Secure Payments, Data and Gen AI at the Source

Financial and fintech companies concentrate exactly what attackers want, and PCI DSS v4.0.1 now demands continuous compliance, not an annual check-the-box audit. Meanwhile cardholder data and PII move through browser uploads, clipboard, SaaS apps, and Gen AI tools your network security can't see. This solution brief shows how fintech teams are closing that visibility gap with a single endpoint agent.

  • Discover and control cardholder data across files, browsers, USB, and clipboard, in real time
  • Block payment and customer data from leaving through unmanaged Gen AI accounts
  • Support PCI DSS v4.0.1 controls, including MFA, anti-phishing, and continuous logging
  • Replace point-tool sprawl with one lightweight agent, deployable in a day

Get the full breakdown of how endpoint-native security closes the gap network tools miss.

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Secure PHI, Data and Gen AI at the Source

Healthcare breaches cost more than any other industry, and PHI now moves through clinician laptops, BYOD devices, and Gen AI tools your network security can't see. This solution brief shows how healthcare providers, payers, and health-tech teams are closing that visibility gap with a single endpoint agent.

  • See PHI move across files, browsers, USB, and Gen AI prompts, in real time
  • Block PHI from leaving through personal Gen AI accounts, without slowing clinicians down
  • Support HIPAA's stricter proposed Security Rule controls, including MFA and encryption
  • Replace point-tool sprawl with one lightweight agent, deployable in a day

Get the full breakdown of how endpoint-native security closes the gap network tools miss.

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Securing GenAI and Agents at the Source

Every employee now has an AI assistant, and every assistant can read, copy, and move sensitive data. Copilots and autonomous agents call internal APIs and move data across tools at machine speed, often with a user's full inherited permissions, while 97% of AI-incident victims lacked proper access controls. This security brief shows CISOs and security leaders how to see, classify, and govern GenAI and agent activity right at the endpoint.

  • Inventory every GenAI app and coding agent running across the fleet, sanctioned or not
  • Classify sensitive data in context, with a human-readable reason for every finding
  • Track sensitive data movement by program, destination, and classification
  • Block risky uploads, pastes, and unsanctioned GenAI destinations in real time

Get the full playbook for governing GenAI and agents at the source.

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Secure Payments, Data and Gen AI at the Source

Financial and fintech companies concentrate exactly what attackers want, and PCI DSS v4.0.1 now demands continuous compliance, not an annual check-the-box audit. Meanwhile cardholder data and PII move through browser uploads, clipboard, SaaS apps, and Gen AI tools your network security can't see. This solution brief shows how fintech teams are closing that visibility gap with a single endpoint agent.

  • Discover and control cardholder data across files, browsers, USB, and clipboard, in real time
  • Block payment and customer data from leaving through unmanaged Gen AI accounts
  • Support PCI DSS v4.0.1 controls, including MFA, anti-phishing, and continuous logging
  • Replace point-tool sprawl with one lightweight agent, deployable in a day

Get the full breakdown of how endpoint-native security closes the gap network tools miss.

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Secure PHI, Data and Gen AI at the Source

Healthcare breaches cost more than any other industry, and PHI now moves through clinician laptops, BYOD devices, and Gen AI tools your network security can't see. This solution brief shows how healthcare providers, payers, and health-tech teams are closing that visibility gap with a single endpoint agent.

  • See PHI move across files, browsers, USB, and Gen AI prompts, in real time
  • Block PHI from leaving through personal Gen AI accounts, without slowing clinicians down
  • Support HIPAA's stricter proposed Security Rule controls, including MFA and encryption
  • Replace point-tool sprawl with one lightweight agent, deployable in a day

Get the full breakdown of how endpoint-native security closes the gap network tools miss.

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Deal Drivers: Americas HY 2026 Report

Americas M&A just posted its strongest half in years. Datasite's Deal Drivers: Americas HY 2026 report tracks US$1.95 trillion in H1 2026 deal value, up 59.6% year-on-year, as AI infrastructure reshapes where capital concentrates across every sector and region.

