Diligent

What do they actually do

Diligent sells configurable AI agents that automate routine KYC/AML tasks for fintechs, payments companies, and banks. Common workflows include investigating sanctions/PEP/adverse-media screening alerts, verifying identity/business documents, and running merchant or entity due-diligence checks. Customers connect Diligent via API/portal and upload their own policies and decision rules so the agent applies institution-specific logic and produces auditable outputs with reasons and evidence trails (site, YC profile).

In production, the agent opens cases (e.g., alerts), reads hit details and linked sources, searches the web to enrich context, and returns a recommended disposition with structured reasoning. Humans stay in the loop during rollout, and the company positions deployments as quick to start (“hours or days”). Diligent says it integrates with major screening providers (e.g., LexisNexis, World-Check, Dow Jones) and emphasizes enterprise data handling (no training on customer data, siloed storage, SOC2/ISO/GDPR posture). Public materials show an early-stage team and pilots/early production with references such as Alma’s merchant-onboarding case study; YC copy also claims daily use by global banks and S&P‑500 firms (company claims) (site, security, Alma case study, YC profile).

Who are their target customer(s)

• Compliance analyst at a mid-stage fintech handling KYC/AML alerts: High volumes of sanctions/PEP/adverse-media hits and false positives require manual review, creating backlogs and slowing onboarding; they need to cut routine work while keeping auditable, policy-aligned decisions (site, case study).
• Financial-crime/AML team at a bank: Must meet regulator and internal audit expectations while processing large alert volumes from legacy tools; scaling typically requires headcount growth and can lead to inconsistent dispositions without better automation (YC profile, site).
• Merchant-onboarding/underwriting team at a payment processor or acquirer: Manual merchant and business checks slow approvals and risk lost deals; they need faster, consistent due-diligence with documented reasoning for audits (site, case study).
• Operations manager at a marketplace or high-growth payments company: Hiring/training analysts is expensive and slow; they want safe automation for routine verifications so analysts can focus on complex cases (about, site).
• Enterprise compliance/risk officer evaluating vendors: Requires strong security controls, data separation, and attestations (SOC2/ISO/GDPR) plus explainable audit trails before approving AI in regulated workflows (security, about).

How would they acquire their first 10, 50, and 100 customers

• First 10: Run tightly scoped paid pilots (8–12 weeks) to automate a single L1 task like screening alert remediation, prove ROI with KPIs (time-per-alert, auto-close rate), and convert references using Alma’s case study, YC intros, and a partner co-sell with a screening vendor; reduce friction with a fast-start pack and an exportable audit pack (case study, YC profile, site).
• First 50: Add an SDR/AE pair and a standardized pilot playbook; scale pipeline via verticalized collateral, short product videos, ROI calculators, sandbox demos, and security FAQs, while deepening referral/integration agreements and co-marketing with screening vendors to source qualified pilots (site, security).
• First 100: Stand up an enterprise sales motion (RFP library, SLAs, pen-test/attestation summaries, single-tenant options) and channel programs with SIs/resellers; expand internationally with localization and regulatory messaging, and use marquee pilots plus co-sell agreements to win larger banks and processors (security).

What is the rough total addressable market

Top-down context:

The AML software market is estimated at roughly $1.7B in 2024 with projections to ~$4.2B by 2030; KYC/sanctions screening is a key subsegment within this spend (Grand View Research). Separately, industry analysts peg RegTech overall at ~$19.5B by 2026, underscoring a large compliance-automation budget pool (MarketsandMarkets).

Bottom-up calculation:

Focus on ~3,000 near-term targets (mid‑market fintechs, PSPs/acquirers, digital banks, and bank business units) with average $150k ARR for L1 screening/doc/merchant workflows implies a ~$450M initial TAM, expanding with additional agent types and geographies.

Assumptions:

• Targetable institutions (global mid-market fintechs, PSPs, and bank units) ≈ 3,000 near term.
• Average contract for L1 automation across one to two workflows ≈ $150k ARR, priced by alert volume/automation rate.
• Expansion to more workflows and regions increases ARPU and eligible accounts over time.

Who are some of their notable competitors

• Silent Eight: AI-based name screening alert adjudication used by large banks; overlaps directly on sanctions/PEP alert remediation.
• ComplyAdvantage: Sanctions/PEP/adverse media data and screening with alert management; an incumbent data + screening alternative.
• Napier AI: AML platform with screening, transaction monitoring, and case management; competes on alert review workflows.
• Lucinity: AML investigations platform with an AI copilot that speeds analyst reviews and SAR drafting; overlaps in analyst workflow automation.
• Unit21: No-code AML monitoring and case management; while not a screening data provider, it’s an alternative for building automated compliance workflows.