Subcategory · AI Citation Index

Government & Public Sector

Government software is AI's most fragmented vertical SaaS category. Tyler Technologies and OpenGov Procurement & Contract Management each surface in 43% of buyer queries about public-sector software, both visible on every engine we audit (ChatGPT, Claude, Gemini, Perplexity). A brand labeled 'default.com' captures 66% of discovery prompts but appears on only three engines, suggesting domain-placeholder noise in the training corpus. The real story is the absence of any consensus pick — no vendor wins enough head-to-head comparisons for us to report evaluation outcomes, and discovery share fragments across a long tail of permitting, civic-engagement, and procurement vendors. This is a fragmented category with no brand consolidating AI attention.

35 discovery queries · refreshed May 1, 2026

Discovery stage

The shortlist

Across 35 buyer-style "Government & Public Sector" queries

Tyler Technologies and OpenGov Procurement & Contract Management split AI discovery share almost evenly. Each shows up in 43% of buyer queries about government software and surfaces across all four engines we audit (ChatGPT, Claude, Gemini, Perplexity). A data artifact labeled 'default.com' captures two-thirds of discovery prompts but appears on only three engines and carries no meaningful brand identity; strip that noise and the shortlist is a tie between Tyler and OpenGov, with PointApp trailing at 43% share but visible on only three engines.

0%5%9%14%19%Coverage — share of discovery prompts where the brand surfaces15%33%52%70%89%Engine diversity

Hover or click a logo to see brand details

X = coverage across discovery prompts · Y = engine diversity · Bubble size = total mentions
Tracked acrossChatGPT,Gemini,Claude

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Signal by intent

By topic

Top 5 most-cited brands per intent cluster. Brands with zero citations in a topic are not shown.

1Default
3/6
2Atlassian
2/6
3OpenGov
2/6
4Salesforce
2/6
5Hyperproof
2/6
1POINT
4/6
2OpenGov
4/6
3Default
3/6
4Tyler Technologies
2/6
5Atlassian
2/6
1OpenGov
6/6
2Granicus
5/6
3Accela
4/6
4Tyler Technologies
4/6
5Atlassian
2/6
1Granicus
3/6
2Salesforce
2/6
3Accela
2/6
4OpenGov
2/6
5POINT
2/6
1Default
5/5
2Tyler Technologies
4/5
3OpenGov
4/5
4Granicus
2/5
5Salesforce
2/5
1Tyler Technologies
3/5
2Default
3/5
3Salesforce
2/5
4Oracle
2/5
5OpenGov
2/5
1Default
4/5
2Tyler Technologies
2/5
3POINT
2/5
4Planview
1/5
5Atlassian
1/5
1Tyler Technologies
4/5
2OpenGov
3/5
3Knowledge
2/5
4Salesforce
2/5
5Granicus
2/5
≥50% cited
25–49%
<25%
Topics are discovery-stage prompt clusters · public-sector

Citation sources

Where AI pulls citations from

781 citations captured across Government & Public Sector prompt runs.

Vendor pages

210

Product, help, and marketing pages from tracked vendors

Independent sources

189

Reviews, encyclopedias, forums, press — not vendor-owned

Buyer questions

What AI cites for top Government & Public Sector questions

Buyers ask AI for government software recommendations filtered by agency size and function. Typical queries ask for software ideal for enterprise-level operations, mid-market project management, or community outreach in large agencies. Every query we captured is top-of-funnel exploration — no one is asking AI to compare specific vendors head-to-head or validate pricing. The prompt mix suggests buyers use AI to build an initial shortlist, then move offline to evaluate finalists.

Discovery

Buyers exploring the category

Evaluation

Buyers comparing options

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