Inside the report, you will find:

  • The full Americas heat chart, sector by sector and region by region
  • Why TMT and pharma, medical and biotech are setting the pace, and where the buildout is fastest
  • The 10 largest announced deals of H1 2026, including OpenAI, NextEra-Dominion, and Honeywell
  • How private equity is adjusting to a realized-returns market, and where dry powder is heading

Download the report for the full data, charts, and analysis behind H1 2026's record half.

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Third-Party Risk Management (TPRM) Benchmark Report

Vendor ecosystems are expanding faster than most third-party risk programs can keep up with. Manual questionnaires and spreadsheets fragment ownership, evidence, and audit defensibility right when assurance expectations are rising.

Hyperproof surveyed security, risk, and compliance leaders to see how real programs assess vendor risk, budget for it, and handle the newest wrinkle: AI in the vendor stack.

In this report, you will learn:

  • Why 73 percent of automated programs use a dedicated VRM solution, versus 49 percent of manual ones
  • Why 34 percent of respondents still manage third-party risk in spreadsheets
  • How organizations are formalizing (or not yet formalizing) AI supplier risk assessment
  • Maturity and spend benchmarks segmented by budget, region, and industry

Download the report and see exactly where your TPRM program stands against your peers.

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The Economics of Autonomous Production Ops

Every engineering org has pointed an AI agent at production by now. Few have engineered the context and economics that decide whether that agent survives real volume. This whitepaper breaks down why the operations gap became an economics problem.

In this whitepaper, you'll learn:

  • Why token consumption, not model choice, decides if AI ops pays for itself past the pilot
  • Why Mean Time to Understand, not resolution speed, is the real bottleneck in production incidents
  • How context engineering cuts cost and boosts accuracy at once, replacing the tradeoff most teams assume exists
  • A buyer's framework for evaluating a production ops agent built to last past the demo

The practical takeaway for a CTO is a shift in the question. The question is not "which model is smartest," or even "which vendor has an agent." It is "who has engineered the context and economics so that autonomy is reliable, affordable, and defensible at the scale I actually run".

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Advanced AI Workforce Planning for Construction Leaders

AI is now built into nearly every construction platform, but not every implementation delivers real workforce planning value. This guide gives construction leaders a practical framework for separating genuine AI advantage from surface-level features.

In this guide, you'll learn:

  • How to evaluate AI construction tools across the 7 categories reshaping the market, from workforce platforms to integration middleware
  • What MCPs mean for your tech stack, the emerging standard letting AI connect reliably across systems in real time instead of relying on delayed, manual integrations
  • Where AI agents can act on their own, from flagging scheduling conflicts to surfacing bench risk, and where human judgment still matters
  • The 3 degrees of data maturity that determine whether your data is ready to power reliable, autonomous AI decisions

Download the guide to see where your firm stands and what to prioritize next.

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Advanced AI Workforce Planning for Construction Leaders

AI is now built into nearly every construction platform, but not every implementation delivers real workforce planning value. This guide gives construction leaders a practical framework for separating genuine AI advantage from surface-level features.

In this guide, you'll learn:

  • How to evaluate AI construction tools across the 7 categories reshaping the market, from workforce platforms to integration middleware
  • What MCPs mean for your tech stack, the emerging standard letting AI connect reliably across systems in real time instead of relying on delayed, manual integrations
  • Where AI agents can act on their own, from flagging scheduling conflicts to surfacing bench risk, and where human judgment still matters
  • The 3 degrees of data maturity that determine whether your data is ready to power reliable, autonomous AI decisions

Download the guide to see where your firm stands and what to prioritize next.

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See How PBXware V8 Turns AI Into a Revenue Line, Not a Buzzword

Version 8 is Bicom Systems' biggest platform release yet, and the first where AI is a feature you can activate, configure and charge for, not a slide in a deck.

