LuminOps

Technical operating partner

Technical operating partner for founders and investors.

Part-time CTO/COO support for startups, funds, and family offices moving from scattered spreadsheets and disconnected tools to reliable AI-ready operations.

Request a systems diagnostic

Bring one messy workflow, CRM, spreadsheet, or investment process.

Who I work with

Two ways LuminOps plugs in: senior operating support for founders, and technical operating partner support for investors.

Founders and operators

For teams where operations still depend on Excel, Notion, ad-hoc CRMs, and manual handoffs. I help turn the recurring mess into a working data layer, practical automation, and internal tools people actually use.

Part-time CTO/COO support when you need senior technical execution without hiring a full team.

VC, PE, and family offices

For investment teams and principals who need better sourcing, screening, memo production, and portfolio oversight. I build the operating layer between public data, internal judgment, and repeatable deal workflows.

Technical operating partner support for funds and holding structures that need leverage across the portfolio.

What I buildThe operating layer behind cleaner data, faster decisions, and fewer manual loops.
01Operating system design

Map the messy workflow, decide what should stay human, then design the data, tools, automations, and review points that make the process repeatable.

02Systems diagnostics

Turn a vague AI or automation ambition into a practical first build: workflow audit, data readiness, tool choices, risks, and implementation roadmap.

03Automation infrastructure

Reliable workflow plumbing between CRM, email, documents, finance tools, public data sources, and internal databases. Built with audit trails and failure handling.

04Data and CRM architecture

Schemas, pipelines, and CRMs structured around how the team actually works. Airtable, HubSpot, Postgres, or custom systems chosen for the job.

05Internal tools and consoles

Operator consoles, dashboards, and client portals for the people who run the system day to day. Softr, Retool, or Next.js depending on the workflow.

06Investment and portfolio workflows

Sourcing pipelines, screening notes, memo generators, DD workplans, and portfolio dashboards for teams that need better leverage without losing judgment.

Use casesConcrete systems for sourcing, screening, reporting, revenue ops, and finance workflows.
Deal-flow sourcing pipeline

Problem. Inbound and one-off scrapes create patchy coverage and stale funnels.

Build. A scheduled sourcing engine enriches public company signals, scores candidates, and writes them into the team's CRM.

Proof. Deployed for a Paris-based impact fund across 8 European jurisdictions.

Investment screening workflow

Problem. Analysts spend 30-90 minutes reading each target before a real decision can happen.

Build. A structured screening note combines web research, source trails, and a human sign-off step inside the CRM.

Proof. 25% actionable rate on a 20-target pilot.

PE and M&A memo generator

Problem. Deal teams rewrite the same memo structure from scratch for every opportunity.

Build. A 12-section house memo template connects source documents, public filings, citations, and Word or Notion export.

Proof. Designed to move first drafts from days to hours while keeping analyst review in the loop.

Family office dashboard

Problem. Holdings, KPIs, board decks, and contacts live across drives, spreadsheets, and inboxes.

Build. A unified dashboard gives each company a structured record, latest metrics, documents, and status flags.

Proof. Built for a European family office with 9 portfolio companies.

Meeting intelligence to CRM

Problem. Good sales or ops meetings turn into transcripts that nobody has time to reread.

Build. Meeting summaries, action items, owners, and follow-ups are pushed into the CRM and team digest.

Proof. Deployed for a French PropTech sales organization handling 60+ meetings per week.

Back-office finance automation

Problem. Receipts, invoices, and reconciliation tasks are rebuilt manually at month-end.

Build. Multi-channel receipt capture, invoice generation, bank matching, and exception queues keep finance work current.

Proof. Live in LuminOps' own accounting workflow.

Working withFunds, scale-ups, and founder-led businesses across Europe.

Funds, scale-ups, and founder-led businesses across Europe.

Investment and capital
Aurae ImpactHRAMEpopée Gestion
Industrial and mobility
Garage Italia
La Manufacture
Newtron
Consumer and media
AktaGR10KChambre 52Panco BunsSCoT(T)Stories We TellPhantasm
Software and platforms
HubloAvalonCohabsThe Oasis House
Education and services
AD EducationLe WagonBackboneThe Ark ManagementAlkiosBilana

About

Why LuminOps sits between product, operations, data, and investment workflows.

Victor Gabella

I got my start co-founding or joining early-stage startups as partner, associate, or first hire across EdTech, CivicTech, PropTech, New Space, and Sustainability. That gave me a practical view of how messy early operations become when product, sales, finance, and data all move at once.

I then worked in venture capital at Bpifrance, built internal data tools, trained in data science at Le Wagon, and joined iad, a French PropTech unicorn, where I led market expansion across five countries over two years.

Today, LuminOps gives founders, funds, and family offices a technical operating partner: broad enough to understand the business workflow, technical enough to build the system, and senior enough to know what should not be automated. Also co-founder and CPTO of Margot. Guest lecturer at ESSEC on venture capital and at Le Wagon on automation and AI. Based in Paris, working in French and English.

Bring me one messy workflow.

Send the spreadsheet, CRM problem, investment workflow, or manual process you want to fix. I will help you map what should be automated, what should stay human, and what a first build could look like.

What to send

  • The spreadsheet, CRM, inbox, or process that keeps slowing people down
  • The tools involved and where the data currently lives
  • What breaks, repeats, or depends too much on one person

What happens next

  1. 01I map the workflow and the handoffs
  2. 02We separate what should stay human from what can be automated
  3. 03I suggest a practical first build with the lowest useful scope