The SASE Comparison Criteria That Actually Matter in 2026 (And the Ones That Don't)

Everyone Has a SASE Comparison Checklist. Most of Them Are Wrong.

I have sat through more SASE vendor evaluations than I care to count. The pattern is always the same. Someone downloads a comparison template from a vendor website, fills in checkmarks during sales demos, picks the vendor with the most green cells, and calls it a day.

Then six months into deployment, the problems start. Mobile devices are not inspected. GenAI traffic slips through unmonitored. The "unified console" turns out to be three portals behind a single sign-on. The vendor's definition of "supported" and yours were never the same.

This is not a hypothetical. According to the 2025 SSE Adoption Report, 96% of organizations encountered barriers during SASE deployment. Only 8% report their SASE deployment is fully live. That gap between evaluation confidence and deployment reality is enormous, and it starts with the wrong comparison criteria.

The SASE market hit $2.7 billion in Q2 2025, growing 22% year-over-year. Gartner now evaluates 11 vendors in its Magic Quadrant. Forrester scores 8 in its Wave. There are more options, more marketing, and more noise than ever before. Choosing wrong is expensive. A retail chain that selected a vendor scaled for 50 locations had to rip and replace when they hit 200 stores 18 months later. A healthcare provider picked the vendor with the best feature sheet and discovered their support could not help with basic deployment issues.

This guide is built from two years of independent vendor testing across 26 comparison topics, 200+ individual capability checks, and cross-referencing three major analyst frameworks (Gartner Magic Quadrant 2025, Forrester Wave Q3 2025, and Gartner Critical Capabilities 2025). It is the criteria list I wish someone had handed me before my first SASE evaluation.

What Changed in 2026: Why Old Criteria Fail

If your SASE evaluation checklist looks the same as it did in 2024, you are evaluating for a market that no longer exists. Three shifts have fundamentally changed what matters.

Shift 1: GenAI Made DLP the New Battleground

Forrester's 2025 SASE Wave called DLP "the cornerstone of platform differentiation." That was not true two years ago. What changed is that employees are now pasting sensitive data into AI tools at industrial scale. Zscaler's ThreatLabz report documented 410 million DLP violations tied to ChatGPT alone. Netskope found that GenAI prompt volume increased 500% year-over-year, with the average organization recording 223 data policy violations per month from GenAI usage.

Traditional DLP criteria ("does the vendor support DLP?") are useless when the real question is whether the vendor can inspect WebSocket-streamed AI responses, handle token-level data flows, and apply context-aware policies to 1,550+ GenAI applications. We tested this across GenAI DLP with 23 checks, and the gap between vendors is massive.

Shift 2: Agentic AI Created an Entirely New Attack Surface

Microsoft reported that 82% of Fortune 500 companies now use agentic AI. Gartner projects 40% of enterprise applications will feature embedded agents by year-end. Researchers found 8,000+ exposed MCP servers in January 2026 alone. This is a category of risk that did not exist during your last SASE evaluation.

Vendors are scrambling. Seven of eight vendors in our AI Security Controls comparison shipped agentic AI visibility within the past six months. But "shipped" and "production-ready" are different things. Your criteria need to distinguish between the two.

Shift 3: Vendor Consolidation Accelerated

Gartner reports that 75% of organizations are pursuing security vendor consolidation, up from 29% in 2020. The average enterprise still uses 60 to 80 distinct security tools. Dell'Oro forecasts that single-vendor SASE will represent 90% of the $17 billion market by 2029. Forrester excluded Cisco from its 2025 SASE Wave entirely because their management interfaces were not sufficiently unified.

The implication: evaluating SASE components in isolation ("how good is the SWG?" "how good is the SD-WAN?") misses the point. What matters is how well the components work together. That requires different criteria than most checklists include.

The 4 Criteria You Can Stop Worrying About

Before we get to what matters, let us clear out the noise. These criteria still appear on most SASE evaluation templates, but they no longer differentiate vendors.

