Autonomous AI Due Diligence Agent
VERA is CleverChain’s autonomous AI Due Diligence Agent which performs end-to-end Customer Due Diligence and Enhanced Due Diligence on legal and natural persons, in full autonomy, in minutes per entity, calibrated to each user’s own due diligence policies and procedures.
Core functionalities
Comprehensive, end-to-end due diligence / KYC / KYB / TPRM
Predominant use cases
Customer onboarding (physical and legal entities), reviews, prospecting; EDD investigations; Third-party due diligence and risk assessment (eg supplier risk assessment)
Relevant for
Financial institutions (banks, insurances, payment companies); Industrial groups; Professional services (eg legal, compliance advisory)
Typical workflows it supports
Onboarding; Escalation; Reviews; Audit; Prospecting
Due diligence that understands the business.
What it does
From a minimal input (an entity name, or a registration number and jurisdiction), VERA validates registry information, researches the nature of business, reconstructs shareholder history and the ownership and control structure beyond registry filings, identifies significant events and company directors, performs multi-dimensional contextual screening, conducts a risk assessment against the user’s risk engine, and produces a time-stamped, fully cited report suitable for the CDD or EDD file. Every investigative step is logged and exportable for regulatory review. VERA also embeds contextual screening, meaning that sanctions, PEP, enforcement, adverse media and reputational signals are evaluated against geography, sector, role, chronology and network, with multi-attribute entity resolution across languages, scripts and transliterations, rather than name-against-list matching.
Point-in-time and continuous
VERA operates both at a point in time and continuously. The same engine performs event-driven and time-based monitoring, re-assessing entities as ownership, control, activity, network or reputation change.
Point-in-time and continuous
VERA operates both at a point in time and continuously. The same engine performs event-driven and time-based monitoring, re-assessing entities as ownership, control, activity, network or reputation change.
THE CHALLENGE
The structural gaps in KYC and KYB.
The unmet need that connects these problems is our multi-layer intelligence, consisting in the capability to understand a business rather than merely identify it, and to keep that understanding current, at a speed and consistency that manual investigation cannot match. The enforcement record, from NatWest to Barclays and others, consistently shows verified, registered customers whose activity was never understood.
The verification and KYB gap
The industry has invested heavily in business verification, confirming that a legal entity exists and that its registry details match official records. It has invested far less in business understanding: what a customer actually does, who controls it, and how its risk profile evolves. Verification is a snapshot of what a company is on paper at its last filing. KYB, as CDD and EDD for legal persons have always required, is the obligation to establish and maintain an evidence-based understanding of purpose, beneficial ownership and control, activity-based risk, and change over time. Most programmes stop at the first and treat it as the whole.
Dependency on a single provider
Most offerings tie the institution to one data vendor and, increasingly, to one underlying AI model. That dependency creates exposure on at least four fronts: contractual terms, performance, coverage, and the ability to customise. Through HELIX, our multy-layer contextual engine, VERA removes such dependency because data sources and models are both orchestrated and selected on a scenario basis. For data, the selection is driven by e.g. the type of assessment and the jurisdiction, while for models, by e.g. the activity to be performed and each model’s current measured performance. The result is scenario-based due diligence rather than a one-size-fits-all pipeline, and an architecture that is not held hostage to any single supplier’s roadmap, pricing or limitations. Last but not least, this also means that new data sources can be swiftly added at any time. For perspective, VERA is offered in two deployment models, both running on the same engine: full-stack, where CleverChain supplies data and intelligence; and intelligence-only, where the client supplies its own data sources and CleverChain supplies the intelligence layer.
Calendar-driven controls
Periodic review cycles treat a live business relationship as a series of snapshots, leaving risk that emerges between reviews undetected until the next scheduled date. VERA’s answer is continuous oversight on the same intelligence engine. For legal entities, it monitors e.g. registry and corporate status, nature of business, ownership and control, sanctions and enforcement, litigation, adverse media and reputational risks. For natural persons, it monitors e.g. role and network changes, multilingual adverse media, sanctions and watchlists, PEP status and close associates. Most importantly, the materiality of changes is interpreted in context rather than treated as a binary change, and workflows are triggered accordingly: a silent, timestamped update where a change is not material; an internal escalation backed by evidence where it is; and a client outreach workflow where action is required. Monitoring is both event-triggered and time-based, and configurable by segment, jurisdiction and product.
THE VERA DIFFERENCE
What sets the intelligence apart.
