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PubConcierge Unveils ‘Responsible Web Data for AI’ Ahead of AI & Big Data Expo London (Feb 4–5, 2026)

PubConcierge

PubConcierge

PubConcierge team at AI & Big Data Expo - London, 4-5 February 2026, booth 244

PubConcierge team at AI & Big Data Expo - London, 4-5 February 2026, booth 244

PubConcierge launches Responsible Web Data for AI, a governance framework for traceable, audit-ready web data collection. See demos at Expo London, Booth 244.

Responsible Web Data for AI makes web-scale collection traceable by design so teams can move fast and still be ready for scrutiny.”
— Flavius Porumb, CEO
LONDON, UNITED KINGDOM, February 2, 2026 /EINPresswire.com/ -- PubConcierge today introduced Responsible Web Data for AI, a practical governance framework for teams collecting public web data for AI and analytics. The approach helps organizations prove where data came from, what policies were applied, and how collection was controlled, with audit-ready logs and traceable provenance built into day-to-day operations.

As AI moves into regulated and revenue-critical workflows, data leaders are increasingly expected to demonstrate governance, not simply promise it.

“AI teams are being asked auditor-grade questions about provenance, controls, and decision logs, often without the luxury of slowing down,” said Flavius Porumb, CEO of PubConcierge. “Responsible Web Data for AI makes web-scale collection traceable by design so teams can move fast and still be ready for scrutiny.”

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬 𝐧𝐨𝐰

Web-scale collection is no longer just an uptime and performance challenge, it’s an accountability requirement. Teams are being asked:
• Where did the data come from?
• What was collected, and what was excluded?
• Which policies were applied, when, and by whom?
• Can we show consistent controls and responsible access behavior?

𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞 𝐩𝐫𝐞𝐬𝐬𝐮𝐫𝐞 𝐢𝐬 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞

• EU AI Act penalties raise the stakes: fines can reach €35M or 7% of worldwide annual turnover (whichever is higher) for certain infringements.
• AI is expanding privacy/compliance programs fast: Cisco’s 2026 Data Privacy Benchmark reports 90% of organizations expanded privacy programs because of AI and only 12% consider their AI governance structures mature.
• Third-party exposure is rising: Verizon’s 2025 DBIR found third-party involvement in breaches doubled to 30%, based on analysis of 22,000+ incidents including 12,195 confirmed breaches.
• Global scope keeps widening: IAPP reports comprehensive privacy/data protection laws are now in effect in 144 countries, expanding cross-border compliance expectations for web data programs.

𝐅𝐢𝐯𝐞 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐩𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬 𝐟𝐨𝐫 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞-𝐫𝐞𝐚𝐝𝐲 𝐰𝐞𝐛 𝐝𝐚𝐭𝐚

Responsible Web Data for AI is built on five principles:
1. Data minimization — collect only what’s needed for a defined purpose.
2. End-to-end audit logs — preserve sources, timestamps, policy decisions, and transformations.
3. Fair access rates — apply responsible pacing and rate limits to reduce disruption.
4. Rule-aware collection — support policy-driven evaluation of site rules, with documented exceptions where appropriate.
5. Sensitive-data filtering — detect and exclude sensitive categories, supported by retention and access controls.

𝐖𝐡𝐲 𝐭𝐡𝐞 𝐩𝐫𝐨𝐱𝐲 𝐥𝐚𝐲𝐞𝐫 𝐦𝐚𝐭𝐭𝐞𝐫𝐬

PubConcierge’s approach highlights a simple idea: the proxy layer can act as a control plane because every request passes through it. Used responsibly, proxy infrastructure can help teams:
• Capture source-level provenance automatically (domains, timestamps, sessions, routing context)
• Standardize logging and controls across distributed collectors and regions
• Enforce fair access rates consistently at the edge
• Support policy-driven allow/deny decisions and exception tracking
• Reduce exposure risk by triggering filtering and retention workflows systematically
Governance becomes an engineering primitive: measurable, enforceable, and auditable.


𝐖𝐡𝐚𝐭 𝐏𝐮𝐛𝐂𝐨𝐧𝐜𝐢𝐞𝐫𝐠𝐞 𝐰𝐢𝐥𝐥 𝐬𝐡𝐨𝐰 𝐚𝐭 𝐀𝐈 & 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐄𝐱𝐩𝐨 𝐋𝐨𝐧𝐝𝐨𝐧 (𝐁𝐨𝐨𝐭𝐡 𝟐𝟒𝟒)

At AI & Big Data Expo Global (Olympia London), February 4–5, 2026, booth 244, PubConcierge will share practical guidance and examples for building governance-ready public web data pipelines, including:
• How to structure audit-ready provenance logs
• How to apply centralized rate fairness and policy controls across teams
• How to build reviewable workflows for rule-aware operations
• How to operationalize sensitive-data filtering + retention governance

Meet PubConcierge
AI & Big Data Expo Global — London (Olympia London)
Dates: February 4–5, 2026
Booth: 244

𝐀𝐛𝐨𝐮𝐭 𝐏𝐮𝐛𝐂𝐨𝐧𝐜𝐢𝐞𝐫𝐠𝐞

PubConcierge is a global IP leasing and proxy infrastructure provider offering access to 100M+ IP addresses across 1,700+ locations, with fast provisioning and infrastructure spanning bare metal and cloud.
PubConcierge powers AI data acquisition, web intelligence, and global testing with clean, compliant sourcing, performance controls, and on-demand proxy solutions, helping data and AI leaders build public web data pipelines with operational control, traceability, and governance-ready collection patterns.

www.pubconcierge.com
marketing@pubconcierge.com

Marketing & PR Team
Pub Concierge LLC
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