VERIDIC
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Trusted AI • Verifiable Compute • High-Risk Digital Processes

VERIDIC

A deep-tech platform for trusted AI and verifiable compute in high-risk digital processes.

VERIDIC integrates into existing AI systems and provides a verifiable answer to the question: why did the model make this decision, and can it be trusted? Which features supported the decision and which opposed it? Demonstration scenarios have already been implemented for ECG, ultrasound and risk analytics in post-release customs control.

Discuss a pilot deployment View prototypes

We are looking for a company or integrator interested in piloting VERIDIC within its own process, AI model or client solution.

Real-time computational trust control
Explainable risk and outcome explanation
Low-friction integration without rebuilding core systems
Problem

Automation is growing faster than trust in digital outcomes

The core market problem is not merely data processing, but demonstrable reliability of outcomes, especially in high-risk and regulated workflows.

Companies automate documents, AI workflows and decision-making, but still cannot guarantee trust in digital outcomes.

The cost of error is growing: fraud, manual review, regulatory pressure and unreliable digital artifacts.

Most existing solutions address only individual layers of the problem rather than creating a universal trusted-computation layer.

Impact for the client

  • manual review overhead
  • fraud / integrity risk
  • regulatory / audit pressure
  • high cost of error in digital processes
Solution

VERIDIC is a trusted and explainable AI layer for digital processes

It is not merely an AI service, but a technology layer operating at the level of the computational operation itself.

Advantage

Control at the level of the computational operation itself, rather than only at the interface, OCR or execution-environment level.

Advantage

Explainable output: the system shows why a case is risky and what specifically needs escalation.

Advantage

Suitable for document-intensive and high-risk scenarios: finance, medical technology, the public sector and critical infrastructure.

Advantage

Potential to scale from an applied product to a trusted AI and verifiable compute platform.

Product

First product: Document & Digital Artifact Verification

A fast path to a pilot and demonstrable ROI in document-heavy scenarios.

Document & Digital Artifact Verification

Automated verification of document structure, attributes, consistency and authenticity of documents and digital artifacts.

Fraud & anomaly detection

Detection of anomalies, editing traces, inconsistencies and suspicious cases before a decision is made.

Trusted AI for regulated workflows

Support for scenarios requiring explainability, traceability and risk control under regulatory requirements.

Client outcome

Less manual review, lower fraud risk, faster decision-making and improved risk screening quality.

Proof of capability

From an arithmetic principle to working demonstration scenarios

Three areas demonstrate VERIDIC's portability: time-series signals, medical imaging and regulated decision-making processes.

MEDTECH / ECG

ECG: explaining rhythm and signal morphology

Research prototype
49,273 cardiac cycles • Accuracy 0.9454

VERIDIC shows not only the ECG segment that influenced the decision, but also the contribution of clinically understandable RR features: beat prematurity, pause and rhythm context.

For class S, the explanation focuses on prematurity and shortened pre-RR; for class V, on QRS morphology and the post-QRS region.

✓ Signals + structured features
MEDTECH / ULTRASOUND

Ultrasound: auditing an existing model without retraining

Runtime-XAI for an existing ViT
BUSI • 780 images • Model accuracy 0.9397

VERIDIC was integrated into the forward pass of an already trained open-source model and generated a 14×14 patch-level influence map comparable with the expert lesion mask.

Demonstrates technology portability to an existing AI model and the ability to reveal the risk of a “right answer for the wrong reason.”

✓ No retraining required
REGTECH / CUSTOMS

Post-release customs control: procedurally clear risk screening

Architectural prototype
20,000 synthetic cases • 47 features

The scenario combines OSINT signals, VERIDIC interpretation, ONYX routing and the AIVANT document interface in an explainable risk-analysis workflow.

The output is a risk score, the source and trust level of each factor, a recommended action and a reproducible audit trail.