01 — HELIX multi-layer intelligence
Most offerings are built around one of two things: a data asset, or a model. The latter group includes the standalone large language model providers, whose tools answer a due diligence question by generating a response from a single model. VERA’s underlying engine (HELIX) is different in kind, as it operates as an orchestration layer that is agnostic to both data source and models. Data sources are selected and configured by scenario, while large language models are drawn from an ensemble on a best-fit-per-task basis, and any model in that ensemble is used only for the parts of an investigation where it genuinely outperforms, with primary-source evidence retrieved directly rather than generated. A standalone model has no access to gated registry or commercial data, no orchestration across sources, no policy-wiring, and no defence against the limitations or roadmap of the single provider behind it. This removes single-provider dependency and lock-in, and it means the engine improves as the whole data and model landscape improves, without re-platforming.
02 — Understanding beyond verification
VERA is designed to deliver the four obligations that separate genuine KYB from identity confirmation: purpose and intended nature of the relationship, beneficial ownership and control beyond the registry layer, an activity-based customer risk assessment, and monitoring calibrated to change. It tests declared activity against evidenced activity, maps control exercised through means other than majority shareholding, and surfaces group-level risk that entity-level checks in isolation cannot see. Network and ownership reasoning is a tangible example, traversal of the full ownership chain, including indirect and circular structures, and mapping of directorship and control networks across jurisdictions.
03 — Contextual screening
Leveraging LUMA, sanctions, PEP, enforcement and adverse media signals are re-evaluated in context (geography, sector, role, chronology and network), with multi-attribute entity resolution across languages, scripts and transliterations. The output is a graded, dated, cited narrative that includes positive and exculpatory evidence, not a hit or no-hit flag. VERA also leverages intelligence on entities for which no watchlist entry exists and can be configured reputational factors that are not univocal nor can be constrained within a list or table.
04 — Data ingestion in any form
VERA ingests internal and external documents in any format, including PDF registry extracts, client KYC files, financial statements and corporate filings, so that material becomes evidence inside the due diligence workflow rather than a separate, manual step performed alongside it. The user’s own internal data and third-party inputs are interpreted within the same investigation as registry and open-source data.
05 — An interactive investigation
Once a VERA report exists, it is not the end of the process. KIRA, CleverChain’s AI digital due diligence consultant, allows the user to interrogate and extend the report conversationally, whether on content already within the report or on external data introduced into the session. A finished report becomes an investigative workspace, the way a human analyst would expect to work, rather than a fixed document.
06 — Regulatory readiness by design
VERA is designed to meet regulatory expectations before they take effect across the jurisdictions we serve. In the EU, for example, VERA already maps to AMLA’s final draft Regulatory Technical Standards (RTS) on customer due diligence under Article 28(1) AMLR, which AMLA published on 1 October 2026 and submitted to the European Commission for adoption. That coverage includes multi-source verification against the reliability criteria (Art. 8); ownership and control structures (Art. 11); purpose and intended nature of the relationship (Art. 16); enhanced due diligence, including reputation, source of funds and source of wealth (Artt.21-23); targeted financial sanctions screening (Art. 25). The final draft asks obliged entities to judge, structure by structure, whether an ownership chain needs further investigation and, in high-risk cases, to understand the rationale behind it (Artt. 11(4) and 21(d)). That judgement depends on evidence that a registry extract, a screening match or a threshold-based UBO calculation cannot supply. VERA flags complexity elements, including entities in high-risk jurisdictions, across the full ownership chain. It tests for opacity through financial anomalies, operational substance, director and UBO patterns, offshore-leak exposure and activity-code mismatches. It records the indicators found and the rationale tested, so the obliged entity can document its assessment. Chartis Research recognised this capability in its Financial Crime and Compliance50 (FCC50) 2026, where CleverChain won the Shell Company Detection Category Award.
IMPACT
Clearer decisions. Stronger evidence. Faster remediation.
Qualitative benefits
Quantitative benefits
VERA’s measurable impact is evidenced by client deployments and by product performance. VERA produces a complete due diligence report in two to seven minutes per entity, depending on complexity and configuration, against the hours or days a complex manual investigation requires. Because the same engine runs at portfolio scale, it is directly relevant to the five-year back-book remediation window under Article 33 of the draft AMLA RTS, under which obliged entities must bring existing customers up to the new CDD standard on a risk-prioritised basis. Remediation work that would otherwise span months can be processed in days.