1. Basic SWG, CASB, and ZTNA

Every SASE vendor on the market offers SWG, CASB, and ZTNA. Over 20 vendors now deliver these capabilities. Forrester explicitly calls them "table stakes." If your evaluation spends significant time comparing basic web filtering or basic cloud app visibility, you are comparing on features where all vendors are adequate. The differentiation is in the depth and integration of these features, not their existence.

2. Number of PoPs (Without Context)

Vendor marketing loves PoP counts. "We have 150 PoPs!" "We have 200 PoPs!" The number alone means nothing. What matters is whether those PoPs are on owned infrastructure or leased capacity, whether inter-PoP connectivity uses a private backbone or the public internet, and what the 95th-percentile latency looks like with all security functions enabled. A vendor with 80 owned PoPs on a private backbone can outperform a vendor with 200 leased PoPs routing traffic over the public internet.

3. Compliance Certifications (The List)

Every major SASE vendor holds SOC 2, ISO 27001, and FedRAMP authorizations. Listing certifications on a comparison spreadsheet does not tell you whether the vendor can keep your data within specific geographic boundaries, support local key management, or meet DORA's Article 28 requirements for audit rights and incident support. Data sovereignty capabilities matter. Certification logos do not differentiate.

4. "AI-Powered" Threat Detection (The Buzzword)

Every vendor now claims AI-powered threat detection. The term has become meaningless. What matters is whether the AI drives measurable outcomes: faster detection, fewer false positives, automated policy recommendations, or real-time user coaching. Forrester noted that "the degree that AI helped in each criterion was a major aspect in setting vendors apart" in 2025, but the operative word is "helped." The AI must produce observable results in specific capabilities, not just exist as a marketing adjective.

The 12 Criteria That Actually Separate SASE Vendors in 2026

These are ordered by differentiation impact, meaning how much variance we see across vendors in our data. A criterion where all 8 vendors score similarly is less useful for selection than one where the spread is wide.

Criterion 1: GenAI DLP Depth

Why it matters: Data shared with GenAI apps increased 30x in one year, from 250MB to 7.7GB per organization per month. 89% of enterprise GenAI usage occurs outside IT visibility.

What to evaluate:

• Prompt-side DLP (outbound) -- all 8 vendors score YES here; this is table stakes
• Response-side scanning (inbound) -- only 6 of 8 vendors score YES
• WebSocket and SSE streaming inspection -- only 1 of 8 vendors scores a full YES
• Desktop GenAI app coverage (ChatGPT Mac, Claude, Copilot) -- only 1 of 8 scores YES
• Mobile GenAI DLP -- only 2 of 8 score YES
• AI app catalog size -- ranges from 300 to 6,500+ across vendors

The data:

The 17-percentage-point spread between the top vendor (Zscaler at 87%) and the bottom tier (70%) translates directly into blind spots in your AI data protection. If your organization is a heavy GenAI user, this is the single most important criterion.

Aryaka's independent research confirmed a key technical gap: many DLP solutions bypass WebSocket messages entirely, fail to handle HTTP/2 and HTTP/3 traffic, and cannot detect sensitive data at the token level that LLMs transmit in 3-to-4-character chunks. Traditional pattern-matching DLP is not enough. Ask vendors whether they use Named Entity Recognition (NER) models and cosine similarity analysis for paraphrased content detection.

Full data: GenAI DLP Comparison

Criterion 2: Platform Unification (Not Just Feature Breadth)

Why it matters: 61% of organizations prefer unified single-vendor SASE. Forrester excluded Cisco from its 2025 Wave because management interfaces were not sufficiently unified. The deployment cost difference between a truly unified platform and a stitched-together portfolio is enormous.

What to evaluate:

• Single management console (truly unified, not SSO across separate portals)
• Single agent for all functions (SSE, DEM, endpoint posture)
• Unified policy model (define once, enforce everywhere)
• Consistent enforcement across branch, remote, and mobile
• Single data lake for analytics and reporting

How we measure it: PARTIAL rates across our comparison data reveal platform integration seams. When a vendor scores PARTIAL on a capability, it often means the feature exists but is not fully integrated into the unified platform. The higher the PARTIAL rate, the more stitching is visible.

