Retool, or custom. The operational UI your team actually lives in: what's running, who owns it, and what needs attention.

n8n / Make workflows with AI nodes

Low-code automation with LLM decision nodes. Business logic that adapts to context, not rigid if-then.

Python agents with tool-calling

Custom agents reaching your databases, APIs, and document stores. Built in your stack, documented for your engineers to maintain and extend.

Clean handoff

Architecture notes, runbooks, and pairing sessions so the capability stays when I leave. No silent vendor lock-in.


Proof points (anonymized)
  • Autonomous audit agent processing 77 client sites — 9 months running without major intervention.
  • M&A enrichment pipeline: 373 companies scored, 155 qualified targets — 2 months of build.
  • Meeting-prep pipeline: transcript → structured note → CRM update, hands-off.
  • 40-hour weekly process reduced to ~2 hours of supervised review.
  • Shipped in weeks, not quarters, when the problem was scoped correctly. A fraction of the usual project weight.