AeroLeads maps 4 IT employee signals for EGSYS. The strongest visible leadership sample is Fernanda Soares (Analista De Qualidade De Software - Tester - QA Lead).
EGSYS's IT Department
Fernanda Soares
Analista De Qualidade De Software - Tester - QA Lead
2
0
Lead (1)
Fernanda Soares
Analista De Qualidade De Software - Tester - QA Lead
2
0
Related company intelligence for EGSYS
10 with employee estimates
10 with websites
10 with social profiles
3 peer evidence types
Peer evidence source coverage
3 source-backed evidence types support this related-company graph.
employee benchmarks, website records, and social profiles
Employee benchmarks
10 / 10
10 of 10 related companies include employee estimates.
Website records
10 / 10
10 of 10 related companies include official website records.
Social profiles
10 / 10
10 of 10 related companies include company social profile signals.
Peer link quality filter
High-confidence peer link set
10 related companies met the 2-signal peer-link threshold. Eligible peers average 4.0 source-backed signals.
10
eligible
0
filtered
4.0
avg signals
Peer comparison matrix
Limited peer comparison
Compares this company with related-company evidence across employee scale and peer graph evidence.
employee scale and peer graph evidence
Employee scale
Smaller than most related peers
This company
29 employees
Related peers
202 median peer employees
7 of 10 related employee-estimated peers are higher.
10 related companies with employee estimates
Peer graph evidence
Multi-signal peer benchmark evidence
This company
Partial peer evidence graph
Related peers
3 benchmark dimensions
Peer benchmark combines 10 related companies with peer graph strength, size benchmark, and size position. Underlying peer graph includes 3 evidence types: employee benchmarks, website records, social profiles.
employee benchmarks, website records, social profiles
Peer benchmark evidence
Multi-signal peer benchmark evidence
Peer benchmark combines 10 related companies with peer graph strength, size benchmark, and size position. Underlying peer graph includes 3 evidence types: employee benchmarks, website records, social profiles.
peer graph strength
size benchmark
size position
Peer position benchmark
Employee-scale peer position benchmark
Peer-position benchmark shows employee scale above 30% of 10 comparable related peers.
Directional peer-position evidence:
Peer-position evidence combines employee scale above 30% of 10 comparable related peers from related-company records.
Employee scale: 30%
Peer graph strength
Partial peer evidence graph
Related peer graph has employee benchmarks, website records, and social profiles across 10 related companies.
Peer median size
202 employees
Largest peer by size
Braskem
10.54K employees
EGSYS size signal
29 employees
Peer size comparison
7 larger · 3 smaller
Peer scale position
Smaller than most related peers
7 of 10 related employee-estimated peers are higher.
EGSYS people graph sample
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Adriana Bueno
Agile Project Manager - Agile Master - Digital Products and Projects
Porto Alegre, Rio Grande Do Sul, Brazil -
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Bruno Silveira Camilo
Coordenador De Infraestrutura E Suporte - Segurança Da Informação - Gestão De Tenologia Da Informação
Porto Alegre, Rio Grande Do Sul, Brazil
How AeroLeads builds company intelligence
Use source-backed company records
AeroLeads combines company source fields, workforce samples, email-pattern aggregates, and related-company records when those signals are available.
Show only available evidence
Blank source fields are omitted. Contact channels are summarized as signals, with raw email addresses and phone numbers masked on public pages.
Compare useful company context
Related company, market, workforce, technology, and management signals help turn a static company listing into a company intelligence page.
Account research
AeroLeads intelligence
Review account research for EGSYS
Account research checklist combines best covered outreach path, buying-committee coverage, ICP fit, technology workforce evidence, related-company graph, and domain trust; raw contact values are hidden.