There is a clear correlation between time-in-market as a cloud-native SASE platform and PARTIAL rate. Palo Alto and Zscaler, with over a decade of cloud-native development, show roughly half the PARTIAL rates of Fortinet and Check Point, which transitioned from on-premises appliance architectures more recently.

Dig deeper: PARTIAL Is the New NO

Criterion 3: Mobile and BYOD Enforcement

Why it matters: Microsoft reports that 80-90% of ransomware attacks originate from unmanaged devices. Users are 71% more likely to be infected on an unmanaged device. The BYOD security market is projected to reach $366 billion by 2029, growing at 34% annually. Yet only 67% of businesses have formal BYOD security policies.

What to evaluate:

• TLS inspection on managed mobile devices
• TLS inspection on unmanaged BYOD (no MDM)
• Certificate-pinned app handling
• iOS-specific limitations (Apple imposes strict constraints)
• Android-specific support across OS fragmentation
• Agentless access for contractor/partner devices

The data:

Our TLS Inspection on Mobile comparison tested 10 specific checks. No vendor scores above 60%.

Every single vendor scores PARTIAL or NO on TLS inspection without MDM. Not one can deliver full TLS decryption on unmanaged mobile devices. When a vendor tells you mobile inspection is "supported" during a sales call, this is the reality behind that claim.

The PARTIAL answers here typically mean the vendor can do basic URL filtering or DNS-level inspection on mobile, but cannot perform full TLS decryption and content inspection without MDM profiles or device management enrollment. For organizations with large BYOD mobile populations, this is the difference between real security and security theater.

Full data: Mobile TLS Inspection Gap

Criterion 4: Agentic AI and MCP Security

Why it matters: Palo Alto Networks reports attack timelines have compressed from an average of 10 days to as little as 2.4 hours. AI agents operating with delegated permissions are the next major attack surface. Gartner projects 60% of all software interactions will be agent-driven by 2028.

What to evaluate:

• MCP server discovery and inventory
• Agentic AI workflow visibility (which agents connect to which systems)
• Inline MCP traffic inspection and policy enforcement
• Non-human identity management for AI agents
• Shadow agent detection (unauthorized AI tools connecting to enterprise systems)

The data:

This is the fastest-moving criterion on this list. Most capabilities shipped within the past six months. The distinction between "production" and "early" matters enormously here. Cisco, Palo Alto, and Zscaler have had months of production hardening. Fortinet's MCP visibility shipped in March 2026, literally weeks old.

Cisco's intent-aware inspection, which evaluates the purpose behind agentic messages rather than just scanning the content, is unique in the market. No other vendor offers this capability. If agentic AI security is a priority, Cisco deserves a look that its Gartner "Challenger" placement might not suggest.

Full data: AI Security Controls Comparison

Criterion 5: Threat Prevention Depth

Why it matters: Over 95% of web traffic is now encrypted, and 87% of threats hide in encrypted channels. Basic URL filtering catches the easy stuff. The hard question is whether your SASE platform can detect advanced threats inside encrypted, streaming, and evasive traffic.

What to evaluate:

• Inline malware scanning (dual-engine vs. single)
• Cloud sandboxing for unknown files
• IPS/IDS with behavioral analysis
• C2 (command and control) detection
• Browser isolation for high-risk sites
• DNS security and tunneling prevention

The data: Our Threat Prevention comparison covers 12 checks.

The spread here is narrower than in GenAI DLP, which means threat prevention alone will not decide your evaluation. But the details within each vendor's approach matter. Zscaler runs two scanning engines simultaneously (Anti-Malware and NG Anti-Malware from SentinelOne), both operating at wire speed with sub-millisecond verdicts. That architectural choice is hard to replicate with a single-engine approach.

Independent testing from CyberRatings.org, using Keysight's tools with real-world attack scenarios, provides a third-party validation layer that vendor datasheets cannot. Ask vendors whether they have submitted to independent testing and request the results.

Full data: Threat Prevention Comparison

Criterion 6: Private Backbone and Real Network Performance

Why it matters: Many SASE providers route traffic over the public internet between their PoPs with no performance SLA. For organizations replacing MPLS (which can save up to 40% on transport costs), the backbone architecture determines whether SASE performance matches or degrades the user experience.

