Didit vs Neurotechnology: hosted KYC and MegaMatcher ID compared
Blog post from Didit
Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.
Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.
This company's pages remain public, but its content is excluded from normalized aggregate trends. Unfiltered raw trends and advanced filtering are available to Accelerate and Lead accounts.
Didit is presented as a hosted onboarding platform offering a core KYC workflow priced at $0.33 per successful check, combining document verification, passive liveness, face matching, and device/IP analysis, while additional AML screening, transaction monitoring, KYB, database checks, national digital IDs, and review services carry separate charges. The material contrasts this model with Neurotechnology’s MegaMatcher ID, which is described as an SDK and on-premises web-service product requiring customers to operate licensing and server infrastructure, rather than a hosted end-to-end KYC service. Didit cites certifications for passive liveness, security standards, broad document coverage, customer adoption, and results from a Spanish financial sandbox, while noting that these findings concern specific tests rather than provider-wide comparative performance. Illustrative budgets show how KYC, AML, manual review, and transaction monitoring costs can scale with user and transaction volumes, with exclusions for taxes, subscriptions, discounts, and optional modules. The text also outlines a staged migration approach involving workflow rebuilding, historical-record imports, webhook and case-management configuration, pilot traffic, and agreed performance thresholds, emphasizing that teams should validate evidence, review requirements, and total scope before replacing an existing biometric or onboarding system.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| MCP | 4 | 4,439 | 399 | 125 | -63% |
| AI Coding Assistant | 3 | 814 | 184 | 89 | -58% |
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