Context
Funds, accelerators, and venture studios often run on a fragile mix of Airtable bases, Notion docs, Slack threads, email templates, spreadsheet trackers, and half-connected automations. That works until volume increases, ownership blurs, or the team starts layering AI on top of messy process data.
I help teams turn that sprawl into a usable operating system. The work starts with auditing how the team actually operates, then designing the right boundary between database, automation, dashboard, and custom software. Airtable or Notion can remain the source of truth. Pipedream or n8n can handle cross-system orchestration. Custom apps are reserved for workflows that need richer UI, stronger configuration, or better control.
This pattern was proven inside 
Iterativeiterative.vcEarly-stage VC fund investing up to US$500K in startups twice a year, working closely with founders for 3 months — 70+ portfolio companies across Southeast Asia and South Asia.
Iterative, where I owned the operating stack behind a 70+ company VC portfolio: application intake, founder communication, partner assignment, interview scheduling, IC preparation, term sheet generation, SLA reporting, and portfolio dashboards.
What I Build
- Ops Audit & System Map: Translate messy team workflows into a clear operating model: who owns each step, what data matters, where state should live, and which handoffs are currently fragile.
- Data Model Design: Normalise Airtable, Notion, spreadsheet, and CRM structures so automations and AI systems have clean records to work with instead of ambiguous process state.
- Right-Sized Automation: Use Airtable automations for table-native state changes, Pipedream or n8n for cross-system workflows, and custom apps only when configuration, reporting, or control justify the build.
- Document & Asset Pipelines: Build flows for pitch decks, attachments, memos, reports, and founder materials so files are stored, named, linked, and retrievable without manual cleanup.
- Slack-Native Operations: Route reminders, SLA alerts, approvals, handoffs, infrastructure health checks, and exceptions into the channels where teams already operate.
- Dashboards & Reporting: Build fund, program, and portfolio dashboards for funnel health, SLA tracking, conversion, partner workload, and portfolio performance.
- Production Guardrails: Add filtered triggers, runtime checks before transactions, idempotency, rate limits, cost limits, and clear ownership between no-code automations and custom code.
Stack & Use Cases
Airtableairtable.comSpreadsheet-database hybrid — the operational data layer for deal flow, portfolio tracking, and internal tooling at fund scale.AirtablePipedreampipedream.comServerless integration platform — connects APIs and runs event-driven workflows without managing infrastructure.Pipedreamn8nn8n.ioSource-available workflow automation — node-based, self-hostable, and the workhorse behind most of the operational automations I ship.n8nNotionnotion.comConnected workspace for docs, wikis, and databases — where team knowledge lives and what internal tools read from and write to.NotionSlackslack.comTeam messaging platform — the front-end where automations deliver their output: alerts, digests, and natural-language queries.SlackMetabasemetabase.comOpen-source business intelligence — dashboards and analytics over any database, without a data team to maintain them.MetabasePostgreSQLpostgresql.orgThe world's most advanced open-source relational database — the default choice for production data that has to be correct.PostgreSQLAirbyteairbyte.comOpen-source data integration — ELT pipelines moving data from SaaS tools and APIs into the warehouse.AirbyteVenture operationsDeal flow CRMApplication intakeFounder communicationsIC preparationSLA dashboardsPortfolio reportingAsset backup pipelines
Outcome
- Manual coordination replaced by visible, reliable operating workflows
- Cleaner data models that support automation, reporting, and AI layers
- Fewer missed handoffs across applications, interviews, approvals, follow-ups, and reporting cycles
- Clearer SLA visibility, workload tracking, and operational accountability
- A reusable venture-ops playbook for turning messy internal process into production-grade infrastructure