What to evaluate:

• Percentage of inter-PoP connectivity on owned vs. leased infrastructure
• Private backbone vs. public internet transit
• 95th-percentile latency (not average) with all security functions enabled
• Availability SLA (target: 99.95%+)
• Geographic coverage relevant to your user locations

RFP question that vendors hate (from Netify's research): "State the percentage of inter-PoP connectivity owned versus leased. Provide traceroute evidence between key city pairs." Most vendors cannot answer this cleanly because their "private backbone" claims often obscure reliance on public internet and tier-1 provider transit.

Vendor architecture models:

• Route-based with private backbone (Cato): Entire stack built as a converged service with a private global backbone that eliminates public internet unpredictability. Zero-touch deployment at branches.
• Proxy-based with massive scale (Zscaler): Terminates connections at cloud edge for deep inspection. Forrester noted "PoP saturation issues" in some regions.
• Hybrid approach (Palo Alto): Requires more networking expertise (BGP, IPsec, routing domains) but offers granular control. Forrester noted the platform "needs more backbone/PoP standardization."
• Global edge network (Cloudflare): Built on one of the world's largest CDN networks. Strong edge performance, but enterprise SASE features are newer.

Full data: Private Backbone Comparison | Global PoP and SLA Comparison

Criterion 7: True Zero Trust (Beyond Marketing)

Why it matters: 79% of organizations plan to implement SSE (the security component of SASE) within 24 months. 46% begin with ZTNA specifically. But "zero trust" has become so overused that Forrester created an entire Wave dedicated to separating real zero trust platforms from branded checkboxes.

What to evaluate:

• Per-application micro-segmentation (not just network-level)
• Continuous device posture assessment (not just at login)
• Identity-based policy enforcement across all access types
• Application discovery for private apps (can the platform find apps you do not know about?)
• Agentless browser-based access for third parties and contractors
• Universal ZTNA covering both remote and on-campus users

What the analysts say: Forrester's 2025 Zero Trust Platforms Wave rated Palo Alto Networks highest on Current Offering, scoring a perfect 5 in 11 of the evaluated criteria. The leaders were Palo Alto, Microsoft, and Check Point. Notably, several SASE vendors that lead Gartner's Magic Quadrant placed lower in Forrester's zero trust evaluation, highlighting that SASE leadership and zero trust depth are not the same thing.

This disconnect matters for evaluation. If zero trust is your primary driver, the Forrester Zero Trust Wave should carry more weight than the Gartner SASE Magic Quadrant in your scoring.

Full data: ZTNA and Private Apps Comparison

Criterion 8: Data Sovereignty and Compliance Architecture

Why it matters: Gartner predicts that by 2027, 40% of AI-related data breaches will be caused by improper cross-border GenAI use. Over 60% of enterprises are expected to adopt Sovereign SASE architecture by 2026. US hyperscalers control over 70% of the EU cloud market, which puts them under CLOUD Act and FISA jurisdiction. DORA entered full enforcement in January 2025. NIS2 went effective October 2024.

What to evaluate:

• Data residency controls (can you guarantee data stays within specific borders?)
• Local key management (who holds the encryption keys?)
• Logging and audit retention capabilities
• Sovereign deployment options (on-prem or local-cloud PoPs)
• Compliance reporting for DORA, NIS2, GDPR, and sector-specific regulations

This criterion has moved from "nice to have" to "deal-breaker" for organizations operating in the EU, financial services, and healthcare. Sovereign SASE, where the control plane and data plane remain within jurisdictional boundaries, is no longer a niche requirement.

Full data: Data Sovereignty Comparison | Compliance Certifications Comparison

Criterion 9: Total Cost of Ownership (Beyond Per-User Pricing)

Why it matters: Organizations underestimate real cybersecurity costs by 30-60%. The per-user-per-month number that vendors lead with ($15-40 is the Gartner benchmark for comprehensive SASE) hides professional services costs (10-20% of first-year spend), enterprise support tiers (20-25% annually), add-on licensing for features like DEM, advanced DLP, and browser isolation, and bandwidth-based charges at branches.