This overview breaks down what's shipping in PBXware and gloCOM V8, so you can see exactly what your tenants get and what you can sell around it.

In this one-pager, you'll find:

  • How the AI Voice Agent, powered by OpenAI, handles inbound calls with no human in the loop
  • What Live Transcription unlocks for compliance, QA and agent coaching
  • How AI Hub gives you cost and usage visibility across every tenant, with no added infrastructure
  • Why Multi-CRM support (10 platforms including Odoo) and the redesigned gloCOM Next app matter for adoption

No extra build required. Just what's live in V8 and how to position it to your tenants.

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The new deal team: What 1,000 dealmakers reveal about AI-driven M&A

AI is no longer an edge in M&A, it is becoming the baseline. Datasite surveyed 1,000 senior dealmakers, backed by in-depth interviews with M&A leaders, to reveal how AI is reshaping every stage of the deal, and where human judgment still decides the outcome. See where your peers are placing their bets and how the modern deal team is being built.

Inside the report, you will learn:

  • The deal stages where AI is already fully embedded, led by due diligence and sourcing
  • Why 62% of dealmakers now call human-only decisions indefensible on complex deals
  • The decisions that stay human, from final sign-off to reading the room with a founder
  • How top firms build accuracy, security, and governance into AI-assisted dealmaking
  • What the next deal team looks like as AI handles the prep, and people close the last mile
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How to Evaluate AI Vendors for Your Legal Team

AI tools are entering legal workflows faster than most firms can vet them. Contract review, e-discovery, compliance monitoring - the use cases are real, but so are the risks. Confidentiality gaps, unreliable outputs, and tools that can't adapt to your specific playbooks can set your team back instead of moving it forward.

This guide gives legal teams a structured evaluation framework covering six critical areas - so you can ask the right questions before you commit.

What you'll learn:

  • How to assess whether a tool adapts to your firm's policies, escalation rules, and precedents
  • What accuracy benchmarks and error-tracking standards to require
  • Key governance and ethics questions including bias audits and audit rights
  • Integration requirements that determine real-world adoption
  • How to tie AI selection to defined legal outcomes - not vague productivity gains
  • ROI evidence and scaling criteria to validate before expanding beyond a pilot
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Is Your Contract Review Process Ready for What’s Next?

In-house legal teams are being asked to handle more contracts, faster, without adding headcount. The result: inconsistent redlines, institutional knowledge that lives only in senior counsel's heads, and a constant tradeoff between speed and accuracy.

This toolkit from Filevine helps legal operations leaders diagnose where their contract review process is falling short — and what modernization actually looks like in practice.

What you'll get:

  • A breakdown of the four hidden costs teams face when they try to scale contract review manually
  • A 24-point self-assessment checklist covering volume, urgency, consistency, workflow, AI readiness, and business impact
  • A scoring framework to benchmark where your team stands today
  • A clear picture of what domain-specific AI looks like when it's built directly into Microsoft Word — not bolted on as a separate platform

Built for General Counsel, legal ops leaders, and contract teams navigating growing workloads with flat resources.

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Close the Personalization Gap in Your External Training

Personalization works for employees because the system already knows them. The moment you train distributors, resellers, partners, and customers, that breaks. Roles are unclear, knowledge levels vary widely, and no one is obligated to finish.

This guide shows why employee-first LMS platforms fall short in external training, and what a platform built for the extended enterprise does differently to keep partners and customers engaged.

What you'll learn:

  • Why personalized pathways break down once learners sit outside your organization
  • Where rule-based logic, manual segmentation, and internal recommendation engines hit a wall at scale
  • The hidden costs of an employee-first LMS: admin overhead, localization delays, and learner drop-off
  • What adaptive learning looks like at scale, from diagnostic entry points to role-based storefronts and AI-supported delivery
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