✓ API-ready pilot contour
Key demonstration • ultrasound

The AI answered correctly. VERIDIC showed that the reasoning requires review.

In a correctly classified example benign the existing model reported 97.3% confidence; however, VERIDIC showed that the model made its decision for questionable reasons. For an integrator, this matters more than another high accuracy score: the technology helps reveal a model that can be right for the wrong reasons.

A research demonstration of explainability for an existing model; it is not a medical conclusion or autonomous diagnosis.
97.3%model confidence in benign
0.010EIL: importance within the mask
0pointing game: maximum outside the mask
0.023top-q overlap with the mask
Readiness transparency: the ECG and ultrasound prototypes demonstrate runtime-XAI feasibility; the ultrasound mode in the current software implementation is resource-intensive and requires optimization for industrial deployment. The customs scenario has been tested on synthetic data and is intended for a closed pilot, not as a claim of achieved impact in a real system.
Differentiation

Not another heatmap, but an AI decision audit workflow

VERIDIC does not have to replace known XAI tools. Its investment thesis is to bring explainability and data provenance into a runtime workflow suitable for audit and response.

Approach
What it provides
Limitation for a high-risk process
Role of VERIDIC
LIME / SHAP
Post-hoc assessment of feature influence after a prediction is produced.
Useful for analysis, but the explanation is formed by an external procedure.
Context and influence accompany computation at runtime; the goal is an audit trail for a specific decision.
Grad-CAM / saliency
A visual attention map for images.
Shows attention regions, but by itself does not record data provenance or a response procedure.
In the ultrasound prototype, patch-level contribution is compared with an expert mask; in ECG, RR features are additionally explained.
TEE / confidential computing
Protection of the execution environment and confidentiality.
Does not answer why the model made a particular decision.
Complements the protected environment with explainability, data provenance and runtime integrity at the result level.
Practical value for the partner: VERIDIC helps determine not only what answer the model produced, but whether the grounds for that answer deserve trust — before the decision is used in a critical process.
Market

New market: High-Assurance AI with built-in arithmetic protection

VERIDIC can be positioned as a trusted AI platform for regulated workflows and critical digital processes.

FinTech

scoring, anti-fraud, document verification and counterparty analysis

MedTech

protection of diagnostic AI from artifacts and failures

Enterprise / EDMS

verification of documents and digital processes

Gov / Critical systems

trust in digital outcomes and resilience to anomalies

TAM

$2.30B → $12.35B

Intelligent Document Processing market, 2024–2030

SAM

Regulated workflows

identity verification, anti-fraud, compliance, explainable AI

SOM

$40k → $1.28M

revenue plan for the first three years

IP status

Rospatent

the VERIDIC application is undergoing formal examination

Business model

Monetization from pilot to platform

VERIDIC scales from a focused product to a trusted and secure AI platform.

Enterprise SaaS / license
API / usage-based pricing
On-premise / private deployment
Strategic integration / platform partnerships
Call to action

Seeking a pilot deployment site and partners for scaling

We are looking for a company or integrator interested in piloting VERIDIC: connecting it to an existing AI model or digital process, generating explainable audit reports and evaluating the practical value of the technology. The most promising areas are banks, financial technology, document-intensive processes, medical technology and other critical digital systems.

Offer a pilot site Discuss investment
anti-fraud trusted AI document verification verifiable compute

MedTech audit pilot

Connection to an existing image or signal model and generation of reports showing which regions and features influenced the decision.

Document / fraud pilot

Verification of documents and digital artifacts with risk explanation and factor traceability.

RegTech decision-support pilot

A closed-loop risk scoring environment with an audit trail, routing of borderline cases and secure API integration.

Contact

Vitaly Gryzunov

viv@veridic.ru

Investment thesis

VERIDIC is a bet on a new trusted AI infrastructure layer: not superficial automation, but trust in the outcome of the digital process itself.

IP status

The VERIDIC invention application is undergoing formal examination at Rospatent.