What to evaluate:

• All-in per-user pricing including every feature you need
• Professional services requirements for deployment
• Support tier costs and response time SLAs
• Data egress and log export fees (prevents vendor lock-in through "data hostage")
• Contract flexibility (multi-year discounts vs. lock-in risk)
• Exit costs and data portability guarantees

Directional TCO positioning from market analysis:

• Cato: Consistently cited as lowest TCO due to converged platform with simplified licensing. Branch pricing based on last-mile bandwidth (50 Mbps starts around $200/location).
• Cloudflare: Free tier for up to 50 users; paid tier starts at $7/user/month but add-ons accumulate (Remote Browser Isolation adds $10/user, logs add $1/GB beyond 10GB).
• Palo Alto: Cited as highest TCO due to fragmented licensing across Prisma Access, Cortex, and Strata Cloud Manager, plus integration complexity.
• Zscaler: Modular pricing offers flexibility, but consumption-based components can create unpredictable quarterly bills.

Here is the uncomfortable truth about SASE pricing: the cheapest option on paper frequently becomes the most expensive in practice. A platform that requires three months of professional services to deploy, plus additional modules for features you assumed were included, will cost more than a pricier platform that works out of the box.

The best RFP question on cost (from Netify): "Include a most-favored-nation pricing clause and require full log export API documentation for 24 months of security data upon termination." This prevents both overpaying and data lock-in.

Criterion 10: Digital Experience Monitoring (DEM)

Why it matters: 93% of organizations consider DEM crucial for their SSE deployment. 33% rate it "very important." When SASE platforms sit in the path of all user traffic, they have unique visibility into end-to-end application performance. The question is whether that visibility translates into actionable diagnostics.

What to evaluate:

• End-to-end path visualization (hop-by-hop from user to application)
• Real-time performance scoring per user and per application
• Automated root cause analysis (is it the network, the endpoint, or the application?)
• Historical baselining for trend detection
• Integration with ITSM tools for ticket automation

DEM is one of those capabilities where "PARTIAL" answers are common because many vendors offer basic metrics (latency, packet loss) without the diagnostic depth needed to actually resolve issues. During your POC, test a real performance degradation scenario and evaluate how quickly each vendor's DEM tool identifies the root cause.

Full data: Digital Experience Monitoring Comparison

Criterion 11: Post-Quantum Cryptography Readiness

Why it matters: NIST has set 2030 as the deadline for deprecating RSA and ECC cryptography. The U.S. CNSA 2.0 framework calls for migration to quantum-resistant algorithms beginning in 2025. This is not a 2035 problem. Organizations starting SASE deployments today will still be running them when quantum threats become real.

What to evaluate:

• Hybrid TLS support (classical + post-quantum key exchange)
• IPsec with quantum-resistant key encapsulation
• Crypto agility (can the platform upgrade algorithms without rearchitecting?)
• PQC standards compliance (ML-KEM, ML-DSA per NIST)
• Timeline for full PQC migration

Current state: Cloudflare is the only SASE vendor with standards-compliant post-quantum cryptography deployed in production, implementing hybrid ML-KEM across their entire platform. Over 60% of human-generated TLS traffic to Cloudflare's network is currently protected with hybrid post-quantum methods. Every other vendor is in various stages of planning or early implementation.

This criterion is a tiebreaker, not a primary decision driver in most evaluations today. But if you are selecting a platform you will run for 5+ years, PQC readiness signals forward-looking engineering investment.

Full data: Post-Quantum Readiness Comparison

Criterion 12: Ease of Deployment and Time to Value

Why it matters: Legacy SASE migrations typically take 18 months for large organizations. Cloud-native platforms have compressed this to 4-6 weeks in documented cases. That difference directly impacts your security exposure window. Every month spent deploying is a month where legacy controls remain your only defense.

