ETALON AI
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ETALON PRODUCTS & EXPERTISE

Artificial intelligence you can manage.

ETALON AI brings together products, training and an engineering approach to AI adoption. We start with a business task, test the solution in a pilot and assess results against clear quality criteria.

01 / AI SECURITY

Generative AI security

We address the AI lifecycle from data sources and model testing to user requests and agent actions. The assessment covers the model, connected knowledge base, tools and access rules.

  • Inventory of AI assets, data sources and available tools.
  • Tests for prompt injection, instruction bypass and confidential data exposure.
  • RAG and agent scenario testing, with risk prioritisation.
  • LLM request controls, sensitive data masking, event logs and human oversight for critical actions.
What the client receives

A risk map, test scenarios, findings report and a security improvement plan.

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02 / DEVSECOPS

Secure development and infrastructure

We embed security from code to operations. Findings feed back into development tasks, while software composition and artifact provenance remain traceable.

  • Source code, open-source component, licence and secret checks.
  • Mobile application assessment and protection of packaged builds.
  • Secure Git, trusted artifact storage and CI/CD checks.
  • A consolidated view of vulnerabilities, prioritisation, build admission rules and remediation tracking.

Tool capabilities

Code analysisDependencies and licencesMobile securityAI testingVulnerability managementSecure GitArtifact registryApplication protectionLLM security gateway
What the client receives

An agreed secure development system: tools, policies, responsibilities and reporting tailored to the company.

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03 / AI TRANSFORMATION

Team training and AI transformation

Training is built around the client’s workflow. Teams use their own materials, create a solution during the programme and learn how to assess and develop it independently.

  • Use AI: task definition, prompting, documents, reports, analytics and role-based assistants.
  • Build agents: connect tools, spreadsheets and events with clear permissions and action rules.
  • Create systems: multiple agents and people, distributed roles, shared memory and result checks.
  • Validate use: quality criteria, real-work scenario tests and feedback-driven improvement.
What the client receives

Working templates, an assistant or agent workflow for the selected task, and a team able to maintain it.

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04 / AI PORTFOLIO · ANALYTICS

AI portfolios and risk analysis

We research algorithmic portfolio approaches: market signals, changes in asset weights and risk limits. The methodology is explained through comparable historical scenarios and discussion of model assumptions.

  • Analysis of market signals and changes in risk.
  • Design and testing of portfolio model rules and limits.
  • Comparison of approaches over the same data history, with assumptions and costs examined.
  • Methodology demonstrations and reviews of drawdowns and historical test results.
What the client receives

An understanding of model logic, limitations and risk assessment criteria before deciding how to use it.

This financial analytics area is presented separately from construction solutions. Historical test results do not guarantee future returns. Terms for applying financial products are considered separately.

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One task. A measurable pilot. Scale what works.

We agree on data, access, automation boundaries and success criteria before starting. The pilot informs the decision on further deployment.

  1. 01

    Task

    Define the process, constraints and intended outcome.

  2. 02

    Pilot

    Use agreed data and real business scenarios.

  3. 03

    Assess

    Check quality, risks and practical suitability.

  4. 04

    Scale

    Transfer knowledge and expand the working system.