Research Methodology – AI and Cybersecurity: SEA Enterprise Vendor Intelligence Ledger 2026
This edition marks a structural shift in Logic Lock Group’s AI and Cybersecurity series: alongside the market-level threat landscape analysis carried since Q2 2026, this edition introduces direct vendor-by-vendor evaluation — bringing regulatory compliance grading and AI and cybersecurity intelligence together in a single vendor-by-vendor evaluation framework for the first time. This page documents our full cybersecurity vendor scoring methodology in AI age, so procurement teams, security & technology leaders, and research consumers can evaluate the work on its own terms.
The Four Flagship Questions in Cybersecurity Vendor Scoring
Rather than a composite ranking, the ledger is organised around four flagship questions that go beyond feature checklists to the decisions security and procurement leaders actually need to make:
- Where does your security actually live? — a direct assessment of data residency, sovereign-deployable infrastructure, and cross-border processing exposure across each evaluated vendor.
- Is what you already have good enough? — an evaluation of whether current vendor relationships meet the bar regulators and threat conditions now demand, rather than assuming past procurement decisions remain sound.
- If the agentic SOC works, why are incident-response retainers growing? — a look at the gap between AI-driven security automation claims and observed enterprise recovery behaviour.
- The ungoverned AI problem, extended — assessment of shadow AI exposure and the governance gap opening as enterprise AI adoption outpaces internal oversight.
Two-Axis Scoring Model
Our vendor scoring methodology has a simple rule: every vendor is scored on a 0–5.0 scale across two independent axes — SEA Fit and AI Readiness — rather than reduced to a single composite number. Buyers can see precisely where a vendor genuinely leads and where it doesn’t, without a blended score masking the trade-off between strong regional presence and strong AI capability. Neither axis is optional reading: a vendor can score well on one and poorly on the other, and the report is built so that distinction stays visible rather than averaged away.
Illustrative placement only — for each vendor’s actual scored position, see the Ledger.
SEA Fit
SEA Fit measures a vendor’s operational deployability across the six markets covered by the report — not brand presence or regional marketing claims, but whether the vendor can actually be deployed, supported, and held to account inside Southeast Asia’s regulatory and operating conditions. It is itself a composite of four weighted components:
| Component | Weight | What It Covers |
|---|---|---|
| Regulatory & Residency Fit | 30% | Alignment with each market’s data residency and regulatory requirements — such as Singapore’s MAS Technology Risk Management Guidelines or Vietnam’s newly effective Law on Artificial Intelligence — including verified in-country infrastructure where claimed |
| Talent-Gap Fit | 25% | Whether the vendor’s delivery model accounts for the region’s cybersecurity talent shortage, rather than assuming enterprise-side staffing that doesn’t exist |
| Delivery Layer | 25% | The strength and maturity of the vendor’s regional partner, channel, and managed-service delivery layer |
| Threat Relevance | 20% | How directly the vendor’s capability maps to the threat patterns actually observed across SEA markets, rather than a generic global threat model |
AI Readiness
AI Readiness is not a single measure of “how much AI” a vendor markets. Each vendor’s AI capability is decomposed across three weighted dimensions, ordered from most to least verifiable:
| Dimension | Weight | What It Covers |
|---|---|---|
| AI-Analytical | 35% | AI as the detection and prioritisation engine itself — the oldest and most verifiable of the three dimensions |
| AI-Operated | 40% | Agentic execution: the degree to which AI autonomously handles triage, investigation, and remediation rather than assisting a human analyst |
| AI-Securing | 25% | Governance of the customer’s own AI estate — models, agents, and MCP traffic — rather than the vendor’s own AI features |
Evidence Grades
Every score is capped by the strength of evidence behind it — a higher claimed capability cannot outrank the quality of proof supporting it. Four evidence grades are applied consistently across all vendors and both axes:
| Grade | What It Means | Score Cap |
|---|---|---|
| A | Independently observed or audited | 5.0 |
| B | Vendor-published operational average | 4.5 |
| C | Best-case “up to” ceiling claimed by the vendor | 3.5 |
| D | Roadmap or preview capability — shipped substance only counts toward the score | — |
This means a vendor’s marketed capability and its scored capability can diverge — deliberately. A roadmap feature, however impressive, does not score as though it were already in production.
Three-Tier Deployment Taxonomy
Every vendor is mapped onto a three-tier deployment taxonomy, used consistently across all six markets as a shortlist structure for regulated buyers:
- Sovereign-deployable platforms and verified in-country services — evaluated first, where they exist
- The storage-processing split — examined explicitly for every vendor, not assumed from a data-residency claim alone
- Managed services delivery by local or regional MSSPs — assessed where direct platform deployment isn’t viable
Vendor and Market Coverage
The Ledger covers 18 vendor entries in total across five categories, plus spotlight and regional vendors — spanning all six Southeast Asian markets: Singapore, Indonesia, Thailand, Malaysia, Vietnam, and the Philippines. Of these, 13 vendors are fully scored against both axes of the two-axis model above; the remaining entries are covered as spotlight or regional context rather than carrying a full SEA Fit / AI Readiness score. Comparisons on the quadrant, and claims like “only one vendor clears both bars,” refer specifically to that fully-scored set of 13 — not the full 18-entry roster.
Research Cut-Off
All assessments in the Ledger reflect information available as of 20 July 2026. Developments after this date are not reflected unless explicitly noted. The next edition will carry an updated research cut-off date.
Publication Cadence
The AI and Cybersecurity series continues to publish on a quarterly cadence. From this Ledger onward, each edition combines updated threat landscape analysis and regulatory developments with direct vendor-by-vendor evaluation, superseding the separate Regulatory Compliance vendor assessment methodology for markets covered in both series.