What to evaluate:

• Agent deployment model (single agent vs. multiple)
• Branch onboarding process (zero-touch vs. manual configuration)
• Policy migration tools (from existing firewalls, proxies, VPNs)
• Time-to-first-value (how quickly can you protect the first cohort of users?)
• Ongoing management complexity (how many FTEs does the platform require?)

Forrester found that professional services from leading vendors reduced implementation time by 50% or more. But the need for professional services itself is a signal. Platforms that require specialist networking knowledge (BGP, IPsec, routing domains) for basic deployment are implicitly more expensive and slower to operationalize than platforms designed for security-team-led deployment.

Full data: Ease of Deployment Comparison | Unified Management Comparison

How the 8 Vendors Map to These Criteria

Every SASE evaluation comes down to trade-offs. No vendor leads on all 12 criteria. Here is where each vendor's strengths and limitations fall, based on our comparison data.

Palo Alto Networks

Analyst position: Gartner Leader (3rd consecutive year). Forrester Leader. Forrester Zero Trust Leader (highest score).

Strongest criteria: Platform unification (15% PARTIAL rate, lowest), Zero Trust depth (perfect Forrester scores in 11 criteria), Agentic AI (production-grade inline MCP enforcement), AI app catalog (5,000+ tracked).

Weakest criteria: Mobile TLS (30%, lowest score), Ease of deployment (Forrester notes "most complex to deploy"), TCO (cited as highest due to fragmented licensing).

Best fit: Large enterprises with deep networking expertise who prioritize security depth over deployment speed.

Zscaler

Analyst position: Gartner Visionary. Forrester Leader. SSE market share leader (34%).

Strongest criteria: GenAI DLP (87% YES, streaming protocol inspection leader, only vendor with full WebSocket DLP), Threat prevention (12/12), Platform unification (17% PARTIAL).

Weakest criteria: SD-WAN maturity (hardware added recently, networking options still limited per Forrester), Network backbone (PoP saturation issues noted), Mobile TLS (60% but still PARTIAL on key checks).

Best fit: Security-first organizations where DLP and threat prevention outweigh networking flexibility.

Netskope

Analyst position: Gartner Leader. Forrester Leader. #1 in 3 of 4 Gartner Critical Capabilities use cases.

Strongest criteria: GenAI DLP (83% YES, patented instance-awareness distinguishes corporate vs. personal AI accounts), DEM, Unified management (praised by Forrester for intuitive interface), Agentic AI (most granular MCP traffic decoding).

Weakest criteria: Mobile TLS (50%), SD-WAN branch throughput (GRE capped at 1 Gbps, IPsec at 250 Mbps per Forrester).

Best fit: Organizations prioritizing data protection across SaaS and GenAI, especially those needing instance-level visibility.

Cato Networks

Analyst position: Gartner Leader. Forrester Strong Performer.

Strongest criteria: Private backbone (purpose-built global backbone with owned infrastructure), Ease of deployment (zero-touch branch onboarding, single console), TCO (consistently cited as lowest), Agentic AI (Aim Security acquisition).

Weakest criteria: GenAI DLP depth (70%), Enterprise browser and some DLP depth (noted by Forrester), Mobile TLS (50%).

Best fit: Mid-market and distributed enterprises prioritizing network performance, simplicity, and cost efficiency.

Cisco

Analyst position: Gartner Challenger. Excluded from Forrester SASE Wave (unified management gap).

Strongest criteria: Agentic AI (only vendor with intent-aware agent inspection, AI BOM), SD-WAN (31% market share leader, 52% growth in Q2 2025), Threat intelligence (Talos).

Weakest criteria: Platform unification (25% PARTIAL rate, management console fragmentation caused Forrester exclusion), GenAI DLP streaming (UNKNOWN on WebSocket), Mobile TLS (40%).

Best fit: Organizations already invested in the Cisco ecosystem, or those where agentic AI security is the top priority.

Fortinet

Analyst position: Gartner Leader (new in 2025). Forrester Strong Performer. SASE ARR: $1.15 billion.

Strongest criteria: Threat prevention breadth (FortiGuard, largest AI URL database at 6,500+), SD-WAN/branch (Gartner Critical Capabilities #1 for Secure Branch), Revenue momentum ($1.15B ARR, 25.7% growth).

