How a startup accelerator runs IT and operations ticketing in Airtable
Employees submit requests via a form, the tech team tracks status and logs resolutions, and every ticket becomes a searchable record. The result is faster answers, fewer repeated questions, and institutional knowledge that stays with the team.
The problem
Support requests arrived through informal channels, making it difficult to triage fairly, track progress, or recall how a past issue was resolved. The same questions surfaced repeatedly as there was no accessible record of previous answers.
Institutional knowledge sat in individual inboxes and memories rather than a shared system. When a team member moved on, that context went with them, and new colleagues faced the same learning curve from scratch.
What they built
The team deployed an Airtable-based ticketing system where employees submit requests through a structured form. Each submission automatically creates a record that the data and tech team can assign, status-track, and annotate as the issue progresses.
Resolved tickets are documented with the solution logged directly in the record, creating a growing repository of past resolutions. This history can be searched by anyone facing a similar question, reducing the burden on the tech team and enabling self-service answers.
The outcome
Support load dropped as employees found answers in the resolution history before raising new tickets. The tech team gained a clear, prioritized queue instead of juggling requests from multiple informal sources.
The searchable record base also laid the foundation for an AI-assisted support experience, where past ticket solutions can be surfaced automatically in response to new questions, further reducing manual triage effort.
Inside the solution
Internal IT and Operations Ticketing
IT Operations and Governance
Information Technology
- Ticket submission via structured form
- Status tracking and team assignment
- Solution documentation on each record
- Searchable resolution history for self-service
- Repeated support questions consuming tech team capacity
- Lost institutional knowledge when team members leave
- Manual ticket triage across informal channels
- Reduced support load through self-service resolution history
- Faster resolution using documented past answers
- Retained knowledge that persists beyond any individual
- Data and Tech
- IT Operations
- Airtable Forms
- Airtable Automations
Internal IT and operations ticketing
Run internal IT and operations support end to end: employees submit structured requests, the tech team works a shared queue with priorities, assignees, and per-service resolution targets, and every fix is documented into a searchable resolution history. Automations open an activity trail on intake, draft a knowledge base article the moment a ticket is resolved, and email a weekly open-queue digest, while AI columns triage new requests and turn resolution notes into self-service answers.
How IT ticketing works in Airtable
Capture requests with a structured form
Assign and track status
Document the resolution
Search the resolution history
FAQ
Frequently asked questions
Employees use a shared Airtable form to submit requests. The form captures all relevant details and automatically creates a new ticket record in the system, so nothing is lost or mis-filed.
All incoming tickets appear in a shared queue that the data and tech team reviews. Each ticket can be assigned to a specific person and given a status, making it clear who is responsible and what stage the request is at.
The resolution is documented on the ticket record before it is marked done. This creates a permanent, searchable log of how each type of issue was handled, which the whole team can reference later.
Yes. Because resolved tickets include documented solutions, employees can search the history before raising a new ticket. Over time, the resolution log acts as a knowledge base that deflects common questions without tech team involvement.
The structured resolution history is designed to support AI-assisted answers. Past ticket solutions can be used to train or prompt an AI tool that surfaces answers automatically when a new similar question is submitted.