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Server Build Request Intake Survey

A structured intake form for IT and infrastructure teams to capture what a requester actually needs before provisioning a new server — workload type, environment, resource needs, and data sensitivity — with an AI follow-up that digs into usage patterns, dependencies, and downtime tolerance that checkbox fields miss.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

14 questions · ~7 min
Q01
Message

Thanks for submitting a server build request! A few quick questions will help our infrastructure team size and configure it correctly the first time. About 8 minutes.

Q02
Multiple ChoiceRequired

What type of server are you requesting?

  • Physical server
  • Virtual machine
  • Cloud instance
  • Container / Kubernetes workload
  • Not sure — need guidance
Q03
Multiple ChoiceRequired

What will this server primarily be used for?

  • Web application hosting
  • Database
  • File or storage server
  • Development / testing sandbox
  • Internal tool or automation
  • Batch or scheduled processing
Q04
Short TextRequired

What project or application is this server for? (Give it a name we can reference in tickets.)

Q05
Multiple ChoiceRequired

Which environment is this server for?

  • Production
  • Staging / pre-production
  • Development
  • QA / testing
Q06
MatrixRequired

How much of each resource do you expect this server to need?

4 rows × 4 columns
  • Processing power (CPU)
  • Memory (RAM)
  • Storage capacity
  • Network throughput
Columns: Low · Medium · High · Not sure
Q07
Opinion ScaleRequired

How tolerant is this workload of downtime or interruptions?

Scale: 1 – 10
Min:Can be down for hours with no real impactMax:Must be available at all times
Q08
Multiple ChoiceRequired

What is the sensitivity of the data this server will store or process?

  • Public, no restrictions
  • Internal use only
  • Confidential business data
  • Regulated data (e.g., customer PII, health, or payment data)
  • Not sure — need guidance
Q09
DateRequired

By what date do you need this server ready to use?

Q10
Long Text

List any systems this server needs to connect to, software it must run, or other technical dependencies we should know about.

Q11
AI Interview

Probe the real workload behind the requester's stated purpose and resource estimates: ask what triggers spikes in usage, roughly how many people or systems will hit it at peak, and what other services it must talk to. Ask concretely what would happen to their work if this server went down for an hour, to sanity-check their downtime tolerance answer. If they picked 'Not sure' for server type or data sensitivity, walk them through what data will live on it and who can access it, then flag their answer for infrastructure team review rather than assuming a default.

Q12
Short Text

If known, what cost center or budget code should this build be charged to? (Leave blank if you don't have one yet.)

Q13
Dropdown

Which department are you requesting this on behalf of?

  • Engineering
  • IT Operations
  • Data / Analytics
  • Product
  • Marketing
  • Finance
  • Other
  • Prefer not to say
Q14
Message

All set — thank you! Your request goes straight to our infrastructure team, who'll use these details (and your follow-up answers) to size and schedule the build. You'll hear back with a timeline shortly.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Pairs structured intake fields (server type, primary use, environment, resource matrix, data sensitivity) with an AI follow-up interview that digs into real usage patterns, dependencies, and downtime tolerance that checkboxes miss.
  • Captures downtime tolerance with a dedicated opinion scale, giving infra teams a usable signal for SLA and redundancy planning instead of a vague text field.
  • Includes cost-center/budget code and department fields so requests can be routed, approved, and charged correctly without a follow-up email chain.
  • Bookends the intake with clear chat messages and routes straight into an auto-generated report for the infrastructure team, rather than leaving raw answers to be manually parsed.

SurveySparrow

Streamline Server Builds | Server Build Request Form Template

A ready-to-field template built specifically for capturing server build requests, so it's directly comparable in purpose to ours. It relies on static fields and conditional logic rather than a live conversational interview, meaning ambiguous answers (e.g., vague resource estimates) can't be clarified in the moment. No indication of automated per-response quality scoring or published prompt methodology.

What it does well

  • Purpose-built specifically for server build requests, not a generic IT form
  • Part of an established survey/form platform with branching logic capability
  • Likely supports quick deployment for IT teams already on SurveySparrow

Where it falls short

  • No adaptive AI follow-up to probe unclear workload or dependency answers
  • No voice AI interview option
  • No visible automated quality scoring or transparent prompt methodology

Typeform

Server Build Request Form Template

A dedicated, fielding-ready template for the same use case, benefiting from Typeform's clean one-question-at-a-time conversational UI. It's still a static form under the hood — logic jumps can branch based on prior answers but can't generate a genuinely new follow-up question tailored to what a requester typed. No published scoring or reporting automation specific to server intake.

What it does well

  • Polished, distraction-light form-filling experience
  • Conditional logic to show/hide fields based on prior answers
  • Widely used, well-documented template platform for quick setup

Where it falls short

  • No AI interviewer that dynamically probes usage patterns or downtime tolerance
  • No voice AI interview mode
  • No automated per-response quality scoring or transparent prompt disclosure

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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