Weakest criteria: Platform unification (31% PARTIAL rate, highest), GenAI DLP depth (70%), Mobile TLS (40%), Deployment complexity (on-prem heritage visible).

Best fit: Organizations with existing Fortinet infrastructure, or those where branch security and SD-WAN are the primary drivers.

Cloudflare

Analyst position: Gartner Visionary. Forrester Strong Performer.

Strongest criteria: Post-quantum cryptography (only vendor with production PQC), Desktop and mobile app DLP (only vendor scoring YES on both), Edge network performance (built on global CDN), Entry-level pricing (free for up to 50 users).

Weakest criteria: Agentic AI (still in beta), Enterprise DLP and compliance depth (noted as gap), Shadow AI detection (PARTIAL), Platform maturity for large enterprise (newer SASE entrant).

Best fit: Tech-forward organizations prioritizing future-proofing (PQC), or smaller teams starting with a cost-effective entry point.

Check Point

Analyst position: Gartner Niche Player. Forrester Zero Trust Leader.

Strongest criteria: Zero Trust depth (Forrester Leader alongside Palo Alto and Microsoft), Prompt-side AI scanning (GenAI Protect), Threat intelligence (ThreatCloud AI).

Weakest criteria: Platform unification (30% PARTIAL rate), GenAI DLP depth (70%), Sanctioned vs. unsanctioned AI differentiation (PARTIAL), AI app catalog size (300+, smallest).

Best fit: Security-centric organizations where zero trust architecture is the primary driver, especially those already using Check Point firewalls.

Building Your Evaluation Scorecard

Here is a practical framework you can use today. It is designed to avoid the two most common evaluation failures: treating all criteria as equally important, and accepting vendor self-reported scores without verification.

Step 1: Weight Your Criteria (Before Talking to Vendors)

Not all 12 criteria matter equally for your organization. Assign each criterion a weight from 1-5 based on your environment. A financial services company with heavy GenAI usage and EU data residency requirements will weight differently than a retail chain prioritizing branch connectivity and cost.

Example weighting for a GenAI-heavy enterprise:

Step 2: Score Using Independent Data (Not Vendor Claims)

For each criterion, score vendors on a 1-5 scale using independent sources:

• Our comparison data (200+ checks with evidence)
• Gartner Critical Capabilities scores (13 capabilities, 4 use cases)
• Forrester Wave scores (Current Offering, Strategy, Customer Feedback)
• CyberRatings.org independent test results
• Gartner Peer Insights customer reviews

Never score based solely on vendor datasheets. Fortinet's CISO Collective blog itself acknowledged that vendors "check boxes for features like CASB, dynamic load balancing, and ZTNA, but when one digs into the product, the feature isn't as comprehensive as advertised." If a vendor admits this about the market, take it seriously.

Step 3: Require Four Answers, Not Two

Ban checkmarks from your evaluation. Require vendors to provide one of four answers for every requirement:

• YES: Fully supported in production today
• PARTIAL: Supported with specific limitations (vendor must document every limitation in writing)
• NO: Not supported
• ROADMAP: Planned with a committed delivery date

This single change will transform your evaluation quality. In our experience, vendors who are forced to classify their own answers this way reveal 20-40% more PARTIAL responses than their marketing materials suggest.

Step 4: Build POC Test Cases from PARTIAL Answers

Every PARTIAL answer should become a specific test case in your proof of concept. Do not let vendors demo their best scenarios. Test the exact edge cases where they acknowledged limitations:

• Certificate-pinned apps on mobile
• WebSocket DLP on a ChatGPT conversation
• Desktop AI app inspection (Claude, ChatGPT Mac)
• Unmanaged BYOD device enforcement
• Policy consistency between branch and remote user

The POC is where PARTIAL answers reveal their true nature. A PARTIAL that works for your use case is as good as a YES. A PARTIAL that fails your specific scenario is functionally a NO, and that changes your scoring significantly.

Step 5: Demand References on Specific Capabilities

Do not ask for generic customer references. Ask for a customer who:

• Runs GenAI DLP in production with streaming inspection enabled
• Deployed mobile TLS inspection across BYOD devices without MDM
• Manages the platform with a security team of your size
• Operates in your regulated industry

If the vendor cannot produce a reference for a capability they claimed as YES, that answer should be downgraded to PARTIAL in your scoring.

The 5 Questions That Reveal More Than Any Checklist

After evaluating dozens of SASE deployments, I have found that five questions cut through more marketing than a 100-line RFP. Ask these in your first technical deep-dive with each vendor.

1. "Show me a DLP alert firing on a ChatGPT response streamed via WebSocket. Not the prompt. The response."

This tests streaming protocol inspection, which is the hardest DLP problem in 2026. If the vendor cannot demonstrate this live, their response-side GenAI DLP has gaps.

2. "Walk me through what happens when an employee pastes source code into Claude on their personal iPhone without your agent installed."

This tests the intersection of mobile, BYOD, and GenAI DLP. The honest answer for most vendors is: "We cannot inspect that traffic." Any vendor that claims full coverage here should prove it in a POC.

3. "How many separate portals does an admin need to configure a complete policy covering remote users, branch offices, and mobile devices?"

This tests true platform unification. The best answer is "one." If the vendor starts explaining how Portal A handles networking while Portal B handles security, you are looking at a stitched-together solution.

4. "What is your 95th-percentile latency with all security functions enabled between [your office location] and [your primary SaaS application]?"

Average latency numbers are meaningless. The 95th percentile reveals worst-case user experience. Vendors who cannot provide this number have not measured it, which tells you something about their performance engineering.

5. "If we terminate our contract in 18 months, what is the process and cost for exporting 24 months of security log data?"

This tests vendor lock-in. Data portability is one of the most overlooked evaluation criteria. Organizations that cannot export their logs are trapped, and vendors know it.

Where the Market Is Heading

Three trends will reshape these criteria by 2027.

Agentic AI security will move from "emerging" to "required." Seven of eight vendors shipped agentic AI capabilities in the past six months. Within 12 months, this will be as expected as CASB is today. Evaluate vendors on production maturity, not just feature announcements.

Post-quantum cryptography will become a compliance requirement. NIST's 2030 deadline is four years away. Procurement cycles are 12-18 months. Organizations starting evaluations in 2027 will need PQC readiness as a hard requirement, not a tiebreaker. Cloudflare's first-mover advantage here is significant.

Single-vendor SASE will become the default, not the aspiration. Dell'Oro projects 90% of the $17 billion market will be single-vendor by 2029. Gartner predicts 65% of new SD-WAN purchases will be part of single-vendor SASE by 2027. Multi-vendor architectures will not disappear, but they will increasingly require justification rather than being the default.

The vendors that close the remaining gaps in mobile TLS, streaming DLP, and agentic AI maturity will define the next generation of enterprise security. The organizations that evaluate on the criteria that actually matter, rather than the ones that vendors want you to focus on, will be the ones that avoid the expensive mistakes.

Explore the full data behind every criterion: All Comparison Topics

Methodology: Findings are based on SASECompare independent research across 26 comparison topics and 200+ capability checks. Analyst references include the Gartner Magic Quadrant for SASE Platforms (July 2025), Gartner Critical Capabilities for SASE Platforms (July 2025), Forrester Wave: SASE Solutions Q3 2025, and Forrester Wave: Zero Trust Platforms Q3 2025. Market data from Dell'Oro Group (Q2 2025), Cybersecurity Insiders SSE Adoption Report 2025, Zscaler ThreatLabz 2026 AI Security Report, and Netskope Cloud and Threat Report 2025. Vendor pricing data is directional and based on published benchmarks and independent analyst estimates. See individual comparison pages for full source citations on all vendor ratings.

Related Head-to-Head Comparisons

Evaluating specific vendors? See how they compare head-to-head:

• Cato Networks vs Zscaler
• Netskope vs Zscaler
• Palo Alto vs Zscaler
• Cisco vs Palo Alto
• Cato Networks vs Fortinet
• Cloudflare vs Netskope

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